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.
git 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/rules/mohitagw15856/pm-claude-skills/brag-doc)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/brag-doc"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/brag-doc/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/rules/mohitagw15856/pm-claude-skills/brag-doc"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/brag-doc.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 | $0.00078 | $0.00827 |
| Opus 5 | $0.00039 | $0.00413 |
| Sonnet 5 | $0.00016 | $0.00165 |
| Haiku 4.5 | $0.00008 | $0.00083 |
Grade A, and why
brag-doc 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 6d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brag Doc Skill
Nobody remembers in December what they shipped in March — so good work goes uncredited at review time.
A brag doc is the fix: a running, dated log of what you did and the impact it had, captured while it's
fresh. This skill turns a pile of "stuff I did" into impact-first entries you can paste straight into a
self-review or promotion-packet.
Required Inputs
Ask for these only if they aren't already provided:
- The win(s) — what you did (rough notes are fine; the skill structures them).
- Impact — the outcome and any metric (before → after, time saved, revenue, users) — even a rough one.
- Scope & role — your specific contribution vs. the team's, and who it affected.
- Date / period and any evidence (PR, doc, dashboard, kudos, ticket link).
Output Format
Brag Doc — [your name], [period]
Entries newest-first, grouped by theme (or quarter). Each entry is impact-first:
[Verb-led headline — the outcome, not the task] · [date]
- What I did: [the specific action and your role in it]
- Impact: [metric / outcome — before → after where possible]
- Scope: [who/what it affected — team, org, customers]
- Evidence: [link]
- Maps to: [the competency / ladder level it demonstrates — e.g. "cross-team influence"]
Example:
Cut onboarding drop-off 18% → 9%, unlocking ~$140k ARR · Mar 2026
- What I did: led the redesign of the 3-step signup flow; wrote the PRD, drove eng + design alignment.
- Impact: activation 41% → 52%; drop-off halved (measured over 6 wks, 20k users).
- Scope: owned end-to-end; affected all new signups.
- Evidence: [PRD] · [dashboard]
- Maps to: drives measurable product outcomes; cross-functional leadership.
End with a "Themes this period" summary — the 3–4 narrative threads your wins ladder up to.
Quality Checks
- Every entry leads with impact/outcome, not the activity
- Metrics include the baseline (before → after), not a bare percentage
- Your specific contribution is distinguished from the team's
- Each entry links real evidence
- Entries are tagged to a competency/ladder level, so the doc feeds a review or promo case directly
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.
- 6d ago First seen · 66 lines · 78 tokens per session scan A 9c8ea0b95ec7
brag-doc is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 2d ago), licensed MIT. It adds 78 tokens to every session and 827 once invoked, about $0.0004 per session on Opus 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 2026-09-03.
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angular-20
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dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
cli-error-handling
CLI command error handling patterns.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.