Agent skill packs are everywhere now. Open GitHub, search for "agent skills," and you will drown in repos promising to turn your AI coder into a 10x engineer. Most of them are just rehashed prompt templates that add noise, not signal.
We spent the last month hands-on with dozens of these packs for Gearscope. The seven below are the ones we kept installed after testing. Each one solves a real problem, not a hypothetical one.
1. Addy Osmani Agent Skills
Verdict: The full software development lifecycle, packed into 23 portable skills.
Key strength: This is not a grab bag of tips. Addy Osmani (yes, the Google Chrome team guy) built a complete engineering methodology that walks your agent from idea refinement through spec writing, planning, implementation, and shipping. Each skill chains into the next one. The craft is obvious.
Who should use it: Teams who want their AI agent to follow a real process instead of just vomiting code. If you have ever watched an AI coder skip the thinking and jump straight to breaking things, this pack fixes that.
2. Engram
Verdict: The most complete agent memory layer you can install right now.
Key strength: Your AI coder forgets everything between sessions. Engram fixes that. It is a single Go binary backed by SQLite with full-text search, and it gives your agent persistent memory across conversations. It exposes an MCP server, HTTP API, CLI, and even a TUI. When your agent finishes a session, it can store what it learned and pick up where it left off next time.
Who should use it: Anyone doing multi-session work with an AI coder. If you are tired of re-explaining your project architecture every time you open a new chat, Engram is the answer. It scored a perfect 5 across every review dimension we track.
3. Antigravity Awesome Skills
Verdict: The biggest skill pack on GitHub. Breadth is the whole point.
Key strength: 1,464 SKILL.md playbooks covering everything from brainstorming to security auditing to React component scaffolding. It works with Claude Code, Cursor, Codex CLI, Gemini CLI, and more. The editorial bundles group related skills together so you are not lost in a sea of options. An npm installer gets you going fast.
Who should use it: Developers who want coverage over depth. If you work across a lot of different stacks and want a skill ready for whatever weird task comes up, this is your library. Quality varies across 1,400+ skills, but the hits outweigh the misses.
4. Agent Toolkit for AWS
Verdict: The AWS-built skill pack every cloud-bound agent needs.
Key strength: Amazon shipped 43 skills (13 core, 30 specialized) covering CDK, CloudFormation, Bedrock, EC2, VPC networking, and data analytics. This is not community cosplay. It is the real reference material from the people who build AWS, formatted as installable agent skills. Three plugin bundles and a managed MCP server round it out.
Who should use it: Anyone deploying on AWS. If your AI coder is touching CloudFormation templates or CDK stacks without this pack, it is flying blind. The documentation quality is top tier, which matters because cloud infrastructure is one area where guessing gets expensive.
5. last30days
Verdict: The research engine that searches where Google cannot.
Key strength: This skill searches Reddit, X, YouTube, TikTok, Hacker News, Polymarket, and 10+ other platforms within a configurable time window. It scores results by real engagement metrics, then synthesizes a structured brief. Most AI research tools just glue together a few API calls. This one actually understands what "recent and relevant" means.
Who should use it: Developers who need market research, competitive analysis, or trend tracking as part of their workflow. If you build products and need to know what people are actually saying about a topic in the last month, not what an old training data snapshot thinks, install this. It scored a perfect 5 in our review.
6. Superpowers
Verdict: A disciplined engineering workflow that forces AI coders to think before they type.
Key strength: 14 interlocking skills that enforce brainstorm-before-building, spec writing, implementation planning, and test-driven development across eight different agent harnesses. It works with Claude Code, Codex CLI, Cursor, Gemini CLI, GitHub Copilot CLI, and others. The methodology is cohesive: each skill picks up where the previous one left off.
Who should use it: Developers who treat AI coders as pair programmers, not autocomplete on steroids. If you want your agent to follow TDD, write specs, and plan before coding, Superpowers lays down that structure.
7. Browserbase Skills
Verdict: The most complete agent skill pack for production browser automation.
Key strength: 13 skills from Browserbase covering web scraping, UI testing, cookie sync, serverless browser functions, and company research. The skills range from basic page fetching all the way to adversarial UI testing. Everything works through the browse CLI, and the documentation is unusually good for an infrastructure tool.
Who should use it: Anyone doing browser automation at any scale. If your agent needs to interact with web pages that do not have a nice API, this pack gives it the tools to do the job properly.
Quick Comparison
| Pack | Skills | Rating | Best For |
|---|---|---|---|
| Addy Osmani | 23 | 4/5 | Engineering methodology |
| Engram | 1 (memory system) | 5/5 | Persistent agent memory |
| Antigravity | 1,464 | 4/5 | Broad coverage |
| AWS Toolkit | 43 | 4/5 | Cloud infrastructure |
| last30days | 1 (research) | 5/5 | Multi-platform research |
| Superpowers | 14 | 4/5 | TDD-first workflow |
| Browserbase | 13 | 4/5 | Browser automation |
All seven are free and open source. Install what fits your workflow, skip what does not.
Reviews sourced from Gearscope, where we test agent tooling so you do not have to guess.
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