PM Skills is a collection of plain-Markdown instructions that teach AI assistants structured methods for handling professional, personal, and life-admin tasks. People use it with Claude, ChatGPT, Gemini, Cursor, Codex, and other supported agents for work such as writing product requirements, reviewing documents, or planning difficult situations.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mohitagw15856/pm-claude-skills --skill claude-project-setupgit clone --depth 1 https://github.com/mohitagw15856/pm-claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/claude-project-setup)<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/claude-project-setup"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/claude-project-setup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/claude-project-setup"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/claude-project-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00168 | $0.01088 |
| Opus 5.5 | $0.00067 | $0.00435 |
| Sonnet 5.5 | $0.00034 | $0.00218 |
| Haiku 4.5 | $0.00017 | $0.00109 |
Grade A, and why
claude-project-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Project Setup
An AI coding agent is only as good as the context it starts with — drop it into a repo with no orientation and it guesses at your architecture, conventions, and commands. A good CLAUDE.md (or equivalent project-context file) is the onboarding doc that turns flailing into fluency. This builds yours: the architecture and conventions the agent needs, the commands to run, the guardrails on what not to touch, and a habit to keep it current.
What This Skill Produces
- A structured CLAUDE.md — the sections an agent actually needs: what the project is, architecture/layout, key conventions, the commands (build/test/lint/run), and the do-nots
- The right altitude — enough to orient the agent fast, not an exhaustive doc it drowns in; signal over completeness
- Guardrails — what the agent must not touch, how to run tests before claiming done, and where irreversible actions need a human
- Convention capture — the implicit rules a human learns over months (naming, patterns, where things go) made explicit
- A commands block — the exact commands to build, test, lint, and run, so the agent verifies its own work
- A maintenance habit — updating it as the project changes so it doesn't drift into wrong
Required Inputs
Ask for these if not provided:
- The project — what it is, the stack, rough architecture
- The conventions — the patterns and rules you'd tell a new hire
- The commands — how to build, test, lint, run
- The danger zones — what an agent should never touch or must be careful with
- Your agent — Claude Code, Cursor, etc. (file name/location may differ)
Framework: Orient, Constrain, Verify, Maintain
- Orient fast. Lead with what the project is and its architecture at a glance — the agent needs the map before the details.
- Capture the implicit conventions. The rules a human absorbs over months (where files go, naming, preferred patterns) are exactly what an agent can't infer — write them down.
- Give the commands. Build/test/lint/run commands let the agent verify its own work instead of guessing — this single section prevents most bad output.
- Set guardrails. What not to touch, always-run-tests-before-done, and where a human must approve — so autonomy doesn't become damage.
- Keep the altitude right. Enough to be useful, short enough to be read — prune anything that doesn't change the agent's behavior.
- Maintain it. Update as the project evolves; a stale context file is worse than none because it misleads.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 68 lines · 168 tokens per session scan A 256312261131
claude-project-setup is a skill published in the GitHub repository mohitagw15856/pm-claude-skills (1,449 stars, last pushed today), licensed MIT. It adds 168 tokens to every session and 1,088 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-12.
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