DEV Community: Skillselion

What improve-claude-md keeps, wraps and deletes in your CLAUDE.md

Skillselion — Sun, 11 Oct 2026 10:03:50 +0000

improve-claude-md is a HumanLayer skill that rewrites a CLAUDE.md so task-specific rules sit inside <important if="..."> blocks. Project identity, the project map and the tech stack stay as plain markdown. Rules a linter can enforce, code snippets and vague advice get deleted. All commands are kept, wrapped in one block. In the skill's own example, six of eight coding rules are deleted.

We run Skillselion, an independent directory of agent skills, not affiliated with Anthropic, OpenAI, Cursor or HumanLayer. For this post we read the skill's SKILL.md at commit 653b6411 of humanlayer/skills (5,182 GitHub stars, MIT, last push Oct 8, 2026, per the GitHub API on Oct 11, 2026). The file is 1,489 words and last changed on Mar 18, 2026. We did not run the skill, so everything below is what the file tells the agent to do.

What problem does improve-claude-md claim to solve?

The skill opens with a claim about Claude Code itself. It says Claude Code injects a system reminder with every CLAUDE.md, and it quotes that reminder as:

"this context may or may not be relevant to your tasks. You should not respond to this context unless it is highly relevant to your task."

Source: improve-claude-md/SKILL.md, "Core Problem"

From there the skill argues that a file full of rules that do not apply to the current task teaches the model to skip the whole file. We could not confirm the quoted reminder in Anthropic's documentation. The Claude Code memory docs do agree on the direction. They tell you to target under 200 lines per CLAUDE.md and say longer files reduce adherence. The same page does not mention <important if>, and its own answer for partly relevant instructions is path-scoped rules. So treat the tag as a prompt-writing convention from HumanLayer.

What stays as plain markdown in a CLAUDE.md?

The skill leaves three things unwrapped at the top of the file: a one-line project identity, the directory map, and the tech stack condensed to one or two lines. Its test for anything else is short:

"The rule of thumb: if it's relevant to 90%+ of tasks, leave it bare. If it's relevant to a specific kind of work, wrap it."

Source: improve-claude-md/SKILL.md, "1. Foundational context stays bare, domain guidance gets wrapped"

Commands are the odd case. The skill says "Do not drop commands from the original file." and calls the commands table foundational reference. Its output structure still wraps that table in a single block, with the condition you need to run commands to build, test, lint, or generate code. Commands survive the rewrite in full, inside a block.

What gets wrapped in `<important if>` blocks?

Everything that only matters for one kind of work: testing patterns, API conventions, state management, i18n. Each gets its own block with a condition that describes when it applies.

The file is strict about how wide that condition may be. A block like <important if="you are writing or modifying any code"> matches every task, so it signals nothing. The skill's instruction for step 5 is:

"You can group rules, but never group unrelated rules under one broad condition."

Source: improve-claude-md/SKILL.md, "How to Apply"

It also tells the agent to keep everything in one file:

"Do not shard into separate files that require the agent to make tool calls to discover, unless the extra context is incredibly verbose or complex."

Source: improve-claude-md/SKILL.md, "3. Keep it short, use progressive disclosure sparingly"

The official docs take a different line and point multi-step procedures toward skills and path-scoped rules. A long procedure in your CLAUDE.md probably fits the skill's own "incredibly verbose" exception, and the skill-creator skill from Anthropic is one way to turn it into a skill.

What does the skill delete from a CLAUDE.md?

Four kinds of content, listed under "Less is more" and "How to Apply":

Linter territory. "Cut any instruction that a linter, formatter, or pre-commit hook can enforce". The skill tells the agent to suggest pre-commit or pre-push hooks as the replacement.
Anything the agent can discover from existing code patterns. If the codebase is consistent, the file argues, the agent picks the pattern up after a few searches.
Code snippets. "Cut code snippets. They go stale and bloat the file." A file path reference replaces each one.
Vague instructions. One of the file's two examples of a line to remove is "follow best practices".

What does a before and after look like?

This pair is taken from the skill's own Example section, abridged to the coding standards rules. Before:

## Coding Standards

- Use named exports
- Use functional components with TypeScript interfaces for props
- Use camelCase for variables, PascalCase for components
- Prefer `const` over `let`
- Always use strict equality (`===`)
- Use template literals instead of string concatenation
- Write JSDoc comments for all public functions
- Use barrel exports in index.ts files

After:

<important if="you are adding or modifying imports or exports">
- Use named exports (no default exports)
</important>

<important if="you are creating new components">
- Use functional components with TypeScript interfaces for props
</important>

Eight rules go in and two come out. The skill's note under the example files the other six (naming case, const over let, strict equality, template literals, JSDoc, barrel exports) as linter and formatter territory, or as discoverable from existing code. In the full example the API, testing and state sections keep all their rules and gain one condition each, and all eight turbo commands remain.

Check that diff before you commit. If your team has no lint rule for strict equality yet, deleting the sentence from CLAUDE.md removes the only place it was written down.

How does it compare with Anthropic's claude-md-improver?

They do different jobs. improve-claude-md restructures one file around a single idea. Per the Skillselion listing for Anthropic's claude-md-improver audit skill, that skill discovers every CLAUDE.md variant in a repo, scores each one A to F on six criteria, and shows a quality report before it proposes targeted edits.

Adoption is lopsided. The Skillselion page for the improve-claude-md skill shows 1,118 installs and claude-md-improver shows 10,587 (skills.sh registry via the Skillselion catalog, data as of Sep 7, 2026).

Our read is that the audit skill suits a file you mostly trust, and the HumanLayer skill suits a file that has grown into a wall of mixed rules. Both sit in the docs and planning category, and the best skills for docs and planning ranking orders the wider field by installs.

What else is in humanlayer/skills?

The repo ships seven skills as of Oct 11, 2026, and each installs the way the README shows:

npx skills add humanlayer/skills --skill improve-claude-md

show-me explains the current topic with diagrams and code-shape sketches. The show-me skill listing has 12,502 installs (skills.sh registry via the Skillselion catalog, data as of Sep 7, 2026), the higher of the two HumanLayer skills with install data. If you want a heavier diagram tool, see our diagram design skill guide.
visual-pr writes a pull request description around a visual change outline.
narrow-react-prop-types, build-iterated-agentic-loop and design-control-loop cover recurring cleanup and scheduled coding-agent workflows.
rpi is new. It landed on Oct 8, 2026 in PR #13 and runs a research, design and implement workflow across separate sessions. Its SKILL.md uses two <important if> blocks of its own.

Our HumanLayer skills guide covers the first six. It was last updated on Sep 29, 2026, so it predates rpi, which has no Skillselion listing and no install data yet. Its summary also says commands stay as plain markdown. The file wraps them in one block, and this article follows the file.

FAQ

Is `<important if>` an official Claude Code feature?

We found no mention of it on the Claude Code memory docs page on Oct 11, 2026. The skill describes it as an XML tag pattern that gives the model an explicit relevance signal.

Does improve-claude-md remove commands from a CLAUDE.md?

The file tells the agent to keep all commands from the original and wrap them in a single <important if> block. That is an instruction to a model, so compare the command table before and after the rewrite.

How do you install improve-claude-md?

Run npx skills add humanlayer/skills --skill improve-claude-md, then type /improve-claude-md in your project. That is the command in the repo README. Other options are in the Skillselion skills catalog.

Last updated: Oct 11, 2026

diagram-design in Claude Code: six steps from your prompt to the .html file

Skillselion — Mon, 28 Sep 2026 08:11:08 +0000

What is diagram-design? An MIT-licensed agent skill by Cathryn Lavery that makes Claude Code draw a diagram as one self-contained HTML file with inline SVG, in your brand colors. It picks one of 41 visual types, states its plan, and runs a checklist before writing the file. Use a Mermaid skill when the diagram must diff in a PR.

Disclosure: we run Skillselion, an independent catalog of agent skills and MCP servers, not affiliated with Anthropic, OpenAI or Cursor. We wrote a longer install and brand-setup walkthrough in our diagram-design guide for Claude Code. This post takes a narrower developer angle: what the skill tells the agent to do, step by step, and what lands on disk. The part that changes how the session feels is step 3: the agent tells you what it is about to draw before it draws it. Every quote below comes from cathrynlavery/diagram-design at commit cea465e, verified 28 September 2026.

How do you install diagram-design in Claude Code?

Two commands inside a Claude Code session, from the repo README:

/plugin marketplace add cathrynlavery/diagram-design
/plugin install diagram-design@diagram-design

Source: README.md, Install, commit cea465e, verified 28 September 2026.

The README also says Claude Code disables auto-update for third-party marketplaces by default, so run /plugin, open Marketplaces, select diagram-design and enable auto-update once. The same skill folder works in Codex and other Agent Skills hosts. For how skill loading works in general, see the Skillselion walkthrough on installing a Claude skill.

Quick numbers, dated: the diagram-design skill listing shows about 4.6k installs (catalog data as of 10 September 2026), and the GitHub repo had 42,618 stars on 28 September 2026 (GitHub API). The SKILL.md is at version 2.6 in its frontmatter.

What happens after you ask for a diagram?

Say you type "Make me an architecture diagram of my app: frontend, backend, database, Redis cache." (the README's own example prompt). The SKILL.md walks the agent through roughly six stages.

1. A first-run gate on your style guide. Before the first diagram in a new project, the agent checks whether references/style-guide.md still holds the shipped default tokens. If it does, it stops and asks you to pick a brand source (a website URL, an installed skill, a local folder or design system, pasted tokens, a saved profile, or keep the default). The rule behind it:

Do not silently ship default-skinned diagrams into a branded project.

Source: skills/diagram-design/SKILL.md, line 21, commit cea465e, verified 28 September 2026.

2. Pick a visual type, load one reference. The skill routes the request to one of its types, then loads that type's reference file (architecture, sequence, ER and so on) before drawing.

Forty-one visual types. Semantic patterns describe behavior; type references describe layout.

Source: skills/diagram-design/SKILL.md, line 13, commit cea465e, verified 28 September 2026.

3. Say the plan before drawing. This is the part you notice in the session. The agent posts one short message first:

Before rendering, state the plan in one short message: the chosen visual type (and semantic pattern, if routed), the size preset, and anything the complexity budget (§7) will force out.

Source: skills/diagram-design/SKILL.md, line 139, commit cea465e, verified 28 September 2026.

If you are in the session, you can redirect it there. If the request already pins type, size and content, the skill skips the pause.

4. Hold the complexity budget. The general limits are 9 nodes, 12 arrows and 2 accent-colored elements per diagram, with tighter per-type limits (5 lifelines in a sequence diagram, 8 entities in an ER diagram). Past that, the instruction is short: "If you exceed, split into two diagrams (overview + detail)." (§7 of the SKILL.md, verified 28 September 2026.)

5. Run the taste gate. A pre-output checklist covers type fit, a "remove test" for every node and arrow, accent count, connector geometry (orthogonal elbows, labels that do not sit on their line, no shared attach points) and the accessibility contract. It also asks the agent to run python3 scripts/self_check.py <file> from the installed skill directory.

6. Write one file. The output is a single self-contained .html file with embedded CSS, inline SVG and no external assets except Google Fonts. It is static unless you asked for motion.

What does the output file look like?

The accessibility contract is the part you can check with grep. Here is our illustrative sketch of the shape the contract requires (not copied from the repo):

<svg viewBox="0 0 960 600" role="img"
     aria-labelledby="checkout-title checkout-desc">
  <title id="checkout-title">Checkout service architecture</title>
  <desc id="checkout-desc">Web client calls the API gateway,
    which reads from Postgres and caches sessions in Redis.</desc>
  <defs><!-- arrow markers --></defs>
  <!-- arrows first, then boxes, so lines sit behind nodes -->
</svg>

The rules behind it, from section 12 of the SKILL.md: role="img", aria-labelledby pointing at the title and desc, <title> as the first child before <defs>, and IDs prefixed per diagram so two inline diagrams on one page do not collide. 0 0 960 600 is the viewBox of doc-inline, the default size preset for all three import commands.

The shipped default palette uses paper #f5f5f5, ink #2d3142 and accent #eb6c36. If you see those three values in a file meant for a branded doc, onboarding probably never ran.

How do you redraw an existing Mermaid or draw.io file?

The plugin ships import commands. Three of the README's examples:

/diagram-design:import-mermaid architecture.mmd --size=slide-16x9 --detail=simplified
/diagram-design:import-drawio platform.drawio --size=slide-16x9 --detail=simplified --audience=executive
/diagram-design:import-excalidraw whiteboard.excalidraw --size=slide-16x9 --detail=simplified

Source: README.md, Import from draw.io, Mermaid, or Excalidraw, commit cea465e, verified 28 September 2026.

Four dials shape the result: format (html, svg, png, html+png), size preset, detail (faithful up to 24 nodes, balanced up to 12, simplified up to 7) and audience (engineer, mixed, executive). The import extracts content with a Python script, discards the source layout and colors, and redraws. One line in the SKILL.md sets the boundary:

An import is bounded by its source: never invent a component to fill a layout, and never silently drop one.

Source: skills/diagram-design/SKILL.md, line 541, commit cea465e, verified 28 September 2026.

Every import ends with a fidelity ledger listing what was merged, collapsed or dropped. Read it before you paste the result into a deck.

When should you use a different diagram skill?

diagram-design writes a designed file. If your diagram has to live as text in the repo and change in code review, that is the wrong output. The alternatives in our catalog, with dated install figures:

the design-doc-mermaid page on Skillselion (GitHub): Mermaid flowchart, sequence, class, ER, state, C4 and architecture diagrams from text or source code, aimed at GitHub wikis. About 44.2k installs as shown on its listing on 28 September 2026.
the Excalidraw Diagram Generator skill (GitHub): an Excalidraw file a teammate can edit by hand. About 29k installs, data as of 7 September 2026.
the Baoyu Diagram skill page (GitHub): SVG diagrams in a dark-themed design system. About 13.8k installs, data as of 7 September 2026.
the Mermaid Diagrams skill listing (GitHub): Mermaid syntax for class, sequence, flowchart, ERD and C4 diagrams in software docs. About 4.8k installs, data as of 7 September 2026.
the Diagram Creator skill (GitHub): Mermaid, PlantUML and ASCII output that renders in docs and IDEs. About 4.2k installs, data as of 7 September 2026.

The SKILL.md makes a related point about when not to draw at all. Lists belong in a table or bullets, and "If a 3-column table communicates the same thing, pick the table." (the SKILL.md selection rules, verified 28 September 2026.)

For the head-to-head, see our comparison of diagram skills for Claude Code. Charts rather than schematics are covered in the data visualization skills guide, and the wider field sits in the Docs and Planning skills ranking and the Docs & Planning category. If you need a diagram during a design conversation rather than for a published doc, obra's brainstorming skill (GitHub) can offer a browser-based visual companion for architecture diagrams and mockups.

FAQ

Does diagram-design need a build step or a renderer?

No. The HTML output opens in any modern browser. PNG export uses Playwright, which the README asks you to install once (pip install playwright && playwright install chromium).

Can I use my company's colors?

Yes. Tell the agent "onboard diagram-design to https://yoursite.com". Per the README, it extracts the palette and fonts, shows a diff, checks WCAG AA contrast of ink on paper at 9 to 12px text sizes, and writes the tokens to references/style-guide.md. Saved profiles plus a .diagram-design marker file let different repos use different brands.

Is it an Anthropic skill?

No. It is a community skill by Cathryn Lavery under the MIT license. Skillselion is independent of Anthropic, OpenAI and Cursor.

Last updated: 28 September 2026. Quotes were checked byte for byte against cathrynlavery/diagram-design at commit cea465e on that date; the SKILL.md last changed in commit da6c92c (27 September 2026 UTC). Install figures are as dated in the text. The Skillselion catalog is refreshed from skills.sh, GitHub and MCP registries and ranked by real installs.

The agent review loop that doubled runtime and changed nothing

Skillselion — Sun, 27 Sep 2026 08:08:06 +0000

obra removed the subagent review loop from the brainstorming skill in superpowers v5.0.6, dated 24 March 2026. The release notes report that dispatching a fresh agent to review plans added about 25 minutes per run and produced identical quality scores across five versions with five trials each. An inline self-review checklist replaced it.

Disclosure before anything else. We run Skillselion, an independent catalog of agent skills and MCP servers, and we are not affiliated with Anthropic, OpenAI, Cursor, Claude, Claude Code or Codex. This piece comes out of our deep dive on the Brainstorming skill listing, written on 20 August 2026 against v6.3.0 of the file. v6.4.1, whose release notes are dated 18 September 2026, has since rewritten the approval gate, so the deep dive still shows the older gate wording. Every quote in this article comes from the current file at commit 8ca22db.

What did the release notes actually say?

Most agent tooling gets louder over time. Another reviewer pass, another orchestration layer, another agent watching the first agent. Here is a maintainer going the other way and showing his working.

The subagent review loop (dispatching a fresh agent to review plans/specs) doubled execution time (~25 min overhead) without measurably improving plan quality. Regression testing across 5 versions with 5 trials each showed identical quality scores regardless of whether the review loop ran.

Source: RELEASE-NOTES.md, v5.0.6, read 27 September 2026.

Five versions, five trials each, one metric, one decision. That is a small experiment by any lab standard, and it is far more than almost any agent workflow gets before it ships. The fancier design lost.

What replaced the review loop?

A checklist the agent runs on its own output, in the same turn. The skill tells the agent to reread the spec it just wrote:

After writing the spec document, look at it with fresh eyes:

Source: skills/brainstorming/SKILL.md, line 247, verified 27 September 2026.

Four items follow: a placeholder scan for TBDs and vague requirements, an internal consistency check, a scope check, and an ambiguity check. Each item is a question the agent has to answer about its own text. The last two do the most work:

Is this focused enough for a single implementation plan, or does it need decomposition?

Could any requirement be interpreted two different ways? If so, pick one and make it explicit.

Source: skills/brainstorming/SKILL.md, lines 251 and 252, verified 27 September 2026.

Then comes the line that decides the cost of the whole thing:

Fix any issues inline. No need to re-review [...]

Source: skills/brainstorming/SKILL.md, line 254, verified 27 September 2026.

No second pass, no iteration cap, no convergence loop. The release notes give the payoff in the same units as the cost: "Self-review catches 3-5 real bugs per run in ~30s instead of ~25 min, with comparable defect rates to the subagent approach". The earlier design carried a three-iteration cap and a subagent dispatch. Both went.

Where does the brainstorming skill refuse to move?

The measurement deleted the review step. It did not touch the approval step, and the skill is emphatic about the difference. The gate sits near the top of the file, inside a HARD-GATE block:

Before taking any implementation action, including invoking an implementation skill, writing product code, scaffolding, installing product dependencies, or creating an external project, complete the selected path's prerequisites:

A reply approves the stage actually presented. Approval of an idea or feature scope does not approve artifacts that do not exist yet.

Source: skills/brainstorming/SKILL.md, hard gate, read 27 September 2026.

Read those two decisions together and a rule falls out. The part that was measured and found inert got cut. The part that protects a human decision stayed, and stayed at full strength on every path. The gate has moved further in that direction since our deep dive was written. v6.4.1, released 18 September 2026, splits approval into stages on the architectural path, where the written spec and then the implementation plan each get a human review.

Why is the path ratchet one-way?

The skill sorts a request into one of three paths before the first question: Spike for a feasibility answer you will throw away, Bounded for a change to a flow that already exists in the repo, Architectural for new subsystems and interface changes. Classification is not a private judgment, and the agent has to say it out loud so a human can override it.

Bounded has a test rather than a vibe. "If there is no existing flow to change, the task is not bounded." That single sentence kills the most common failure, where an agent decides a greenfield feature is small because it can picture the shape of it.

Movement between paths runs in one direction only:

When in doubt between two paths, take the heavier one. The ratchet is one-way: hidden complexity discovered mid-task upgrades the path [...] Nothing downgrades mid-task.

Source: skills/brainstorming/SKILL.md, path selection, read 27 September 2026.

An agent that can talk itself down a tier will do it, because the lighter tier is where the work is allowed to start. Removing the downgrade removes the incentive.

Is a small change exempt from approval?

No, and the skill gives that exemption its own section titled as an anti-pattern.

Every path ends with your human partner approving the required design before implementation. A bounded change may need only two sentences in chat. A new todo-list project is architectural and requires the written spec and planning handoffs.

Source: skills/brainstorming/SKILL.md, lines 92 to 95, verified 27 September 2026.

Two sentences in chat is a real approval, and the gate applies to it in full. If you have ever watched an agent decide that a config change was too trivial to mention and then rewrite three files, you know which half of that sentence is doing the work.

Does this contradict subagent-driven-development?

Not really. The same pack ships the Subagent-Driven Development skill, which holds 197,517 installs in our catalog as of 7 September 2026, and v6.4.1 rebuilt executing-plans so that it ends with one fresh whole-branch review. The maintainer has not sworn off subagents. That skill is about executing a plan task by task. What v5.0.6 removed was a subagent reading a plan or a spec and grading it before implementation started. Both use subagents, for different jobs.

The claim worth stealing is narrow: on this codebase, on these five versions, a review subagent did not beat a 30 second self-check on plan quality. Your workflow might measure differently. The point is that it got measured at all.

What should you copy from this skill?

Three things survive the trip out of this repo.

Put the gate near the top of the file, above the path definitions. The same rule in a references section at the bottom reads as a suggestion.
Give the classification a falsifiable test. "If there is no existing flow to change, the task is not bounded" beats any adjective.
Time your review step before you defend it. Twenty five minutes of overhead is easy to mistake for rigour when nobody has checked what it buys.

If you want to compare gate designs across skills, the same pack's Systematic Debugging skill listing and its Test Driven Development skill both refuse to let the agent proceed on different evidence, and all of them sit together on the obra/superpowers pack page. For the wider field we keep a ranked shortlist of Testing and Review skills and the Dev Tools skills category.

FAQ

Is the brainstorming skill official Anthropic software?

No. It ships in obra/superpowers, a community MIT-licensed repository, which GitHub reported at 292,010 stars and 26,133 forks on 27 September 2026. Skillselion is an independent catalog and has no affiliation with Anthropic.

How popular is the skill compared with the rest of the pack?

Our catalog records 353,451 installs for brainstorming as of 7 September 2026. Inside the same pack it leads systematic-debugging at 250,011 and the Writing Plans skill at 241,042. Source: Skillselion catalog listings, data as of 7 September 2026.

Does deleting the review loop mean plan review is a waste of time?

It means one specific implementation of it was. The replacement is still a review, run inline by the same agent, with a four item checklist and no re-review pass. What the measurement removed was the second agent and the 25 minutes, not the act of checking.

Where do I read the whole file?

The full section by section reading is on the Brainstorming skill page under the deep dive heading. That reading predates v6.4.1, so use the GitHub links above for the current gate wording. The rest of the series is indexed at our skill and MCP deep dives. How long skills like this stay maintained is the subject of the Agent Skill Maintenance Census.

Last updated: 27 September 2026. Every quote above was checked byte for byte against obra/superpowers at commit 8ca22db on that date. The most recent commit to touch skills/brainstorming is the v6.4.1 release commit 5bf4e78 (committed 19 September 2026 UTC; the release notes date v6.4.1 to 18 September 2026). Install figures are Skillselion catalog values, dated where they appear.

One file, two listings: verifying lark-doc against the GitHub source we said did not exist

Skillselion — Sun, 13 Sep 2026 08:38:00 +0000

We spent this morning doing something boring, and it turned up a correction we owe our own readers.

We run a directory of agent skills. In August we published a deep dive on lark-doc, ByteDance's skill for driving Lark (Feishu) documents from a coding agent, and the dive opened with a sourcing note saying the skill had no public repository, so there was no commit to pin quotes to. Today we went looking for the upstream file again before quoting it. The repo has been public since March.

Here is what the check found, what changed in the file since August, and the four-command recipe so you can run it on anything you install.

The short version

The lark-doc SKILL.md that Feishu serves from its own domain is byte-identical to skills/lark-doc/SKILL.md in the MIT-licensed larksuite/cli repo. Both are 4,192 bytes over 49 lines and both hash to 2786f910370662069b1b52b98508033c84baaf0bd7b0bae177426ece4ceafacc. We fetched both on 13 September 2026. Two listings carry that same file with different install counts.

Two listings, two counts, and no total

	Vendor namespace	GitHub namespace
Install command	`npx skills add https://open.feishu.cn --skill lark-doc`	`npx skills add https://github.com/larksuite/cli --skill lark-doc`
All-time installs	663,945	439,469
Figure stamped as of	September 12, 2026	September 7, 2026
Repo stars shown	none	17k

Both numbers come from the skills.sh registry, and we read both pages on 13 September 2026. The gap is 224,476, which makes the vendor-namespace count about 1.5 times the GitHub one.

We are not going to add them for you. The Lark Doc skill page on Skillselion carries a notice that reads, verbatim as it rendered on 13 September 2026:

This is a copy of lark-doc by larksuite - installs and ranking accrue to the original listing.

What we can observe is that our catalog holds a separate record per install path and that the registry reports a different number against each. How an install gets attributed between them is not something we can see from outside, so this post carries no combined audience figure.

Byte-identical duplicates across namespaces are common enough that we measured them. Our Agent Skill Clone Census report, frozen on 2026-08-12, content-matched 79,848 listings and found 3,443 verified copies holding 26,061,541 installs, 15.8% of every install counted. The census test for a copy is a byte-identical SKILL.md. That is exactly the test lark-doc passes here, and the census found publishers re-listing their own work account for 35.0% of those copy-installs, a bigger slice than anyone ripping anyone off.

How do you check a skill file against its repo?

Four steps, about thirty seconds, curl and shasum only.

Hash what you were served.

curl -sS https://open.feishu.cn/.well-known/skills/lark-doc/SKILL.md | shasum -a 256
# 2786f910370662069b1b52b98508033c84baaf0bd7b0bae177426ece4ceafacc

Get the current head SHA from the GitHub API. Never quote from a moving branch.

curl -sS "https://api.github.com/repos/larksuite/cli/commits?per_page=1" | jq -r '.[0].sha'
# 39aaf9fca0e08825b51f6d8c6c617bf781db761b

Fetch the same path at that exact SHA.

curl -sS "https://raw.githubusercontent.com/larksuite/cli/39aaf9fca0e08825b51f6d8c6c617bf781db761b/skills/lark-doc/SKILL.md" | shasum -a 256

diff them. Match means you can cite a pinned commit. Mismatch means the repo wins, because that is what the author currently says, and the difference itself is worth writing down.

Step 2 is the one people skip, and it is the one that matters. A permalink to main drifts off the lines it quotes the next time anybody touches the file. Your citation then points at the wrong sentence and nothing tells you.

While you are there, check the endpoint's headers. The vendor response carried no ETag and no Last-Modified, so there is nothing on that surface to pin a citation to even if you wanted to.

What the file actually says

At commit 39aaf9f, skills/lark-doc/ holds 44 files: the SKILL.md, 15 reference files, and 28 document-genre templates under references/genres/. The SKILL.md is 49 lines and does almost nothing but route between them. The repo ships 28 directories with a SKILL.md in them and carries 17,151 stars and 1,381 forks under MIT (GitHub API, 13 September 2026).

The frontmatter declares dependencies as machine-readable metadata instead of prose:

metadata:
  requires:
    bins: ["lark-cli"]
    skills: ["lark-shared"]

Source: skills/lark-doc/SKILL.md, frontmatter, commit 39aaf9f, read 13 September 2026

A binary and a sibling skill, checkable before anything lands on disk. Compare that to the usual "make sure you have X installed" sentence halfway down a README.

The first body instruction is about context budget, not documents:

**CRITICAL：先判断场景，再读取该场景的参考文件；不要在任务开始时一次性读取全部参考文件。每个文件只在首次进入对应阶段时读取一次。**

Source: skills/lark-doc/SKILL.md, "场景与 Shortcut 路由", commit 39aaf9f, read 13 September 2026

Our translation: "CRITICAL: judge the scenario first, then read that scenario's reference file; do not read all the reference files at once when the task starts. Read each file only once, on first entering its stage." With 43 reference files behind a 49-line router, that is the whole design.

The best line in the file is in the routing entry for writing a document from scratch:

- **从零创作 — [`创建工作流`](references/lark-doc-create-workflow.md)**：先完整执行创建工作流，**简单任务不是跳过的理由**；

Source: skills/lark-doc/SKILL.md, "文档内容", commit 39aaf9f, read 13 September 2026

"A simple task is not a reason to skip it." Somebody watched an agent decide a job was too small for the process and ship something malformed, then wrote a rule about it.

The auth handling runs backwards from most skills, and we think it is the right call. The file tells the agent not to pre-read the shared auth skill and not to pre-run auth status --verify, and to load it only after an unauthenticated, token, identity or scope error, then retry. Most skills pay an auth check on every single run forever. This one pays it once, on failure.

One line changed since our August dive

Our deep dive verified its quotes on 20 August 2026. Between 525a98270f80693bdaf3c0a6006e9f3f94820851 (2026-08-14, the last change before that) and today's head, diff returns exactly one changed line. Line 19, the rule for resolving local file paths.

It went from a single sentence pinning @path references to the current working directory, to a four-clause rule with a lookup order, a fallback to the source XML file's directory, and an explicit list of inputs that get no fallback at all (inline content, stdin, online documents). It arrived in commit 9a29abea on 2026-09-09. The file grew from 4,009 to 4,192 bytes and stayed at 49 lines.

Two things worth reading off that rule rather than around it: local references widened from CWD-relative only to absolute paths anywhere on disk, and on a filename collision the copy in the working directory wins, silently.

Our own catalog copy still shows the older line. Four days behind, confirmed by reading our listing page on 13 September 2026. That lag is precisely why the rule in our process is to re-fetch upstream before quoting, and it is the rule that caught our own error today.

What we got wrong in August

The August dive says "this skill has no public repository" and "There is no commit history to pin". Both wrong. skills/lark-doc/SKILL.md has been public since 2026-03-28, in the commit that open-sourced lark-cli as the official Lark and Feishu CLI. Forty commits have touched that one file since then.

What went wrong is mundane. We checked the vendor's .well-known endpoint, saw no version handle, and stopped looking instead of searching GitHub for a distinctive line of the file. Thirty seconds of searching would have found it. The dive stays useful and its quotes still hold, but its sourcing note is wrong, and this post is where we say so. The index is at the Skillselion deep dive series index.

Should you install it?

If your documents live in Lark or Feishu, yes, and take the suite rather than this one node. lark-doc deliberately does not handle file-level operations or comments, which belong to the Lark Drive agent skill page, and it does not touch spreadsheets or Base tables.

One thing to read before you run the install command. Our GitHub-namespace listing shows a security audit of 2 of 3 scanners passed, sourced from the skills.sh audit and read on 13 September 2026. That is not a red flag by itself, but check the Security Audits panel on the listing before this goes anywhere near production.

If you do not use Lark, skip it. Every capability assumes ByteDance's ecosystem, from the CLI binary to the URL formats it routes on.

Prefer the GitHub install path either way. Same bytes, plus a diff for every future change. If the term itself is new to you, we keep a plain definition on the Skillselion agent skill glossary entry, and the listing that carries the repository, the stars and the security audit panel is the larksuite/cli Lark Doc skill listing.

Run the four commands on the next skill you install. It takes thirty seconds and it is the only thing standing between you and quoting a file nobody can check.

Verified against larksuite/cli at commit 39aaf9fca0e08825b51f6d8c6c617bf781db761b and against the vendor-served SKILL.md on 13 September 2026. Install figures carry the as-of date stamped by the page they came from. Translations from the Chinese are ours. Skillselion is an independent directory and is not affiliated with ByteDance, Lark, Anthropic, OpenAI or Cursor.

Playwright CLI vs Playwright MCP in Claude Code: Microsoft's own READMEs already pick a side

Skillselion — Fri, 11 Sep 2026 09:15:10 +0000

Claude Code can drive a browser two ways: a skill that runs shell commands, or an MCP server that keeps the page inside the conversation. For everyday coding work, use Microsoft's playwright-cli skill and keep Playwright MCP for long exploratory runs and self-healing tests. Microsoft draws that line itself: both repos carry the same "CLI vs MCP" bullets near the top of their READMEs.

Disclosure: we run Skillselion, a directory of Claude Code, Codex and Cursor extensions ranked by installs. This post condenses our Playwright CLI vs Playwright MCP guide for Claude Code, which keeps the numbers below current.

What does Microsoft's README say about CLI vs MCP?

From the CLI bullet, word for word:

CLI invocations are more token-efficient: they avoid loading large tool schemas and verbose accessibility trees into the model context, allowing agents to act through concise, purpose-built commands.

Source: microsoft/playwright-cli README, "Playwright CLI vs Playwright MCP"

And from the MCP bullet in the same section:

MCP remains relevant for specialized agentic loops that benefit from persistent state, rich introspection, and iterative reasoning over page structure, such as exploratory automation, self-healing tests, or long-running autonomous workflows where maintaining continuous browser context outweighs token cost concerns.

Source: microsoft/playwright-cli README, "Playwright CLI vs Playwright MCP"

The Playwright MCP repo carries the same two bullets, and its intro tells anyone using a coding agent that they "might benefit from using the CLI+SKILLS instead."

How do the two compare on installs and stars?

Numbers from the Skillselion catalog on September 11, 2026 (skills.sh registry and GitHub):

	playwright-cli skill	Playwright MCP server
Installs as an agent skill	144,722	not tracked (MCP server)
GitHub stars	13,091	36,836
License	Apache-2.0	Apache-2.0
Fit, per Microsoft's README	coding agents	exploratory, self-healing and long-running loops

Playwright MCP has close to three times the stars. The CLI skill is the one developers install into their agents, and at 144,722 installs it leads every skill with "playwright" in its name. Both have listings with setup details: the playwright-cli skill page and the Playwright MCP server page.

What does the CLI loop look like?

Install the CLI, then let it place the skill where Claude Code finds it:

npm install -g @playwright/cli@latest
playwright-cli install --skills

The skill teaches a snapshot-then-act loop:

playwright-cli open https://example.com
playwright-cli snapshot
playwright-cli click e15

Each command prints the page URL, the title and a link to a YAML snapshot under .playwright-cli/. The accessibility tree stays in that file until Claude asks for it, and on a heavy page playwright-cli snapshot --depth=4 or playwright-cli find "Add to cart" keeps the read small. The SKILL.md frontmatter pre-approves three Bash patterns (playwright-cli, npx, npm), and the microsoft/playwright-cli skill folder bundles 9 reference files, request mocking, tracing and test generation among them.

If you want MCP instead, the Playwright MCP README gives the Claude Code one-liner:

claude mcp add playwright npx @playwright/mcp@latest

Which playwright-cli skill should you install?

Microsoft's. Check the owner before you run the install. A search of our catalog on September 11, 2026 returns at least 12 skills named exactly playwright-cli. Microsoft's holds 144,722 installs, and no other one passes 1,500:

screenci's playwright-cli skill: 1,498 installs
testdino-hq/playwright-skill: 463
coleam00/Archon: 255
gitlab-org/ai: 137
seven more with 50 installs or fewer

The other 11 hold 2,495 installs between them. Most sit inside other projects' repos, and screenci's version, for one, is adapted from Microsoft's skill with steps added for ScreenCI video scripts.

Two more names from the same search can trip you up. The dev skill in Microsoft's playwright-cli repo has 4,378 installs, but it covers rolling Playwright versions and preparing releases for that repository, so it does nothing for your app. And OpenAI's playwright skill in openai/skills (6,314 installs) drives the browser through playwright-cli as well, so Codex users who install it get the same CLI approach under a different name.

When is something else the better pick?

If you want Python scripts committed next to the app, Anthropic's webapp-testing skill (151,377 installs) has Claude write native Python Playwright scripts and ships a with_server.py helper that starts your dev server first.

If you maintain a real test suite, the playwright-best-practices skill from currents.dev (79,834 installs) covers writing, debugging and maintaining Playwright tests, flaky-test fixes and CI sharding included.

If the bug lives inside Chrome itself, our Chrome DevTools MCP debugging guide covers setup, and the ranked list of Chrome MCP servers shows the alternatives.

One setup to avoid: Playwright MCP and the CLI skill connected for the same task. Claude can then load the tool schemas the CLI was meant to keep out of context.

Where to go next

For the same trade-off outside browsers, read Claude Skills vs MCP. Testing tools ranked by installs are on Best Skills for Testing & Review, and more are in our roundup of testing skills for Claude Code.

Which side of the split does your setup fall on? If you run Playwright MCP in a coding loop and it holds up on context, we would like to hear how.

We counted 5,690 agent skill authors. Eight of them hold half the installs.

Skillselion — Thu, 10 Sep 2026 08:17:51 +0000

We counted every publishing account in the Skillselion catalog on 2026-08-28: 5,690 accounts behind 59,685 agent skills and 162,061,967 registry installs. Authorship is wide, adoption is not. Eight accounts hold 50.05% of all installs, the top 1% hold 83.3%, and the author-install Gini coefficient is 0.982.

Disclosure: we run Skillselion, an independent directory of Claude Code, Codex and Cursor extensions. We are not affiliated with Anthropic, OpenAI or Cursor, and not with any account named below. The full study is The Agent Skill Author Census, published 2026-08-28.

How concentrated is the AI agent skill ecosystem?

Very. We sorted all 5,690 accounts by cumulative installs and added from the top. Eight accounts reach 50.05%. Ten reach 54.6%. The top 1%, which is 57 accounts, reaches 83.3%, and 120 accounts (2.1% of all publishers) cover 90% of every install recorded in the catalog on 2026-08-28.

The Gini coefficient of that distribution is 0.982. For reference, a Gini of 1.0 is one account holding everything.

If you have shipped a skill and watched the install counter sit still, you are in the majority of accounts in this census. That is a fact about the distribution. It is not a diagnosis of your skill.

Which accounts hold half of all installs?

Frozen to the 2026-08-28 census, ranked by share of the 162,061,967 total installs. The first eight rows are the ones that add to 50.05%. Ranks 9 and 10 are shown for context and take the running total to 54.6%.

Rank	Account	Skills	Install share
1	open.feishu.cn	28	10.19%
2	mattpocock	45	9.46%
3	microsoft	186	7.67%
4	prime-skills	60	6.71%
5	larksuite	42	6.57%
6	vercel-labs	117	3.8%
7	heygen-com	44	3.2%
8	lllllllama	45	2.46%
9	anthropics	336	2.37%
10	Leonxlnx	20	2.18%

Source: Skillselion Agent Skill Author Census, August 2026, Finding 01.

Several of those names are already the ones developers hit first when they browse. Microsoft's Azure work shows up as the microsoft-foundry skill, Vercel Labs ships the agent-browser skill, Anthropic's own account ships the frontend-design skill, and rank 2 belongs to one person: Matt Pocock's grill-me skill sits in the same account that holds 9.46% of the 162,061,967 installs in this census. His public repos are at github.com/mattpocock.

One caveat before anyone reads the table as a quality ranking. An account here is a publishing account, so an organization counts as one author. Case-folding GitHub owner names merged 34 casing variants and brought 5,724 raw spellings down to 5,690 authors.

Do official vendor accounts explain the concentration?

Partly, and less than the table suggests. Each listing carries a flag for whether the publisher is the vendor of the product the skill drives. On 2026-08-28 that was 5,576 skills, 9.3% of the census, carrying 41,384,836 installs, or 25.5%.

So one skill in eleven is official and one install in four lands on one. Vendors do punch above their listing share. But 74.5% of installs still go to community accounts, which means the concentration is not simply big companies winning. Individual accounts are stacked at the top too.

We wrote more about that split in our guide on whether vendors are replacing Claude Code skills.

Does publishing more skills earn more installs?

No. Of the five findings, this is the one we would most want a first-time publisher to read.

The most prolific account in the catalog, affaan-m, published 544 skills. They average 5,392 installs each and sum to 1.81% of the census. mattpocock published 45 skills that average 340,684 installs each and sum to 9.46%. One account out-published the other twelve to one. The other out-earned it five to one on installs.

Publishing volume buys shelf space, and little else.

Source: Skillselion Agent Skill Author Census, August 2026, "Finding 04".

The pattern holds further down the prolific list. sickn33 published 445 skills at 1,303 installs per skill. TheBushidoCollective published 387 at 47 installs per skill. Neither registers in install share.

None of that is a judgement on the work. The census measures installs per publishing account and nothing about quality. See affaan-m's repositories on GitHub.

What should you do if you publish agent skills?

Three things follow directly from the numbers.

Ship one skill you would use every day rather than a catalog. Dividing the two published averages gives an install-per-skill ratio of 63 to 1 between rank 2 and the most prolific account. That ratio is a derived figure, not a measured one, and it describes those two accounts rather than a rule about yours.
Read the top of your own category before you write. The AI and agents category and the install leaderboard show what already has traction, which is also what you have to be visibly better than.
Expect a slow start. The median author in this census has zero installs, and 52.7% of the 5,690 accounts have never recorded one.

How was this counted?

We dumped all 82,157 catalog listings on 2026-08-28 and aggregated the 59,685 skill listings by publishing account. MCP servers, plugins and marketplaces are excluded because they carry no comparable install count. Installs count registry install events, not active users, so read them as distribution rather than daily usage.

The catalog itself is a live catalog, refreshed daily from skills.sh, GitHub and MCP registries, ranked by real installs. The counting rules and their limits are written up in How Skillselion Research is done.

Every number above recomputes from the author census dataset, which has one row per publishing account with skill count, cumulative installs, install share and the official-vendor columns. It is CC BY 4.0. Cite "Skillselion Agent Skill Author Census, August 2026" and you are done.

If you want the market-shape view instead of the author view, that is The Agent Economy Census, and the running totals are on the AI agent statistics page. Reading a table is slower than browsing, and the agent skills catalog is the same data with filters on it.

FAQ

Who builds AI agent skills?
5,690 publishing accounts, counted as case-folded GitHub owners and registry publishers, authored the 59,685 agent skills in the Skillselion catalog as of 2026-08-28. An organization counts as one account, so this measures concentration across publishers rather than across individual people.

How many installs does the average skill author have?
The arithmetic mean is about 28,481 installs per account, which no account near the middle resembles. The median is zero. 2,998 accounts (52.7%) have no recorded install on anything they published, and 3,539 accounts (62.2%) published exactly one skill.

Is 0.982 a normal Gini coefficient for a developer ecosystem?
It is extreme on its face: 0.982 sits very close to the 1.0 ceiling, where a single account would hold everything. We measured it inside one catalog on one date, and we have not run the same computation on a package registry, so treat it as the shape of agent skill adoption on 2026-08-28 rather than a cross-ecosystem comparison.

Can I reuse these numbers?
Yes, under CC BY 4.0. Cite "Skillselion Agent Skill Author Census, August 2026" and link the study. The dataset download is on the same page.

Last updated: 2026-09-10. Census figures frozen to 2026-08-28.

Supabase promoted its Postgres skill's security tier to CRITICAL in January. The shelf behind it has not gained a file since.

Skillselion — Sun, 06 Sep 2026 08:26:49 +0000

Agent knowledge skills ship a priority table. Eight tiers, CRITICAL down to LOW, one prefix per tier, and it reads as a map of what is inside the bundle. It is not. It is a map of what the authors think matters, and those two things drift apart in a way you can watch commit by commit.

Here is the case I read this morning, in supabase/agent-skills. On 2026-01-16 the Postgres skill's table ranked Security and RLS fifth, at MEDIUM-HIGH. Six days later two commits moved it to third, at CRITICAL:

0ffac72  2026-01-22T08:20:54Z  bump security and RLS to critical
a1fbd23  2026-01-22T08:32:12Z  turn rls basics critical

Neither commit added a security rule file. There were three that day. There are three now, out of thirty-one, seven and a half months later, while the bundle grew by one rule in a different tier. The label moved two ranks and one impact level. The material behind it did not move at all.

That is not misconduct and the skill is a good one. It is a reason to stop reading tier labels as a proxy for depth, and I want to show you the three checks that replace them. Disclosure: I run Skillselion, a directory of agent skills ranked by install count, and I read this bundle while writing its Supabase Postgres Best Practices deep dive.

Check 1: count the reference directory, not the tiers

supabase-postgres-best-practices has 386,740 installs (skills.sh registry, September 5, 2026). Its table promises eight categories. Its references/ directory holds thirty-one rule files plus three meta files, and the split is this:

Prefix	Files	Table priority
`schema-`	6	4, HIGH
`query-`	5	1, CRITICAL
`conn-`	4	2, CRITICAL
`data-`	4	6, MEDIUM
`lock-`	4	5, MEDIUM-HIGH
`monitor-`	3	7, LOW-MEDIUM
`security-`	3	3, CRITICAL
`advanced-`	2	8, LOW

Source: GitHub listing of skills/supabase-postgres-best-practices/references, read 2026-09-06

Security is third by stated priority and seventh by volume. Only the LOW tier is thinner. Schema design, ranked below it, carries twice the material.

Now open the three files themselves, because each rule carries its own impact: line and inside the CRITICAL security tier they read:

File	Own `impact:`
`security-rls-basics.md`	CRITICAL
`security-rls-performance.md`	HIGH
`security-privileges.md`	MEDIUM

Source: frontmatter of the three references/security-*.md files, read 2026-09-06

Two thirds of the CRITICAL security tier does not describe itself as critical. The tier label is the loudest thing in the file and the least specific thing in the bundle.

The three that exist are good, and security-rls-basics.md is the one to read even if you never install anything:

-- Relying only on application to filter
select * from orders where user_id = $current_user_id;

-- Bug or bypass means all data is exposed!
select * from orders;  -- Returns ALL orders

Source: references/security-rls-basics.md, "Incorrect (application-level filtering only)" block

security-privileges.md annotates grant all privileges on all tables in schema public to app_user with -- Any SQL injection becomes catastrophic. Fifteen good minutes. Three files.

Check 2: does the metadata agree with the changelog?

Supabase's frontmatter still says this today:

version: "1.1.1"
date: January 2026

Source: SKILL.md frontmatter, read 2026-09-06

The CHANGELOG shipped in the same directory has its most recent entry at 1.6.0, dated 2026-07-30. Five minor versions and six months separate what the file says about itself from what the file is. The January date is a creation stamp, accurate when written and never touched since.

Harmless until your install tooling or a freshness check reads a version string to decide whether to re-pull. This one has been wrong for half a year, and it never errors, because a file reporting on itself cannot report that it is stale.

Check 3: do the rules teach the broken version first?

Every rule file in the bundle leads with the mistake before the fix, and that is documented policy rather than a habit I inferred. references/_contributing.md names it:

Always show the problematic pattern first, then the solution. This trains agents to recognize anti-patterns.

Source: references/_contributing.md, "Error-First Structure"

This is the single best thing in the bundle and it is worth demanding from any knowledge skill you install. An agent asked to review a schema somebody else wrote has to recognise the anti-pattern in the wild, which means it must have seen the anti-pattern labelled, next to its replacement. A rule file that shows only correct code teaches the agent to write, not to review.

Where did this table shape come from?

Worth knowing, because it explains why the tier labels are so uniform across vendors: the shape is not Supabase's. Vercel committed it first.

Supabase's opening sentence:

Comprehensive performance optimization guide for Postgres, maintained by Supabase. Contains rules across 8 categories, prioritized by impact to guide automated query optimization and schema design.

Source: supabase/agent-skills, skills/supabase-postgres-best-practices/SKILL.md, read 2026-09-06

Vercel's:

Comprehensive performance optimization guide for React and Next.js applications, maintained by Vercel. Contains 70 rules across 8 categories, prioritized by impact to guide automated refactoring and code generation.

Source: vercel-labs/agent-skills, skills/react-best-practices/SKILL.md, read 2026-09-06

The longest identical run is nine words: across 8 categories, prioritized by impact to guide automated. Nine words is short enough to be coincidence on its own. Three byte-identical headings (## When to Apply, ## Rule Categories by Priority, ## How to Use), two byte-identical lead-ins (Reference these guidelines when: and Each rule file contains:) and a priority table with the same header row, exactly eight rows and the same advanced- bottom tier are not.

File	First commit
`vercel-labs/agent-skills` react SKILL.md	2026-01-14 02:35Z
`supabase/agent-skills` postgres SKILL.md	2026-01-16 02:52Z

Two days, and read that second row carefully if you go checking. Supabase's file has been renamed twice, from postgresql-best-practices to postgres-best-practices to supabase-postgres-best-practices, so GitHub's per-path history reports a January 26 first commit and will tell you the gap was twelve days. Read the tree at the repository's first commit instead. The opening sentence, the three headings and the eight-row table are all there on January 16, at version 0.1.0.

I read the README, CONTRIBUTING, AGENTS and CLAUDE files in both repositories and found no mention in either direction. Both SKILL.md files carry license: MIT in their own frontmatter, which permits exactly this, though only Supabase ships an actual LICENSE file.

So the honest word is reuse, and what it tells you as a reader is more useful than any accusation. A house style for vendor knowledge skills exists: thin index, deep per-rule reference files, impact tiers as the organizing idea, error first inside each rule. It travels. You will meet it again, which is exactly why the shape has stopped being a signal and the three checks above have to do that work instead.

Vercel's version is the fuller build of the same idea. Its rules/ directory really does hold seventy rule files behind the seventy the header claims, plus a pipeline that compiles and tests them, and you can read what is in it on the Vercel React Best Practices listing.

Run the three checks on the rest of your database shelf

Counting a reference directory takes a minute and sorts a category faster than an install count will. The Prisma Postgres, Prisma Database Setup and Prisma Client API skills are the obvious next three. Outside Postgres, Azure Kusto and Lark Base sit on the same backend and data category page.

The checks generalise past databases, and the interesting cases are the ones that answer "where should the knowledge live" differently. Web Design Guidelines is a thin index with nothing behind it at all. Agent Browser ships a stub and fetches its real instructions from a CLI at runtime, version matched so they cannot go stale. The shadcn skill shells out for live project config rather than trusting the model's memory of the registry.

Should you install supabase-postgres-best-practices?

Yes, if an agent writes SQL that reaches production, on Supabase or anywhere else. The frontmatter scopes it to "Postgres running anywhere" and the rules are standard Postgres. The priority ordering is sound, the error-first format is the best teaching shape I have seen in a knowledge skill, and the three security files are worth the read on their own. Skip it if your database work is read-only analytics against a warehouse you do not own. Adjust your expectations on depth before you install rather than after: eight tiers sounds comprehensive and thirty-one files is what arrives.

npx skills add https://github.com/supabase/agent-skills --skill supabase-postgres-best-practices

FAQ

Did Supabase copy Vercel's skill?
The two files share three byte-identical headings, two byte-identical lead-ins, a nine-word run in the opening sentence and a priority table of the same shape, and Vercel's was committed two days earlier. Neither repository credits the other, and both SKILL.md files declare license: MIT, so the reuse is permitted. Commit dates document the direction. Nothing documents the intent.

Does supabase-postgres-best-practices only work with Supabase?
No. The frontmatter scopes it to "Postgres best practices maintained by Supabase, for Postgres running anywhere". The rules are standard Postgres: indexes, pooling, RLS, locking, schema design. Individual rule files add Supabase-specific notes where the platform differs.

Eight categories sounds big. How many rules actually ship?
Thirty-one reference files plus three meta files, spread unevenly: schema six, query five, connections four, data four, locking four, monitoring three, security three, advanced two. The eight tiers describe priority, not volume.

Where can I read the full breakdown?
The line-by-line read is in the Supabase Postgres Best Practices deep dive, and the companion pieces are in the deep dive series index. For why vendors are shipping these at all, Are vendors replacing community Claude Code skills? has the wider argument.

Last updated: September 6, 2026. Install counts from the skills.sh registry as of September 5, 2026. File quotes, commit hashes and dates, and the reference directory listing were read from GitHub on September 6, 2026.

The start-here skill of a 60,112-star AI gateway links 17 sibling skills. 16 are dead.

Skillselion — Wed, 02 Sep 2026 14:42:48 +0000

OmniRoute is having its breakout month. OmniRoute is a free, MIT-licensed AI gateway that puts one OpenAI-compatible endpoint in front of many model providers (352 of them, by its own README). It sits at 60,112 GitHub stars, and "omniroute" is a Breakout riser in Google Trends as of September 2, 2026. So we did what we do for skills with momentum: we read the repo's designated start-here skill for REST access, omni-auth, byte by byte at commit 93265ee, and published the full walkthrough as a line-by-line deep dive on the omni-auth listing.

The file is 7,168 bytes over 150 lines, and the most interesting thing in it is a table that has quietly died.

The file tells you it was not written by a person

The first line after the frontmatter:

<!-- generated by src/lib/agentSkills/generator.ts; manual edits will be overwritten -->

OmniRoute generates its skill files from the application's API surface, the way OpenAPI docs come out of route definitions. The endpoints in the file cannot drift from the running server. The parts the generator does not touch, we found out, can.

What the skill actually teaches an agent

Most agent skills are prose instructions; this one is closer to a compressed API reference. It teaches three things, and they are the right three:

Two credential types, and the boundary between them. API calls take a Bearer key. The dashboard takes a password and returns a session cookie. The file says this in two sentences, and an agent that mixes them up gets a clean 401 instead of a mystery.
A two-variable setup. There is no Claude Code section or Cursor section because none is needed: any agent that speaks OpenAI-style REST points at the same base URL. Running the server itself belongs to the sibling cli-serve skill.

export OMNIROUTE_URL=http://localhost:20128
export OMNIROUTE_KEY=...          # minted in the dashboard
curl $OMNIROUTE_URL/api/health    # {"ok":true}

A status-code-to-recovery table. 401 means refresh your key, 503 Provider circuit open means wait Retry-After and let auto-fallback work. Four bullets that stop an agent from retry-hammering a provider whose circuit breaker is open.

For a generated file, the OIDC section is unusually explicit: state-cookie CSRF protection, ID-token verification against the issuer's JWKS, an optional subject allowlist, and a 30-day session JWT. That paragraph is where the dashboard's security posture actually lives, and you can read it in the skill file instead of the source.

The dead tables

The back half of the file is older, and it says so: a comment marks it as content migrated from an earlier skill and preserved. It ends with the skill's most useful-looking artifact: two tables linking 17 sibling skills by raw URL. Chat, images, TTS, embeddings, routing, compression, the MCP server, the CLI family.

We fetched all 17 URLs on September 2, 2026. Sixteen return 404. The only one that resolves is omni-mcp, the only entry whose name survived the catalog's rename to the current omni-* and cli-* families. The repo holds 46 SKILL.md files on disk; its own live skills index lists 45 of them correctly, one directory up from the dead tables.

The defense is printed in the file itself: the block is labeled as preserved legacy content, and the generator's notice says manual edits get overwritten, so a hand fix would not stick. The consequence still lands on the agent, though. An assistant that follows the start-here skill's own index to load a capability fetches sixteen 404 pages while the working index sits beside it.

The preserved block has a second tell: it says 327 providers while the README at the same commit says "352 providers" four times. Content outside the generator's reach trails the product. Anything below that migration comment deserves a date check.

Is it safe to route your prompts through it?

Yes, if you keep it on your own machine. A gateway sees every prompt that passes through it, so the trust question is about where it runs. OmniRoute is self-hosted by default, MIT-licensed end to end, with password plus optional OIDC-allowlist login and CSRF-guarded flows. The 30-day session token is long-lived, and the allowlist only protects you if you configure it. For calibration on how rare any scrutiny is in this ecosystem: our agent skill security census, taken in August 2026, scanned 79,848 listings and found 87.8% of agent skills have never had a security audit.

If you are weighing OmniRoute against the incumbent, we also published a comparison against LiteLLM (57,827 stars, MIT core plus a commercial enterprise tier, with its own MCP server listing): OmniRoute vs LiteLLM. Short version: OmniRoute belongs on a machine you own, LiteLLM on a proxy a team shares.

Where OmniRoute sits in the catalog

The repo ships 46 skills; skills.sh shows its 20 most-installed at 308 to 388 installs each (all-time, September 2, 2026), tiny numbers next to the head of the skills leaderboard where grill-me alone crossed a million. The 60k stars and the Breakout search curve say the gateway is what people want; the skills are along for the ride. That gap between repo fame and skill adoption is the same shape our agent economy census measured across the whole ecosystem: attention concentrates, installs concentrate harder.

Both entry-point skills are now listed on Skillselion, alongside the rest of the deep-dive series where we read one skill's actual file per piece.

Source repo: diegosouzapw/OmniRoute. The pinned file we quoted: skills/omni-auth/SKILL.md at 93265ee.

Disclosure: we run Skillselion, the directory these listings live on. The catalog is refreshed daily from skills.sh, GitHub and MCP registries, ranked by real installs.

What is inside Emil Kowalski's design skill? We read all 27KB of emil-design-eng

Skillselion — Wed, 02 Sep 2026 02:26:53 +0000

emil-design-eng is Emil Kowalski's agent skill for interface polish: one 27,226-byte SKILL.md and nothing else. It opens with a scripted first reply, spends most of its animation framework arguing against animating, swaps the CSS easing keywords for three cubic-bezier constants, and requires a Before/After/Why table in every review. It has 243,573 installs as of September 2, 2026 (Skillselion catalog).

"emil kowalski design skill" is a breakout rising query on Google Trends today, September 2, 2026 (past 30 days, worldwide). Most pages answering it repeat the one-line description, so we read the file section by section for the emil-design-eng deep dive on Skillselion. This is the developer cut: what the file instructs an agent to do, and where it argues with itself. Its last commit in emilkowalski/skills is dated July 21, 2026, so what we read on August 20 is what installs today.

Disclosure: we run Skillselion, an independent directory of agent skills (live catalog, refreshed daily from skills.sh, GitHub and MCP registries, ranked by real installs). We are not affiliated with Anthropic, OpenAI, Cursor or Emil Kowalski.

What does emil-design-eng say before you ask anything?

On an invocation with no question attached, the "Initial Response" section fixes the reply to one line. It begins "I'm ready to help you build interfaces that feel right, my knowledge comes from Emil Kowalski's design engineering philosophy." and ends by pointing at the author's course at animations.dev. Then:

Do not provide any other information until the user asks a question.

Source: SKILL.md, "Initial Response"

The wait rule is sound. A 27KB payload with no question to spend it on should stay latent. The course link is a marketing placement written as an instruction, one sentence, once. Know it is there before the agent's output reaches a customer.

Does the emil-design-eng skill tell the agent to animate?

Mostly it tells the agent not to. Four questions are asked in order, and the first is whether to animate at all, answered by a frequency table whose top row (keyboard shortcuts, command palette toggle) reads "No animation. Ever."

Never animate keyboard-initiated actions. These actions are repeated hundreds of times daily. Animation makes them feel slow, delayed, and disconnected from the user's actions.

Source: SKILL.md, "Should this animate at all?"

Question two demands a purpose from a list of five and rules that "it looks cool" on something seen often is a no. About half of the opening framework in a skill filed under polish is a brake, and that is the part an agent needs most, because an agent asked to make a component feel alive will otherwise animate everything it can reach.

Which easing curves does emil-design-eng ship?

Question three routes entrances and exits to ease-out, on-screen movement to ease-in-out, hover and color changes to ease, constant motion to linear, then rejects the default shape of all four.

Critical: use custom easing curves. The built-in CSS easings are too weak. They lack the punch that makes animations feel intentional.

Source: SKILL.md, "What easing should it use?"

/* Strong ease-out for UI interactions */
--ease-out: cubic-bezier(0.23, 1, 0.32, 1);

/* Strong ease-in-out for on-screen movement */
--ease-in-out: cubic-bezier(0.77, 0, 0.175, 1);

/* iOS-like drawer curve (from Ionic Framework) */
--ease-drawer: cubic-bezier(0.32, 0.72, 0, 1);

Source: SKILL.md, "What easing should it use?"

One keyword is banned for interface work: "Never use ease-in for UI animations." The reason is mechanical. ease-in delays the initial movement, which is the moment the user watches most closely, and a rule with a mechanism is one an agent can extend to cases the file never lists. The same three values sit, identical, in at least four sibling files at the commit we read, so installing this skill next to animate, find-animation-opportunities, review-animations or improve-animations puts the constants in context twice.

Why does the duration table contradict its own rule?

Question four is a five-row table: button press feedback 100-160ms, modals and drawers 200-500ms. Printed under it:

Rule: UI animations should stay under 300ms. A 180ms dropdown feels more responsive than a 400ms one.

Source: SKILL.md, "How fast should it be?"

A drawer is a UI element, and the row three lines up allows it 500ms. A person reads 300ms as the default and 500ms as the allowance for the largest surfaces. The file never says so, and the closing checklist turns 300ms into a defect:

| Duration > 300ms on UI element | Reduce to 150-250ms |

Source: SKILL.md, "Review Checklist"

So a 400ms drawer that question four permits gets flagged when the same skill reviews the code, with a fix band the duration table never offers drawers. An agent applies both halves as written.

What does a review look like with emil-design-eng installed?

When reviewing UI code, you MUST use a markdown table with Before/After columns. Do NOT use a list with "Before:" and "After:" on separate lines.

Source: SKILL.md, "Review Format (Required)"

A five-row example follows, then a fenced block labelled as the wrong format, showing the list layout the author did not want. Printing the output you do not want is a correction aimed at a habit the author kept seeing. The Why column forces a reason per row, and an eleven-row issue-to-fix checklist closes the file, so a review has a mandated shape and a mandated sweep. Ask to "review my animation code" and the prose list you got before becomes a table, one row per issue.

Which Emil Kowalski skills should you install alongside it?

The repo has 34,182 stars as of September 2, 2026 (Skillselion catalog). The ranked shortlist, installs as of the same date (Skillselion catalog):

Skill	Installs	Job	Source
emil-design-eng skill	243,573	The reference corpus	GitHub
review-animations skill	133,796	Audits existing motion, standards file beside it	GitHub
animation-vocabulary skill	121,235	Vague motion description to precise term	GitHub
apple-design skill	114,701	Gestures, springs, sheets	GitHub
improve-animations skill	106,122	Read-only audit of shipped animation code, with fix plans	GitHub
find-animation-opportunities skill	93,723	Where motion is missing	GitHub
pick-ui-library skill	77,984	One opinionated component-library pick per task	GitHub
prototype skill	66,855	Several working versions of one UI piece behind a picker	GitHub

Should you install emil-design-eng?

Install it if you want one opinionated reference in context for interaction work and would rather over-fetch than route. The brake is the strongest part, and the performance rules read like notes from shipped libraries rather than a style guide (the file names Sonner and Vaul, and cites a dropped-frames fix on the Vercel dashboard). Some passages are written for a person, such as testing gestures on a real phone over USB; an agent cannot execute those, so they hold up as reference a human consults through it.

Skip it if your context budget is tight. It is the largest file in the repo, about 20 percent above apple-design at 22,715 bytes, and the only model-invocable skill there whose description has no "Use when" clause, so the biggest file has the weakest routing. Skip it too if you expected a design system; there is no color, spacing or layout guidance in it. For that half, the design-taste-frontend skill and Anthropic's frontend-design skill sit beside it on the best skills for frontend design shortlist, ranked by real installs.

npx skills add https://github.com/emilkowalski/skills --skill emil-design-eng

More files read this way: the Skillselion Deep Dives series.

FAQ

Is emil-design-eng the same as the other Emil Kowalski skills? No. The README lists it first as the main skill; the task-shaped siblings repeat the constants and the frequency framework they need, rewritten in their own words.

How much context does it cost? 27,226 bytes at the commit we read, the largest SKILL.md in the repo, and the catalog lists it as the only file that ships.

Does it work outside React? The reasoning does. The samples assume CSS, React and Motion, so a Vue or Svelte codebase gets the rules and none of the copy-paste.

Last updated September 2, 2026. Every quote verified against emilkowalski/skills, skills/emil-design-eng/SKILL.md (last commit July 21, 2026).

The number 2 most-installed agent skill is seven lines long and delegates all of them

Skillselion — Sun, 30 Aug 2026 08:18:32 +0000

At 1,005,653 installs, the second most-installed agent skill in our catalog is seven lines long. Not seven hundred. Seven. As of August 30, 2026, Matt Pocock's grill-me skill trails only the find-skills skill from Vercel Labs, which holds 3,170,600. The installed file writes no code and contains no method. Its one working instruction hands off to a sibling.

Disclosure: we run Skillselion, an independent catalog refreshed daily from skills.sh, GitHub and MCP registries, ranked by real installs. We read both files line by line at commit 885e2ca of mattpocock/skills on August 20, 2026, as part of our deep dive series. Every quote below is from that commit.

What does the seven-line grill-me skill actually do?

Call the Skill tool with "grilling".

Source: SKILL.md, full file at the grill-me folder in mattpocock/skills

That is routing, not laziness. The repo keeps one method skill named grilling and points two trigger skills at it: grill-me for plans, and the grill-with-docs skill for architecture decisions against a live codebase. grill-with-docs is itself at 856,939 installs, third in the catalog. The dependency matters when you install: seven lines have nothing to fall back on, so grill-me does nothing unless the grilling skill is present too.

Why can the agent not start grill-me by itself?

disable-model-invocation: true

Your agent cannot fire grill-me on its own. You say "grill me", or nothing happens. For a skill whose entire output is questions aimed at you, that is the right lock. The interesting part is where the lock is not: grilling, the method underneath, carries no such flag, and its description invites the agent to reach for it when you seem to want your thinking stress-tested. The trigger phrase belongs to you. The method keeps its own judgment.

How does grill-me structure its questions?

The method models your plan as a tree where every decision branches into the decisions hanging off it. The set of questions whose prerequisites are already settled is called the frontier, and the agent asks the whole frontier in one numbered round:

❓ Q1 - <question title>: <question body>
➡️ <your recommended answer>

Each question ships with the agent's own recommendation, so you can answer "yes to your suggestion" instead of writing an essay. A question that depends on another still-open question belongs to a later round, explicitly. Every answered round reshapes the tree.

How does grill-me avoid asking you to run ls?

Finding facts is your job, never the user's.

Source: grilling SKILL.md

Anything the agent could look up in the environment, it dispatches a sub-agent to find instead of asking you. A running lookup counts as an unsettled prerequisite, so only the questions downstream of it wait while the rest of the frontier gets asked. You never get asked to run ls.

The exit condition is testable rather than vibes based: the session ends when the frontier is empty, and even then the agent must not act until you confirm you have reached shared understanding.

What changes once grill-me is installed?

You say	Without grill-me	With grill-me
"Grill me on this plan"	The agent agrees and starts building	Numbered question rounds until no branch is silently assumed
"We should add a Postgres cache here"	"Great idea", then an implementation	The frontier fills with invalidation, the local dev story, and who owns the schema

npx skills add https://github.com/mattpocock/skills --skill grill-me

Install notes and the trigger vocabulary are in the grill-me guide.

Why do mattpocock/skills entries hold seven of the top ten?

Look at the top ten by installs on August 30, 2026 and seven slots belong to skills from the mattpocock/skills repository. The tell is the setup-matt-pocock-skills skill at 734,383 installs in eighth place. That skill does nothing but scaffold the per-repo configuration the other skills assume: issue locations, triage labels, domain-doc layout. On its own it is useless. The likeliest read is that people install the author's stack rather than picking individual files. The tdd skill at 797,033 and the improve-codebase-architecture skill at 824,417 ride the same wave.

The other pattern in that list: skills that stop the agent outrank skills that make it produce. The same shape shows up across the August 2026 agent economy census. If you want to compare planning skills against each other, the docs and planning hub ranks that category, and the full skills catalog covers the rest.

Install counts are live as of August 30, 2026. Quotes are from commit 885e2ca, verified August 20, 2026.

Vercel's web-design-guidelines skill is 39 lines long and contains zero rules

Skillselion — Sat, 29 Aug 2026 08:04:00 +0000

The UI review skill with 587,920 installs (August 29, 2026, Skillselion catalog) does not contain a single accessibility rule. web-design-guidelines, Vercel's UI review skill, is 39 lines including frontmatter, and every rule it checks lives in a second repository it fetches at review time, from a URL that tracks main.

We run Skillselion, a directory of Claude Code, Codex and Cursor extensions ranked by real installs, and we read the skill file at commit b8caa26 of vercel-labs/agent-skills for our deep dive on the skill. Here is what the architecture actually implies for your reviews.

The file is an instruction to go get instructions

One sentence defines the whole design:

Use WebFetch to retrieve the latest rules. The fetched content contains all the rules and output format instructions.

Both halves of a review live somewhere else: what to check, and how to print what you find. The repo's README advertises "100+ rules covering accessibility, performance, and UX", and that number appears nowhere in the skill file. It arrives by download when the review runs.

That means the skill needs the network, and it asks for it by naming WebFetch, a Claude Code tool. In a sandboxed CI runner, or under an agent with no equivalent fetch tool, the skill still loads and still triggers, with nothing to check your code against.

The rules changed on August 18 and your install did not

The fetch target is raw.githubusercontent.com/vercel-labs/web-interface-guidelines/main/command.md. main is a branch. GitHub's history for that path shows five commits, three of them dated August 18, 2026, adding accessibility and media rules and revising the curly-quote guidance.

So a component that came back clean in July can come back with findings in August, and the diff that caused it sits in vercel-labs/web-interface-guidelines, a repository you do not depend on and were never asked to watch. Your rules improve when Vercel improves them, which is the defensible intent. The bill arrives as reproducibility: two reviews of unchanged code, weeks apart, can legitimately disagree.

Teams that need a review to hold still have the usual escape hatch: vendor the rules file into your own repo and point the agent at your copy.

The sheet it fetches is missing the rules with numbers in them

Vercel publishes three rule documents in the guidelines repo. Read on August 20, 2026: the README carries 129 rule bullets, AGENTS.md carries 107 written as MUST, SHOULD and NEVER, and command.md, the one this skill hard-codes, carries 103.

The coverage gap is not random. Under "Targets & Input", AGENTS.md holds two MUST rules the command sheet has no equivalent of: a hit target of at least 24px (44px on mobile), and a mobile input font size of at least 16px so iOS Safari stops zooming on focus. The command sheet also drops focus management, tooltip timing and most of the README's Design section.

Ask this skill "are my tap targets big enough?" and you get a guess. The fetched sheet carries no minimum hit-target rule, and nothing in the report tells you the question was out of scope.

What it does cover is worth having: ARIA labeling and semantic elements, focus-visible rings, form autocomplete, compositor-friendly animation, Intl formatting, hydration-safe inputs. The gap is a subset problem, not a quality problem.

It is a template, and the copies inherit Vercel's edits

The same repo ships writing-guidelines, the prose review skill: the same file with five lines changed (name, description, heading, summary, URL). Any raw markdown URL can become a review skill this way, and every skill built this way needs the network at review time and tracks a branch somebody else controls.

Our Agent Skill Clone Census, frozen at August 12, 2026, ranks web-design-guidelines the second most-copied original in the catalog: 36 identical or near-identical copies, behind Anthropic's frontend-design at 59. Each copy inherits the one URL, which points into a repository the copier does not control. The copies that keep that URL fetch Vercel's rules on every run and inherit Vercel's edits, which is an unusual property for a fork to have.

Contrast the sibling skill in the same repo: vercel-react-best-practices, the React performance skill, ships 70 rule files on disk after install. Same author, opposite architecture.

Should you install it?

Install it if you review UI in Claude Code and want the check driven by a published external standard instead of whatever the model feels strongly about that session. The rules on the other end are genuinely good, and the cost of keeping them current is one fetch per review.

Skip it if your agent runs without network access, or if your reviews need to be reproducible. Vendor the sheet instead.

If you want the generation-side counterpart, the guidelines repo pairs this skill with its AGENTS.md on purpose: the skill reviews what exists, AGENTS.md shapes what gets generated. Installing the skill does not put AGENTS.md in your project.

For the taste-layer alternatives developers actually cross-shop, see our hub of frontend design skills: Anthropic's frontend-design generates UI under a design brief, impeccable applies Paul Bakaus's design playbooks, ui-ux-pro-max looks up palettes and WCAG rows, and design-taste-frontend is the landing-page taste layer. web-design-guidelines is the only one of the five that generates nothing: it grades the files you already have.

Every quote above is verified against the repository at the commit named, section by section, in the full deep dive. The dive series index is at Deep Dives, and the full catalog at the skills directory.

Disclosure: we run Skillselion. Counts come from our live catalog, refreshed daily from skills.sh, GitHub and MCP registries, ranked by real installs.

Anthropic's frontend-design skill names the three cliché "AI looks", hex codes included

Skillselion — Fri, 28 Aug 2026 08:22:40 +0000

Anthropic ships an official Claude Code skill whose whole job is stopping your agent from designing the same page every other agent designs. It is called frontend-design, it is 55 lines of prose with no scripts and no component library, and it has 825,477 installs as of the August 27, 2026 Skillselion catalog sync, which makes it the third most-installed agent skill overall.

We read the file line by line for the frontend-design deep dive on its listing page. Disclosure: we run Skillselion, the directory the dive lives on.

The part worth your attention is one paragraph in the middle. Anthropic describes, with a hex code, exactly what AI-generated design collapses into when nobody stops it.

The paragraph to screenshot

"AI-generated design right now clusters around three looks: (1) a warm cream background (near #F4F1EA) with a high-contrast serif display and a terracotta accent; (2) a near-black background with a single bright acid-green or vermilion accent; (3) a broadsheet-style layout with hairline rules, zero border-radius, and dense newspaper-like columns. All three are legitimate for some briefs, but they are defaults rather than choices."

Source: SKILL.md, "Process" section, anthropics/skills on GitHub. Quotes verified against the upstream file on August 19, 2026; the file last changed June 9, 2026.

If you have shipped an agent-built landing page this year, you have probably shipped look number one.

A blacklist became a description, and that is the interesting engineering

The earlier version of this skill banned aesthetics by name: Inter, Roboto, purple gradients on white. The rewrite drops the blacklist entirely and replaces it with descriptions of the failure modes. A banned-fonts list rots the day a new default font appears. A description of the cliché generalizes: the agent can recognize the cream-serif-terracotta pattern in any font, any framework, any year.

That is a prompt-engineering pattern worth stealing for your own skills: describe the failure mode you want avoided instead of enumerating instances of it.

What the other 50 lines do

The file changes agent behavior in eight moves. The short version:

A focused trigger. The frontmatter description scopes it to visual design for new or reshaped UI, so it does not fire on every request that touches pixels.
A role with stakes. "Approach this as the design lead at a small studio" whose client "has already rejected proposals that felt templated". The load-bearing line: "take one real aesthetic risk you can justify".
Subject grounding. If the brief is vague, the agent must pin a concrete subject, audience, and the page's single job before designing, out loud.
Six design principles. One paragraph each: hero as thesis, typography as personality, "Structure is information", motion as "an orchestrated moment", complexity matched to the vision, and copy as a principle of its own.
The calibration warning. The three looks above.
A two-pass process. Plan a compact token system (named palette, type pairing, layout, one signature element), then critique the plan for genericness before writing any code. Code comes third.
A restraint rule. "Spend your boldness in one place", plus Chanel's mirror advice: remove one accessory.
A writing chapter. Roughly a fifth of the file is about words: "A person manages notifications, not webhook config", "Save changes" not "Submit", and errors that never apologize and are never vague.

The full walkthrough with every quoted section lives in the deep dive on the frontend-design listing.

What it will not do for you

Two honest caveats from our read. It optimizes for distinctiveness, so on plain internal tools it can over-art-direct; constrain it with your own brief. And it contains almost no engineering: one CSS-specificity warning and a quality floor (responsive, keyboard focus, reduced motion), no accessibility depth, no performance budgets. It tells your agent what designed means, not how to ship it.

One more thing to check before installing: a repackaged clone of this skill circulates under a different owner. Verify the repo owner is anthropics.

Where it sits in the taste stack

frontend-design is the biggest entry in a cluster of skills that all attack the same problem: agent output that looks generated. If you are building out a design-side setup, these are the neighbors, with installs as of the same August 27 catalog sync:

Grill Me, the plan-interrogation skill by Matt Pocock, 985,753 installs. It now sits above frontend-design at number 2 overall; the two are often installed together, one for the plan, one for the pixels.
anti-ui-slop, the UI cliché blocker, 528,289 installs. The community's harder-edged answer to the same three looks.
web-design-guidelines by Vercel Labs, 582,881 installs. Built on explicit rules where frontend-design leans on a role; a useful contrast in approach.
design-taste-frontend, the taste layer, 410,792 installs, and its sibling minimalist-ui skill.
impeccable, the frontend polish skill, 250,618 installs, for the final polish pass.
emil-design-eng, Emil Kowalski's design-engineering skill, 233,965 installs, for the motion-and-microinteraction end.

We keep the whole category ranked by real installs on the frontend design skills hub, and the section-by-section reads for other major skills in the Deep Dives library. If you want to see how a discovery skill does the instructions-only trick at even larger scale, the find-skills listing sits at 3,135,861 installs, and the broader skills directory is refreshed daily from skills.sh, GitHub and MCP registries, ranked by real installs.

Install line, if you want it:

npx skills add https://github.com/anthropics/skills --skill frontend-design

825,477 installs, as of the August 27 sync, for a file that is mostly a client brief. Read the file before you let it art-direct you.

DEV Community: Skillselion

What improve-claude-md keeps, wraps and deletes in your CLAUDE.md

What problem does improve-claude-md claim to solve?

What stays as plain markdown in a CLAUDE.md?

What gets wrapped in <important if> blocks?

What does the skill delete from a CLAUDE.md?

What does a before and after look like?

How does it compare with Anthropic's claude-md-improver?

What else is in humanlayer/skills?

FAQ

Is <important if> an official Claude Code feature?

Does improve-claude-md remove commands from a CLAUDE.md?

How do you install improve-claude-md?

diagram-design in Claude Code: six steps from your prompt to the .html file

How do you install diagram-design in Claude Code?

What happens after you ask for a diagram?

What does the output file look like?

How do you redraw an existing Mermaid or draw.io file?

When should you use a different diagram skill?

FAQ

The agent review loop that doubled runtime and changed nothing

What did the release notes actually say?

What replaced the review loop?

Where does the brainstorming skill refuse to move?

Why is the path ratchet one-way?

Is a small change exempt from approval?

Does this contradict subagent-driven-development?

What should you copy from this skill?

FAQ

One file, two listings: verifying lark-doc against the GitHub source we said did not exist

The short version

Two listings, two counts, and no total

How do you check a skill file against its repo?

What the file actually says

One line changed since our August dive

What we got wrong in August

Should you install it?

Playwright CLI vs Playwright MCP in Claude Code: Microsoft's own READMEs already pick a side

What does Microsoft's README say about CLI vs MCP?

How do the two compare on installs and stars?

What does the CLI loop look like?

Which playwright-cli skill should you install?

When is something else the better pick?

Where to go next

We counted 5,690 agent skill authors. Eight of them hold half the installs.

How concentrated is the AI agent skill ecosystem?

Which accounts hold half of all installs?

Do official vendor accounts explain the concentration?

Does publishing more skills earn more installs?

What should you do if you publish agent skills?

How was this counted?

FAQ

Supabase promoted its Postgres skill's security tier to CRITICAL in January. The shelf behind it has not gained a file since.

Check 1: count the reference directory, not the tiers

Check 2: does the metadata agree with the changelog?

Check 3: do the rules teach the broken version first?

Where did this table shape come from?

Run the three checks on the rest of your database shelf

Should you install supabase-postgres-best-practices?

FAQ

The start-here skill of a 60,112-star AI gateway links 17 sibling skills. 16 are dead.

The file tells you it was not written by a person

What the skill actually teaches an agent

The dead tables

Is it safe to route your prompts through it?

Where OmniRoute sits in the catalog

What is inside Emil Kowalski's design skill? We read all 27KB of emil-design-eng

What does emil-design-eng say before you ask anything?

Does the emil-design-eng skill tell the agent to animate?

Which easing curves does emil-design-eng ship?

Why does the duration table contradict its own rule?

What does a review look like with emil-design-eng installed?

Which Emil Kowalski skills should you install alongside it?

Should you install emil-design-eng?

FAQ

The number 2 most-installed agent skill is seven lines long and delegates all of them

What does the seven-line grill-me skill actually do?

Why can the agent not start grill-me by itself?

How does grill-me structure its questions?

How does grill-me avoid asking you to run ls?

What gets wrapped in `<important if>` blocks?

Is `<important if>` an official Claude Code feature?