DEV Community: wolfejam.dev

Not all MCP servers are equal — what 7/28 just made official

wolfejam.dev — Fri, 31 Jul 2026 06:34:03 +0000

TL;DR — 7/28 (wire: 2026-07-28) is the modern MCP release. The big deal is STATELESS: no protocol session, request/response core, Discover, stamped lists, Streamable HTTP routing headers. A server can expose health on three hosts and still be three different machines operationally. This post is the GOOD → BETTER map, plus a runnable textbook you can install in minutes.

MCP lives under the Agentic AI Foundation / Linux Foundation. Spec: modelcontextprotocol.io/specification/2026-07-28. Claude-side rollout note: Bringing MCP 2026-07-28 to Claude (2026-07-28). Ship note: faf.one/blog/mcp-better.

Same name, different machine

InterOp is not “does tools/list return a string called echo?”

InterOp is: does this server behave like a 7/28 peer under a modern client?

Question	Why it bites
Does the client use Discover, or only legacy `initialize`?	Handshake-as-identity is GOOD-era. 7/28 is request/response + `server/discover`.
Does `tools/list` return `ttlMs` + `cacheScope`?	List cache is part of the modern contract — not optional polish for BETTER claims.
Is tool order stable?	Prompt-cache and client caching assume determinism.
On HTTP: are `Mcp-Method` / `Mcp-Name` present?	Routing without body parse — required on Streamable HTTP POSTs.
Does the server invent session stickiness as identity?	Protocol sessions are gone. App state = explicit handles if anything.

If two servers both advertise echo but only one answers those questions honestly, they are not interchangeable. Host A “works.” Host B “flakes.” The tool name stayed the same. The operational surface did not.

GOOD habits (pre-7/28 muscle memory)

None of this is “you’re bad.” It was the world the old samples taught.

Habit	What it looked like
Session as identity	Sticky `Mcp-Session-Id`, “connected” means long-lived peer
Handshake as the event	`initialize` / `initialized` as the main lifecycle story
Unstamped lists	`tools/list` works, but no cache hints — clients re-poll forever
Host-lucky InterOp	Works in one Desktop config; mystery failure in another
Banner claims	README says “modern MCP”; wire is still 2024-shaped

Call that GOOD: real MCP, real tools, real value — with session-era operational assumptions.

BETTER after 7/28 (checklist you can audit)

Humans say 7/28. Machines negotiate 2026-07-28. The big deal is STATELESS.

BETTER check	Spec-shaped meaning
Stateless core	No protocol session; any request can hit any healthy instance (HTTP)
Discover	Clients prefer Discover / Auto → 7/28; servers answer discover correctly
Self-describing traffic	Version + capabilities travel with the request (`_meta` / headers)
Stamped lists	Positive `ttlMs`, intentional `cacheScope` (`public` for static catalogs)
Stable tool order	Same process, same order across N list calls
HTTP road (if claimed)	Streamable HTTP + `Mcp-Method` / `Mcp-Name`; no fake “we’re remote-prod” without auth
Honest claim surface	Docs + CI prove what you claim; no deprecated Roots/Sampling/protocol Logging as greenfield features
MRTR / Tasks / OAuth	Real, but not required to be a BETTER tools textbook on day one — document later if you go deep

BETTER is not “more tools.” BETTER is claim = wire.

If MCP had an AGENTS.md

One box. Steal it for every server README you touch:

## Operational contract (7/28)
- Protocol: 2026-07-28
- Lifecycle: Discover-compatible (not initialize-only)
- tools/list: ttlMs + cacheScope + stable order
- Transports: stdio (default) · Streamable HTTP (if enabled — document bind + auth posture)
- Non-goals: (resources / OAuth / Tasks — say so if out of scope)
- Prove it: (link CI / smoke that fails when you lie)

Short. Specific. Actionable. Same discipline as a good AGENTS.md — facts the peer can verify, not vibes.

10-minute textbook: `mcp-better`

mcp-better is a small Rust server built for this era — not a product platform. Two tools: health, echo. Official rmcp 3. Discover-compatible. Stamped list. v0.1 = 7/28 over stdio. v0.2 = same era + opt-in Streamable HTTP (local demo).

On crates.io and the MCP Registry as io.github.Wolfe-Jam/mcp-better.

Step 1 — Install

cargo install mcp-better --version 0.2.0
mcp-better --help

First install compiles Rust deps once — one-time wait; then you’re done.

Step 2 — Run stdio (default)

mcp-better

Point a Discover-capable client / smoke at it. Or from the repo:

git clone https://github.com/Wolfe-Jam/mcp-better.git
cd mcp-better
cargo build --bins
cargo run --example stdio-client

Expect: negotiated 2026-07-28, list stamps (ttlMs / cacheScope), tools in stable order: health, then echo.

Step 3 — Optional HTTP road (same era)

mcp-better --http
# http://127.0.0.1:8787/mcp

Local demo only — no auth/TLS (see the repo SECURITY.md). From source, http-smoke exercises list + health + echo with Mcp-Method / Mcp-Name.

Step 4 — What you just proved

Claim	Evidence
Built for 7/28	Discover path + era string
List cache	Positive `ttlMs`, `public` scope for a static catalog
Dual transport	stdio default · HTTP opt-in — not a second protocol “version”
Small surface	Two tools — enough to teach the contract

That’s the point of a textbook: copy the operational contract, not a 40-tool megaserver.

What this is not

Not a tour of every SEP.
Not “everyone has migrated.” Hosts and SDKs roll out on their clocks (Claude products are rolling 7/28 support — see Anthropic’s post).
Not a connector-directory pitch. Open Registry + honest wire still matter when app-store shelves optimize for other shapes.
Not a product install funnel. One runnable example. One checklist.

Close

7/28 is hot for a reason. The big deal is STATELESS — Discover, stamped lists, and honest HTTP headers are how the wire enforces that.

If you only remember one line: same tool name ≠ same operational server. Audit the contract. Ship the smoke. Prefer BETTER over banner.

I’m an AAIF Ambassador. This piece is public MCP education — the kind of practical path the program exists for. Questions welcome.

AGENTS.md Series Wrap: Five Lessons, FAQs, and What I'd Do Differently

wolfejam.dev — Tue, 28 Jul 2026 14:48:53 +0000

TL;DR — Five posts. One file. The whole arc: what it is → write one → why it rots → keep it true → author from facts. This is the wrap: the map of the series, five FAQs, and the lesson that stuck — facts block vs unique prose.

📚 The AGENTS.md Series · you're on Part 6 — Series wrap

New here? AGENTS.md is a single Markdown file at the repo root that tells AI coding agents how to work in it — commands, tests, conventions, guardrails. Open standard under the AAIF / Linux Foundation. Start at Part I if you want the full path.

What we covered

Five lessons. One job: make the briefing agents obey true.

Part	Role	One line
I	Field guide	What belongs in AGENTS.md — and what doesn't
II	Hands-on	Build a real file, then point an agent at it
III	The threat	A stale file is still obeyed — at full confidence
IV	Discipline	Same-PR anti-rot, verify with an agent, keep truth current
V	Endgame	Author from repo facts so the file can't drift

If you only read one besides this wrap: III if you've never felt rot; V if you already have a file and want it to stop lying.

Step-through: how the arc fits

Read it as a single path, not five islands.

I   What is AGENTS.md?          →  principles, shape, anti-patterns
II  Write one                   →  real file, real agent payoff
III Watch it go stale           →  why "present" ≠ "true"
IV  Keep it true by hand        →  human discipline while the code moves
V   Stop hand-maintaining facts →  regenerate what the tree already knows
VI  This post                   →  map · FAQs · the lesson that remains

I and II get you a file that works.

III and IV get you a file that stays honest under change.

V removes the class of lines that should never have been typed by hand.

VI (here) is the map and the judgment call: what still needs a human.

The series does not argue for a longer AGENTS.md. It argues for a truer one: a concise facts block, then your prose. Overall length is yours.

Five FAQs

1. Do I need AGENTS.md if I already have README / CONTRIBUTING / CLAUDE.md?

Yes, if agents work in the repo. README is for humans browsing. CONTRIBUTING is process. Vendor files (CLAUDE.md, etc.) are tool-specific. AGENTS.md is the tool-agnostic briefing many agents already look for. Keep it short; link out for depth. Don't duplicate a novel.

2. How long should it be?

Short enough that an agent (and a human) will still trust every line. Prefer commands you can run, paths that exist, and guardrails that bite. If a section can't be verified against the tree or a one-line rule, cut it or move it.

3. What's the #1 failure mode?

Stale truth that still looks official. Renamed scripts, dead test commands, structure maps that lag the tree — the agent obeys them at full confidence. Part III is the whole point. Freshness is not a nicety; it's the product.

4. Should every line be auto-generated?

No. Generate (or check) what the repo can prove: package names, scripts, layout, CI commands. Keep human what only a human owns: judgment, product "why," team norms that aren't in the tree, "never do X" that isn't a linter rule yet. Part V is the endgame for the facts half — not a replacement for judgment.

5. Where do I start if I have nothing?

Part I — shape and anti-patterns
Part II — write one and verify with an agent
When it starts lying, IV then V

Don't skip III forever — you'll meet it the hard way.

My lesson: facts block vs unique prose

If the series leaves one idea standing, make it this.

	Facts block	Unique prose
What	Things the repo already knows or can prove	Things only a human should assert
Examples	Build/test commands, package layout, entrypoints, CI checks	Why the product exists, team taste, soft norms, hard "never" that isn't encoded yet
Failure mode	Drift (tree moves, file doesn't)	Vagueness or lecture that no agent can act on
Fix	Author/check from the tree; fail CI on drift (V)	Write short, actionable, owned by a human; same PR as the change when norms move (IV)

BETTER AGENTS.md = facts that match the tree plus prose that earns its tokens.

I used to treat the whole file as "documentation I should maintain." The series taught me to split the job: automate honesty for the map; reserve human attention for judgment. That's the difference between a file that exists and a file that deserves to be trusted.

What "good" vs "BETTER" looks like in practice

	Good	BETTER
File exists at repo root	✓	✓
Agent can follow setup/test	Often	Commands match `package.json` / `just` / CI today
Structure / map	Hand-wavy or partial	Matches live tree (or deliberately points at it)
Stale lines	"We'll fix later"	Same PR as the change, or regenerate facts
Length	Long and impressive	Short and true

Goose, Cursor, Claude Code, Copilot, Codex — none of them need your autobiography. They need a briefing that won't send them into a renamed script at full confidence.

Q&A / feedback

This wraps the series for the AAIF Ambassador program — A practical, vendor-free AGENTS.md guide.

I'd like to hear from you:

Where does your AGENTS.md rot first (commands, structure, guardrails, something else)?
Did you try authoring from facts (Part V) — what broke?
What's still missing from the open AGENTS.md conversation that these five parts didn't touch?

Comment on this post, or open a discussion on a project you care about (for example: keep that repo's Structure true to crates/ / src/). The standard gets better when real trees push back on pretty docs.

Series index (bookmark this)

AGENTS.md: The One File That Makes AI Coding Agents Actually Useful — field guide
AGENTS.md, Hands-On: Build One Step by Step — tutorial
Your AGENTS.md Is Already Stale (And Your Agent Trusts It Completely) — the threat
AGENTS.md Kept True: Stop the Rot Step by Step — discipline
AGENTS.md From Facts: Author One That Can't Drift — endgame tool path
This post — wrap · FAQs · facts vs prose

Further reading: the standard itself at agents.md, and a section-by-section field guide — what earns a line, ordering, length, the anti-patterns — at faf.one/agents.

Thanks for reading the series.
Ship a short true file.
Then keep it true.
👍

AGENTS.md From Facts: Author One That Can't Drift (Step by Step)

wolfejam.dev — Fri, 24 Jul 2026 12:00:00 +0000

TL;DR — Parts I–IV got you a real AGENTS.md and the discipline to keep it honest. This is the endgame Part IV pointed at: stop hand-maintaining lines the repo already knows. Author a minimal file from detected facts, protect human notes outside markers, fail CI when it drifts, point an agent at it. Six steps. One CLI. Facts only.

Series: I · field guide → II · hands-on → III · stale → IV · keep it true → you're on V.

Why the file still earns its keep

Twenty seconds on why AGENTS.md exists before we automate it:

Benefit	What the agent gets
Faster first move	Real setup / build / test commands — no guessing the runner
Self-check loop	Tests as the bar for "done" — re-derive truth from the world
Less interruption	Map + conventions — fewer "where do routes go?" questions
Fewer expensive mistakes	Guardrails (always / ask first / never) + definition of done
One briefing, many tools	Tool-agnostic Markdown — Cursor, Claude Code, Codex, Copilot, goose, Grok, peers

Short. Current. Specific. Actionable. Parts I–II covered what and how to write it. Parts III–IV covered why it dies and the human discipline that keeps it alive.

Part IV Step 5's honest endgame: regenerate from the repo so the file can't drift. This is that tutorial.

In one line: Part II taught you to write the file · Part IV taught you to keep it true · Part V hands you the tool — stop hand-maintaining what the tree already knows. Ready?

The trap

Two failure modes, both real:

Hand-written and left alone → it rots. You rename a script; the agent still runs the old one at full confidence.
"Let an AI write the whole file" → it bloats. Research (Gloaguen et al., 2026) found LLM-written instruction files can reduce task success and raise cost — plausible padding the agent over-obeys.

The fix is not more vibes. Facts only: every managed line traces to something the tree already declares — real scripts, real configs, real entry points. Nothing invented. Nothing padded.

That's agents-md-facts: a small CLI that authors a minimal AGENTS.md from repo facts. Open a real project and follow along.

Step 1 — Dry-run first

Any repo with a real package.json, pyproject.toml, Cargo.toml, or go.mod:

npx agents-md-facts --dry-run

You get the plan — orientation, setup/build, tests, map, conventions, guardrails, definition of done — without writing a file. Sanity-check: are those the commands you actually run? If not, fix the scripts/config (source of truth), not the prose later.

Optional — managed block only:

npx agents-md-facts --stdout

Step 2 — Author (or refresh)

npx agents-md-facts

Writes or refreshes AGENTS.md at the repo root. Managed region:

<!-- agents:from-facts:start -->
<!-- authored by agents-md-facts — from your repo's facts, never guessed · re-run to refresh -->

# AGENTS.md — your-project

…

<!-- agents:from-facts:end -->

Non-destructive: everything outside those markers is yours. Re-run anytime; hand-written notes survive. Put tool quirks, domain gotchas, and "don't touch this without a human" outside the block. Author the rest from facts.

Step 3 — Read it like an agent

Open the file. Shape for a small Node/TS example (exact style from the tool's examples):

Orientation

TypeScript · Node.js · npm package manager · v1.0.0

Setup & build

npm install    # install dependencies
npm run build    # build
npm run dev    # dev

Run the tests

npm run test
npm run lint

Where things live

package.json
src/index.ts
tsconfig.json

Conventions

TypeScript strict mode (tsconfig.json)
ESM modules (type: module)
Style enforced by ESLint · Prettier — obey the configs

Guardrails

Always OK: read files, run the tests (npm run test), build the project.
Ask first: dependency installs, deletions, migrations / schema changes.
Never: force-push, commit secrets.

Definition of Done

Done when: npm run lint exits 0 · npm run test passes · committed with a clear message.

Part IV rules, automated:

Commands copy-pasteable and backticked as literals
Tests where the agent needs a feedback loop
Conventions point at configs — don't restate "use 2 spaces"
Guardrails enable-first (always / ask / never)
Definition of Done mechanically checkable

If a line wouldn't resolve an ambiguity for a fresh agent, the tool drops it. Short by construction.

Step 4 — Human layer (outside the markers)

Facts can't know product judgment. Below the end marker (or above the start), add what only you know:

<!-- agents:from-facts:end -->

## Project notes (human)

- Prefer the query builder in `src/db/` — no raw SQL in handlers.
- Feature flags live in `src/flags.ts`; don't hardcode rollout in routes.
- Billing code is off-limits without a human in the loop.

Next refresh leaves this intact. Machine-owned facts inside · human-owned judgment outside.

Step 5 — Make drift a build failure

Part IV's anti-rot rule: AGENTS.md changes in the same PR as the code. Automate it.

Local / CI:

npx agents-md-facts --check

Exits 1 if missing or the managed block is stale vs the repo.

GitHub Action:

# .github/workflows/agents-md.yml
name: AGENTS.md
on: [push, pull_request]
jobs:
  check:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: Wolfe-Jam/agents-md-facts@v0.1.0

Pre-commit:

# .pre-commit-config.yaml
repos:
  - repo: https://github.com/Wolfe-Jam/agents-md-facts
    rev: v0.1.0
    hooks:
      - id: agents-md-facts

Then: pre-commit install.

When scripts or layout change, fix in the same PR:

npx agents-md-facts

Treat the file like code — because your agent already does.

Step 6 — Verify with an agent

Same proof as Parts II and IV. Small real task:

"Add a tested /health endpoint."

Watch for:

It reads AGENTS.md first.
It runs the exact test/lint commands from the file.
It respects Always / Ask / Never.
It hits Definition of Done without you re-explaining the toolchain.

If it runs the wrong command or ignores a convention, the file (or the underlying scripts) lied — fix the fact source, re-author, re-check. Don't scold the agent for trusting the briefing you gave it.

What this does not replace

Still yours	Why
Judgment outside markers	Facts don't know billing, legal, or when to "ask the Owner first"
README for humans	AGENTS.md = how to work; README = what/why
Code review	A true file helps the agent; humans still ship
Lint of your prose	Complements bloat-linters — this authors clean from truth

You can still hand-write the whole file (Part II). You can still run Part IV without a generator. The CLI is for lines that should never have been hand-copied from package.json in the first place.

The loop, closed

Part	What you learned
I	What belongs · anti-patterns · short > complete
II	Build section by section · watch an agent use it
III	Stale cache worse than empty · facts only
IV	Same-PR updates · point-at-config · enable-first guardrails
V (this)	Author from facts · markers · `--check` · CI · agent verify

Short. Current. Specific. Actionable. And now re-derivable from the tree — so the agent stops inheriting last sprint's lies.

Where to go deeper

Series: I · II · III · IV · V (you are here)

Tool (source + stars) — github.com/Wolfe-Jam/agents-md-facts · npx agents-md-facts
Standard — agents.md
Field guide (what earns a line, length, anti-patterns) — faf.one/agents

⭐ If this saved you a hand-written or LLM-bloated AGENTS.md, a star on the repo helps others find it.

Keep the facts honest. Your agent only ever trusts the last true thing you told it.

AGENTS.md, Kept True: Stop the Rot Step by Step (and Watch Your Agent Trust It)

wolfejam.dev — Sat, 11 Jul 2026 17:56:44 +0000

TL;DR — A good AGENTS.md isn't written, it's maintained — and the maintenance is where every one dies. Here's the exact discipline that keeps yours true: tie every line to a fact in the repo, verify it runs, and make it change in the same PR as the code. Six steps, one worked example, and an agent that stops guessing.

You've got an AGENTS.md — maybe you built one step by step. The problem now isn't writing it. It's that, as we covered, it goes stale the day you write it — it starts lying the moment your code moves, and your agent believes it anyway. So let's harden it. Open a repo and follow along.

Step 1 — Start from the truth, not a template

Before you write a line, list what's actually real:

cat package.json | jq .scripts     # your real commands
ls src/                            # your real entry points
ls .eslintrc* tsconfig.json 2>/dev/null   # your real conventions (the configs)

Rule for the whole file: if it isn't in the repo, it doesn't go in the AGENTS.md. No aspirations, no "we should probably." Facts only.

Step 2 — Write the commands copy-pasteable, then RUN them

Don't type npm build from memory. Run it, and paste what actually works:

npm run build && npm test

Put the exact strings in the file. If the command in your AGENTS.md doesn't run, your agent's first move fails — and it won't know why. Tests go above build: they're the agent's only way to check its work against reality.

And wrap every tool and command name in backticks — mypy, ruff, npm test. A formatted token reads as a literal to run, not a vague suggestion the model can paraphrase away when the context is saturated.

Step 3 — Point at the config; don't restate it

You already have a linter and a formatter. So don't write "use 2 spaces, prefer const, strict types." Write:

## Conventions
- Style is enforced — run `npm run lint`. Obey the config, don't hand-format.
- TypeScript strict mode (tsconfig.json).

Restating a rule your linter owns is how the file goes stale (you change the config, the prose lies). Point at the source of truth instead. One line, can't rot.

Step 4 — Guardrails in three tiers + a Definition of Done

Give the agent a safety map and a finish line:

## Guardrails
- **Always:** read files, run the tests, build.
- **Ask first:** dependency installs, deletions, migrations.
- **Never:** force-push, push to `main`, commit secrets.

## Definition of Done
Done when: `npm run lint` exits 0 · `npm test` passes · committed with a conventional message.

Now the agent can know it's finished, not guess — and it knows which moves need a human.

One phrasing note that punches above its weight: lead with the enable, not the prohibition. "Branch and open a PR" hands the agent the safe path; a bare "don't push to main" hands it only the landmine — and a naked negative can prime the very move it's warning against. Say what to do, then the boundary.

Step 5 — The anti-rot rule: it changes in the same PR as the code

This is the step everyone skips, and it's the whole game. Make drift a bug, not a someday:

Add it to your PR template: "Touched build/test scripts? Update AGENTS.md."
Or a CI check that fails if package.json scripts changed but AGENTS.md didn't.
Or — the honest endgame — regenerate the file from the repo so it can't drift (more on that below).

Treat AGENTS.md like code, because your agent already does.

Step 6 — Verify: point your agent at it and watch

Give the agent a small, real task ("add a tested /health endpoint"). Watch it: read the file, run the tests you listed, respect the guardrails, hit your Definition of Done. If it does the wrong thing — wrong command, ignored convention — your file lied. Fix the line, not the agent.

That loop — task, watch, fix the line — is how an AGENTS.md earns trust. A true one becomes the most reliable thing in your repo.

Where to go deeper

The series: 1 · the field guide → 2 · build one, hands-on → 3 · why it goes stale → you're on 4.

The AGENTS.md standard — agents.md (the spec itself).
Section-by-section definitions + a field guide — faf.one/agents (what earns a line, ordering, length, and the anti-patterns).
Why "generated from truth" beats hand-writing and AI-slop — the research and the deeper dive, same place.

Keep it honest, and your agent stops guessing. That's the whole point of the file.

Your AGENTS.md Is Already Stale — And Your Agent Trusts It Completely

wolfejam.dev — Fri, 10 Jul 2026 17:43:45 +0000

TL;DR — A hand-written AGENTS.md rots the day you write it. And unlike a stale README (which a human skims skeptically), a stale AGENTS.md is obeyed by your coding agent with full confidence: wrong build command, missing guardrail, dead convention — followed to the letter. The fix isn't more discipline. It's writing the file so every line traces to a fact you can verify, and refusing to let it drift.

In the field guide, I covered what an AGENTS.md is and what belongs in it. In the build-along, we wrote a complete one against a real repo and watched an agent use it. This is the part nobody warns you about — the part that decides whether all of that pays off: keeping it true.

Why you need to know this

You probably already have an AGENTS.md — or you're about to. Here's the part nobody says out loud: it's a cache, and a stale cache is worse than an empty one.

A human reads a stale README and thinks "hmm, that looks old." An agent reads your AGENTS.md and acts on it — it runs the build command you renamed three sprints ago, skips the guardrail you added last week, follows the convention you already abandoned. Confidently. No second-guessing.

So the real question isn't "should I have an AGENTS.md." (Yes.) It's "how do I keep it true?"

How to do it

A good AGENTS.md answers exactly one question: how do I work in this repo? Not what the project is — that's the README. How to actually operate here. Six moves:

1. Orientation — one line. What it is, the language, the stack. Then stop.

2. The real commands. Setup, build, and — most important — how to run the tests. Copy-pasteable. Tests rank above build, because tests are the agent's only way to check its work against reality instead of trusting a stale belief.

3. Where things live. Entry points and key directories — not a file dump (the agent can run ls). Just the non-obvious "start here."

4. Conventions — only what resolves ambiguity. "Validate input at the route boundary with Zod" is useful. "Write clean code" is ignored. And if a rule is already enforced by your linter or formatter, point at the config — don't restate it.

5. Guardrails — what NOT to do. The landmines. Three tiers is the sweet spot: what's always safe, what to ask first, what to never do (force-push, touch prod, commit secrets).

6. A definition of done. "Done when lint passes, tests pass, changes committed." Make it mechanically checkable — the agent should be able to know it's finished, not guess.

Keep it short — 20–50 lines. Every line earns its place by one test: does it resolve a real ambiguity, or save the agent an expensive hunt? If it does neither, cut it. (Past ~150 lines you're adding cost with no gain.)

The part almost everyone gets wrong

There are two failure modes, and they're opposite:

Hand-written and left alone → it rots. You change the code; the file quietly lies.
"Let an AI write it for me" → it bloats. The research here is blunt: auto-generated instruction files measurably reduce task success and add cost, because the model pads them with plausible-sounding requirements the agent then over-obeys.

The fix is the same for both: every line should trace to a fact. A real command. A real file. A real constraint. Not prose, not padding, not guesses. And when the code changes, the file changes in the same PR — treat it like code, because your agent already does.

Get those two things right — facts only, kept current — and your AGENTS.md stops being a liability and starts being the most reliable thing in the repo.

Why we care about this

We maintain a lot of repos, and we kept paying the same tax: the AGENTS.md goes stale, everywhere, every week. Getting the file right is an afternoon. Keeping it true is the harder half — and it's the half that actually decides whether your agent helps you or confidently ships you the wrong thing.

Write one well. Keep it honest. Your agent is only as good as the last true thing you told it.

Further reading: the standard itself at agents.md, and a section-by-section field guide — what earns a line, ordering, length, the anti-patterns — at faf.one/agents.

Coming next: the exact discipline to keep it true — step by step, stopping the rot, with an agent you can watch trust it.

AGENTS.md, Hands-On: Build One Step by Step (and Watch an Agent Use It)

wolfejam.dev — Sat, 04 Jul 2026 03:31:12 +0000

In the field guide I covered what an AGENTS.md is and what belongs in it. This is the hands-on follow-up: we'll build a complete AGENTS.md for a real project, one section at a time, then point an AI coding agent at it and watch the difference it makes. By the end you'll have a working file — and you'll have seen it pay off.

New to AGENTS.md? It's a single Markdown file at the root of your repo that tells AI coding agents how to work in it — build steps, tests, conventions, guardrails. The "why" behind each section is in the field guide.

The project we'll use

We'll write the AGENTS.md for a small but real service: a URL shortener API in Python — FastAPI, SQLite, pytest. A couple of endpoints, a thin data layer, a test suite. Follow along with this, or swap in your own repo — the steps are identical.

Its shape:

linkshort/
  app/
    main.py        # FastAPI routes
    db.py          # SQLite access
    models.py      # Pydantic models
  migrations/      # generated SQL — not hand-edited
  tests/
  requirements.txt

Step 0 — Start with an empty file

At the repo root:

touch AGENTS.md

That's the whole step. We'll fill it in one section at a time, building toward a file an agent can read in thirty seconds.

Step 1 — Orientation: one line

Tell the agent what it's looking at. Add:

# AGENTS.md

A URL shortener API in Python — FastAPI, SQLite, pytest.

One sentence sets the agent's priors: it knows the language, framework, and storage before it reads a single line of code.

Step 2 — Setup and run

The agent can't help if it can't start the project. Add the real, copy-pasteable commands:

## Setup
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

## Run
uvicorn app.main:app --reload   # http://localhost:8000

Use the commands that actually work in your repo — no placeholders.

Step 3 — Tests: the agent's feedback loop

This is the most important section, because tests are how the agent checks its own work. Add:

## Test — all must pass before a change is done
pytest
ruff check .
mypy app

Now the agent knows how to verify a change and the bar it has to clear. An agent that knows pytest will run it; one that doesn't hands you a broken branch.

Step 4 — The map: where things live

A short map so the agent finds its way without spelunking the whole tree:

## Structure
- app/main.py    route handlers
- app/db.py      SQLite access (parameterized queries only, never string-built SQL)
- app/models.py  Pydantic request/response models
- migrations/    generated SQL — do not hand-edit
- tests/         pytest, mirroring app/

Notice we're already slipping a convention ("parameterized queries only") and a guardrail ("do not hand-edit") in right where they're relevant.

Step 5 — Conventions: the house style

The patterns you want followed. Be specific — vague rules are noise:

## Conventions
- Validate all input with Pydantic models at the route boundary.
- Raise HTTPException for client errors; never return raw dicts on failure.
- Type everything; mypy must stay clean.
- Match the style of the surrounding file.

"Type everything; mypy must stay clean" tells the agent exactly what to do. "Write good code" wouldn't.

Step 6 — Commits and PRs

If your agent opens PRs, give it the house rules:

## Commits & PRs
- Conventional Commits (feat:, fix:, chore:).
- One logical change per PR; update CHANGELOG.md.

Step 7 — Guardrails: the landmines

The "don'ts" that prevent expensive mistakes:

## Don't
- Don't hand-edit migrations/ — they're generated.
- Don't commit directly to main — branch and open a PR.
- Never run the seed script against a non-local database.

Your finished AGENTS.md

Put it together and you have a complete, copy-pasteable file:

# AGENTS.md

A URL shortener API in Python — FastAPI, SQLite, pytest.

## Setup
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

## Run
uvicorn app.main:app --reload   # http://localhost:8000

## Test — all must pass before a change is done
pytest
ruff check .
mypy app

## Structure
- app/main.py    route handlers
- app/db.py      SQLite access (parameterized queries only, never string-built SQL)
- app/models.py  Pydantic request/response models
- migrations/    generated SQL — do not hand-edit
- tests/         pytest, mirroring app/

## Conventions
- Validate all input with Pydantic models at the route boundary.
- Raise HTTPException for client errors; never return raw dicts on failure.
- Type everything; mypy must stay clean.
- Match the style of the surrounding file.

## Commits & PRs
- Conventional Commits (feat:, fix:, chore:).
- One logical change per PR; update CHANGELOG.md.

## Don't
- Don't hand-edit migrations/ — they're generated.
- Don't commit directly to main — branch and open a PR.
- Never run the seed script against a non-local database.

Thirty seconds to read. Now let's see if it works.

Step 8 — Prove it: point an agent at it

This is the part that matters. Open your repo in an AI coding agent — Claude Code, Cursor, Codex, whatever you use — and give it a real task:

"Add a DELETE /links/{code} endpoint that removes a link, with a test."

Watch what it does with the AGENTS.md in place:

It reads the file first — it knows the stack and where routes live.
It adds the handler in app/main.py, validating input the way your conventions require.
It writes a pytest test in tests/, mirroring the structure.
It runs pytest, ruff, and mypy — because you told it that's the bar — and fixes what fails.
It doesn't touch migrations/, and it doesn't commit to main — it opens a branch.

Now picture the same task without the file. The agent has to guess: Which test runner? Where do routes go? Is there a lint step? So it asks you, or it guesses wrong, or it edits a generated file you'll have to revert. The AGENTS.md is the difference between an agent that interrupts you and one that just ships.

That's the whole payoff — and you can watch it happen in real time.

Keep it alive

One habit before you go: treat the file like code. When the test command changes, or you add a directory, or you catch yourself telling the agent the same thing twice — update AGENTS.md in the same breath. A stale file is worse than none, because the agent trusts it.

That's the loop

You started with an empty file, added eight short sections, and watched an agent use every one of them to land a correct, tested change without hand-holding. Write it once, and every agent that walks into your repo gets the same briefing.

This was the hands-on build. For the principles behind each section — what belongs, the anti-patterns, why short beats complete — see the field guide.

AGENTS.md: The One File That Makes AI Coding Agents Actually Useful

wolfejam.dev — Tue, 30 Jun 2026 01:51:07 +0000

If you’ve used Claude Code, Cursor, Codex, Aider, Gemini CLI, GitHub Copilot, Grok, goose, or similar tools, you’ve seen the same pattern: the agent’s first priority is context. What is this project? How do I build it? How do I run the tests? What conventions should I follow? What must I not break?

AGENTS.md is the open answer. It’s a single Markdown file placed at the root of your repository that serves as a dedicated, predictable briefing for AI coding agents. Think of it as a README written specifically for the agent instead of a human. The format is deliberately simple and tool-agnostic — one file that works across many agents.

AGENTS.md was pioneered by OpenAI's Codex and shaped alongside tools like Cursor, Amp, Factory, and Google's Jules. In December 2025 it was donated to the Agentic AI Foundation under the Linux Foundation, where it's now stewarded as an open standard.

Most AGENTS.md files fail in one of two ways: they’re either too thin to be useful or they’re long, rambling documents the agent skims and mostly ignores. A good AGENTS.md sits in the middle — short, current, specific, and actionable.

README is for humans. AGENTS.md is for the agent.

This distinction determines everything that belongs in the file.

README.md answers what and why: what the project is, why it exists, and how a human gets started.
AGENTS.md answers how to work here: the exact commands, conventions, and guardrails an agent needs to make changes and verify them without asking questions.

Do not duplicate content from the README. If the agent doesn’t need it to act effectively, leave it out. Every non-essential line dilutes the signal.

What actually belongs in AGENTS.md

The highest-value sections, in rough priority order.

One-line orientation. A single sentence telling the agent what the project is and what stack it uses — for example, “A TypeScript REST API on Node 20 with Postgres, deployed to Fly.io.”

Setup and build commands. The single most valuable section. Give the real, copy-pasteable commands:

npm install
npm run build
npm run dev

How to run tests. Even more important than build commands — tests are how the agent verifies its own work:

npm test          # all tests must pass before considering a change complete
npm run lint
npm run typecheck

Where things live. A short, focused map of key directories and entry points — not a full tree dump.

Conventions. Specific patterns you want followed: validation approach, error handling, naming, preferred libraries, architectural decisions. Vague statements like “write clean code” are useless; specific rules like “Validate all input with Zod at the route boundary” are useful.

Commit and PR rules. Message format, branch naming, changelog updates, and any other process requirements.

Guardrails — what NOT to do. The landmines that prevent expensive mistakes: don’t edit files in /generated, never run migrations against production config, and don’t commit directly to main.

The anti-patterns that make it worse than nothing

A bad AGENTS.md doesn’t just fail to help — it actively misleads the agent.

The novel: Too long. The agent skims and important instructions get lost. Cut anything that isn’t load-bearing.
The stale file: An outdated command or path is worse than no file at all. The agent will confidently do the wrong thing.
Vagueness: “Follow best practices” gives the agent nothing actionable.
Secrets: Never put credentials, keys, or tokens in AGENTS.md. Point to where they come from (.env, secrets manager) instead.
README duplication: Wasted tokens and maintenance burden.

Keep it alive — treat AGENTS.md like code

AGENTS.md files rot when no one owns them. Treat the file the same way you treat production code:

Review changes to it in pull requests.
Update it the moment reality changes (new test command, new directory structure, new convention).
Watch what the agent actually does. When it guesses, asks unnecessary questions, or touches something it shouldn’t, that’s usually a missing or stale instruction.

A useful habit: every time you find yourself giving the same instruction to an agent twice in chat, move that instruction into AGENTS.md.

One file, many agents

The strength of AGENTS.md is that it isn’t tied to any single tool. Most major coding agents either read it directly or converge on the same root-level instruction pattern. Write plain Markdown with tool-agnostic instructions. Avoid “if you are using X tool” branching.

For monorepos, you can place additional AGENTS.md files in subdirectories. Most agents use the nearest file to the code they’re working on.

A minimal, complete example

# AGENTS.md

A TypeScript REST API on Node 20, Postgres, deployed to Fly.io.

## Setup
npm install
cp .env.example .env   # fill in DATABASE_URL

## Build & run
npm run build
npm run dev            # http://localhost:3000

## Test — all must pass before a change is considered done
npm test
npm run lint
npm run typecheck

## Structure
- src/routes/     HTTP handlers
- src/db/         Postgres queries (use the query builder, no raw SQL)
- src/lib/        shared utilities
- test/           Vitest tests, mirroring src/ structure

## Conventions
- Validate all input with Zod at the route boundary
- Throw AppError (from src/lib/errors.ts), never a bare Error
- Match the style and patterns of the surrounding file

## Commits & PRs
- Use Conventional Commits (feat:, fix:, chore:)
- One logical change per PR
- Update CHANGELOG.md when relevant

## Don't
- Don't edit anything in src/generated/ (regenerated from schema)
- Don't commit directly to main — always branch and open a PR
- Never run db:reset against a non-local DATABASE_URL

An agent (or a new human teammate) can read this in under 30 seconds and start being productive.

The real test of a good AGENTS.md

You’ll know it’s working when a fresh agent can land a correct, tested change in your repository without asking how to build, how to test, or which conventions to follow — and without touching the one thing you explicitly told it not to touch.

Short. Current. Specific. Actionable. That’s the entire job.

This was the field guide — the why and the what.

Coming next in the series: a step-by-step build-along, where we’ll write a complete AGENTS.md against a real repo, then point an agent at it and watch it build, test, and respect the guardrails without being asked. (A day or two out.)

The Chameleon Edition - gemini-faf-mcp v2.4.0

wolfejam.dev — Tue, 09 Jun 2026 15:18:29 +0000

TL;DR: gemini-faf-mcp now auto-selects its transport — stdio locally, Streamable HTTP on Cloud Run. Same binary, 12 tools, zero config. One binary that's a local MCP server and a hosted one, decided by its environment.

One Command, Both Modes

gemini-faf-mcp reads its environment and adapts. Run it locally and it speaks stdio — the transport uvx and MCP clients expect. Set a PORT (as Google Cloud Run does) and the same binary serves modern Streamable HTTP: stateless, JSON, no SSE. No flags. No second package. No config. The server decides.

uvx gemini-faf-mcp        →  stdio   (local / MCP client)
PORT=8080  →  python app  →  Streamable HTTP  (Cloud Run)

Twelve tools either way. Identical behavior. The only thing that changes is the door it answers.

Why a Chameleon

A chameleon doesn't change what it is — it changes how it meets its surroundings. Same here: one codebase, 12 tools, one main() shared by the console script and the container. What shifts is the transport, chosen by where it runs.

Under the hood, the entry point passes the transport explicitly (transport="stdio" when local) instead of leaning on a framework default. The payoff is real: a strict MCP client that used to stall mid-handshake now connects cleanly — initialize, tools/list, tools/call, every time.

Drop It Into Google Antigravity

Google's agentic IDE, Antigravity, reads one MCP config file — and it accepts both modes.

Local (stdio) — in ~/.gemini/config/mcp_config.json:

{
  "mcpServers": {
    "gemini-faf": { "command": "uvx", "args": ["gemini-faf-mcp"] }
  }
}

Hosted (Streamable HTTP) — same file, the running endpoint:

{
  "mcpServers": {
    "gemini-faf": { "serverUrl": "https://mcpaas.live/gemini/mcp/v1" }
  }
}

One gotcha: Antigravity expects serverUrl — not url, not httpUrl. The same config works in the Gemini CLI, which converges into the Antigravity CLI.

Try It

uvx gemini-faf-mcp

Or point any MCP client at the hosted endpoint — tools execute on Google Cloud Run, fronted at the edge:

https://mcpaas.live/gemini/mcp/v1

The Numbers

v2.4.0 — Released June 7, 2026
12 tools — identical across both transports
221/221 — tests passing (FastMCP 3.4)
2 transports, 1 binary — stdio + Streamable HTTP
Google Cloud Run — tools execute hosted (us-east1)
PyPI + MCP Registry + Gemini Extensions — all on 2.4.0

Originally published on faf.one/blog/chameleon-edition

One-click MCP install for Claude Desktop (skip the JSON)

wolfejam.dev — Sun, 19 Apr 2026 22:28:57 +0000

If you've ever set up an MCP server for Claude Desktop, you've edited claude_desktop_config.json by hand.

Find the file. Figure out the right keys. Add a command, an args array, restart Claude. If you got the JSON wrong, Claude silently fails to load and you wonder why nothing works.

There's a better way, and almost nobody knows it exists.
.mcpb — Desktop Extension format

Anthropic ships a format called MCPB — a packaged MCP server you install like any native app.

Think .dmg on macOS or .exe on Windows, but for AI tools.

The flow:

Download the .mcpb file
Double-click
Claude Desktop installs it, restart, done

No terminal. No JSON. No "what's the right path to ~/Library/Application Support/Claude?"

Try it

Here's one I built: claude-faf-mcp — 32 tools for persistent project context that survives
sessions.

👉 Download claude-faf-mcp-5.5.1.mcpb

Double-click it. Claude Desktop opens the install dialog. Confirm. Restart. You now have 32 MCP tools live. Tell Claude to "extract context from my README" and it runs.

The catch

First download goes through your browser's Downloads folder. So technically it's "download → find → double-click" on first use.

Every .mcpb after that? Genuinely one click — Chrome remembers the "always open files of this type" preference and hands future .mcpb files straight to Claude Desktop. Safari is even more permissive.

Why this matters

MCP is about to have a lot of servers. The JSON-config install path doesn't scale to mainstream devs who don't want to touch config files. .mcpb is the format that changes that.

If you ship an MCP server, package it as .mcpb. Your non-technical users will actually install it.

TL;DR

.mcpb = Desktop Extension format for Claude Desktop
Way better than editing claude_desktop_config.json
Double-click install, 10 seconds
Try it: github.com/Wolfe-Jam/claude-faf-mcp

Define your project once, generate AGENTS.md + .cursorrules + CLAUDE.md + GEMINI.md

wolfejam.dev — Tue, 24 Feb 2026 06:43:02 +0000

Every AI coding tool invented its own context file:

Four prose files. Four places to keep in sync. Update one, forget another. Context rot
starts day one.

What if there was one source of truth?

project.faf is ~35 lines of structured YAML. IANA-registered as application/vnd.faf+yaml. It
defines your project once — stack, goals, conventions, architecture — and generates all
four formats:

npm i -g faf-cli
faf bi-sync --all

That's it. CLAUDE.md + AGENTS.md + .cursorrules + GEMINI.md from one file.

Three layers, three jobs:

.faf defines — structured YAML, machine-readable, single source of truth
.md files instruct — prose for each tool, generated from .faf
AI interprets — each tool reads its native format, no translation needed

What shipped in v4.5.0:

faf agents import/export/sync — full AGENTS.md interop
faf cursor import/export/sync — full .cursorrules interop
faf bi-sync --all — every format in one pass
87 new tests caught 3 cross-platform bugs (Windows \r\n, UTF-8 BOM, old Mac \r) before any user ever would
1,051 tests passing total

MIT licensed. Free forever. 23,000+ npm downloads across the ecosystem.

Blog post with diagrams: https://faf.one/blog/agents-md-edition

GitHub: https://github.com/Wolfe-Jam/faf-cli

The File That Sits Between package.json and README.md

wolfejam.dev — Tue, 27 Jan 2026 05:33:34 +0000

AI changed my auth system last year. Not a bug. Not a misunderstanding. It just... changed it. Confidently. Wrongly.

I went looking for the industry standard for AI context. The package.json for AI tools. The file that says "here's what this project is, here's how we do things."

It didn't exist.

So I built one.

The Alphabetical Accident

When I created project.faf, I didn't plan this. But look where it sits:

package.json    ← npm's context
project.faf     ← AI's context
README.md       ← human's context

Alphabetically, it lands exactly where it belongs. Between the machine context and the human context. That's not marketing - that's the filesystem.

The Problem: DAAFT

Without persistent context, AI operates in a cycle I call DAAFT:

Discover — "What is this project?"
Assume — "Probably React? Maybe TypeScript?"
Ask — "Which API are you using?"
Forget — Next session, repeat from step 1
Tokens — LOST (and time)

The math:

Without project.faf: ~1,750 tokens per session re-discovering your project
With project.faf: ~150 tokens once

91% reduction. Nice.

But here's what nobody talks about.

Every session, AI's understanding shifts slightly. Different assumptions. Different mental model. After weeks, months — AI has drifted so far from reality it makes confident wrong decisions.

Then you blame AI. "It's hallucinating." "It doesn't understand." "AI is overhyped."

No. Your context drifted. AI is working with what it has.

That's how my auth system got changed. AI wasn't broken. My context was.

project.faf doesn't just save tokens. It makes drift impossible. The foundation doesn't move. AI stays aligned with your project, forever.

Stop blaming AI. Fix the drift.

The Fix: project.faf

project:
  name: "acme-dashboard"
  goal: "Real-time metrics for engineering teams"
  main_language: typescript

stack:
  frontend: react
  backend: node
  database: postgres
  hosting: vercel

human_context:
  who: "Engineering team at Acme Corp"
  what: "Internal tool replacing spreadsheet workflows"
  why: "Manual reporting takes 10 hours/week"

That's it. YAML. Human-readable. AI-readable.

When AI loads this first, it doesn't guess. It knows.

What's in v4.0

Bi-Sync

One source of truth that stays aligned with every AI's context file:

project.faf ←→ CLAUDE.md
            ←→ GEMINI.md
            ←→ conductor/
            ←→ any context file

8 milliseconds average sync time. You edit one, the others update. Context drift becomes impossible.

faf bi-sync --watch

Universal Format Detection

FAF scans your project and detects 154 framework/config combinations automatically:

$ faf formats

Detected formats:
  ✓ typescript (tsconfig.json)
  ✓ react (package.json → dependencies)
  ✓ vite (vite.config.ts)
  ✓ tailwind (tailwind.config.js)
  ✓ eslint (.eslintrc)
  ✓ prettier (.prettierrc)

Framework pyramid: 6 formats detected

AI-Readiness Scoring

$ faf score

project.faf analysis:
  Project basics:  100% (3/3 slots)
  Stack coverage:  100% (5/5 slots)
  Human context:    80% (4/5 slots)

  Overall: 🏆 95% - Gold tier

  Missing: human_context.when
  Suggestion: Add target timeline or deadline

The score isn't arbitrary. It's slot-based. A minimal project needs ~4 slots. A full enterprise project might use 21+. The percentage is filled slots divided by needed slots.

At 100%, AI has complete context for your stack. No clarifying questions needed.

The Credentials

I'm not going to oversell this. Here's what's real:

IANA Registration: application/vnd.faf+yaml is now an official media type. Filed October 2025, approved October 30. The format has a home alongside JSON, XML, PDF.

Anthropic MCP: PR #2759 merged into the official Model Context Protocol registry. FAF works natively with Claude Desktop.

Downloads: 21,000+ across the ecosystem (faf-cli, claude-faf-mcp, faf-mcp, grok-faf-mcp).

License: MIT. Free forever. No enterprise tier. No upsell.

Getting Started

# Install
npm install -g faf-cli

# Initialize (do this FIRST on any project)
cd your-project
faf auto

# Check status
faf status --oneline
# 🏆 project.faf 100% | bi-sync ✓ | foundation optimized

# Keep synced
faf bi-sync --watch

That's it. Your project now has persistent AI context.

The Philosophy

FAF first. The earlier AI has your project.faf, the more tokens you save, more importantly--the more time you save, and it adds up. So, don't add it after months of development (although it works on any repo, of any age). Get into a new habit--Add it day one.

Foundation, not configuration. This isn't settings. It's the ground your AI builds on. You don't configure a foundation. You establish it.

Trust, not hope. With FAF, you're not hoping AI understands your project. You know it does.

What's Next

Native integrations with more AI tools
Conductor orchestration patterns
Enterprise patterns (monorepo support)
Community-driven format extensions

Try It

npm install -g faf-cli && faf auto

GitHub: github.com/Wolfe-Jam/faf-cli

Website: faf.one

AI changed my auth system because it didn't know my project.

Now it does.

What's your biggest frustration with AI context? I'd love to hear what's missing or what would make this more useful for your workflow.

Your AI Context Now Works Everywhere: faf-cli Google Gemini Edition

wolfejam.dev — Thu, 15 Jan 2026 22:52:51 +0000

published: true
tags: ai, devtools, gemini, claude

faf-cli v3.4.7 brings bidirectional interoperability between Claude and Gemini ecosystems.

If you've ever wished your Claude context files worked with Gemini (or vice versa), that's now a single command away.

## The Problem

Every AI assistant has its own context format:

Claude uses CLAUDE.md
Gemini uses GEMINI.md
Cursor, Windsurf, others have their own conventions

You maintain multiple files saying the same thing. When your project changes, you update one and forget the others. Your AI assistants diverge.

## The Solution: One Format, Every AI

The .faf format (Foundational AI-context Format) acts as a universal hub. One source of truth. Automatic sync. Every AI stays current.

## How It Works


bash
  faf gemini export

  That's it. Your .faf context becomes a native GEMINI.md that Gemini CLI understands.

  Why This Matters

  Switch AIs without losing context. Start in Claude Code. Continue in Gemini CLI. Your project DNA follows you.

  Team flexibility. Some prefer Claude. Others use Gemini. Everyone shares context through .faf.

  Future-proof. When the next AI launches, adding support is one export target away.

  Get Started

  npm install -g faf-cli
  faf init
  faf gemini export

  npm: https://www.npmjs.com/package/faf-cli
  Docs: https://faf.one
  Blog: https://www.faf.one/blog/google-gemini-edition

  ---
  The .faf format is IANA-registered and part of the official Claude MCP ecosystem (#2759).

DEV Community: wolfejam.dev

Not all MCP servers are equal — what 7/28 just made official

Same name, different machine

GOOD habits (pre-7/28 muscle memory)

BETTER after 7/28 (checklist you can audit)

If MCP had an AGENTS.md

10-minute textbook: mcp-better

Step 1 — Install

Step 2 — Run stdio (default)

Step 3 — Optional HTTP road (same era)

Step 4 — What you just proved

What this is not

Further reading (one hop)

Close

AGENTS.md Series Wrap: Five Lessons, FAQs, and What I'd Do Differently

What we covered

Step-through: how the arc fits

Five FAQs

1. Do I need AGENTS.md if I already have README / CONTRIBUTING / CLAUDE.md?

2. How long should it be?

3. What's the #1 failure mode?

4. Should every line be auto-generated?

5. Where do I start if I have nothing?

My lesson: facts block vs unique prose

What "good" vs "BETTER" looks like in practice

Q&A / feedback

Series index (bookmark this)

AGENTS.md From Facts: Author One That Can't Drift (Step by Step)

Why the file still earns its keep

The trap

Step 1 — Dry-run first

Step 2 — Author (or refresh)

Step 3 — Read it like an agent

Step 4 — Human layer (outside the markers)

Step 5 — Make drift a build failure

Step 6 — Verify with an agent

What this does not replace

The loop, closed

Where to go deeper

AGENTS.md, Kept True: Stop the Rot Step by Step (and Watch Your Agent Trust It)

Step 1 — Start from the truth, not a template

Step 2 — Write the commands copy-pasteable, then RUN them

Step 3 — Point at the config; don't restate it

Step 4 — Guardrails in three tiers + a Definition of Done

Step 5 — The anti-rot rule: it changes in the same PR as the code

Step 6 — Verify: point your agent at it and watch

Where to go deeper

Your AGENTS.md Is Already Stale — And Your Agent Trusts It Completely

Why you need to know this

How to do it

The part almost everyone gets wrong

Why we care about this

AGENTS.md, Hands-On: Build One Step by Step (and Watch an Agent Use It)

The project we'll use

Step 0 — Start with an empty file

Step 1 — Orientation: one line

Step 2 — Setup and run

Step 3 — Tests: the agent's feedback loop

Step 4 — The map: where things live

Step 5 — Conventions: the house style

Step 6 — Commits and PRs

Step 7 — Guardrails: the landmines

Your finished AGENTS.md

Step 8 — Prove it: point an agent at it

Keep it alive

That's the loop

AGENTS.md: The One File That Makes AI Coding Agents Actually Useful

README is for humans. AGENTS.md is for the agent.

What actually belongs in AGENTS.md

The anti-patterns that make it worse than nothing

Keep it alive — treat AGENTS.md like code

One file, many agents

A minimal, complete example

The real test of a good AGENTS.md

The Chameleon Edition - gemini-faf-mcp v2.4.0

One Command, Both Modes

Why a Chameleon

Drop It Into Google Antigravity

Try It

The Numbers

10-minute textbook: `mcp-better`