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 pm-weekly-reviewgit 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/pm-weekly-review)<a href="https://agentmods.dev/skills/mohitagw15856/pm-claude-skills/pm-weekly-review"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/pm-weekly-review/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/pm-weekly-review"><img src="https://agentmods.dev/badge/skills/mohitagw15856/pm-claude-skills/pm-weekly-review.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 | $0.00064 | $0.01239 |
| Opus 5.5 | $0.00026 | $0.00496 |
| Sonnet 5.5 | $0.00013 | $0.00248 |
| Haiku 4.5 | $0.00006 | $0.00124 |
Grade A, and why
pm-weekly-review 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM Weekly Review Skill
Turn the chaotic end-of-week brain dump into a structured 20-minute ritual that keeps you, your team, and your stakeholders aligned — without a meeting.
Not quite this? Use
weekly-review-ritualwhen you want a personal GTD-style weekly review rather than a product review.
The Weekly Review Structure (20 minutes)
5 min — Metrics check: What moved? What didn't? What's surprising? 5 min — Ship progress: What shipped? What slipped? What's blocked? 5 min — Insights: Any customer feedback, support tickets, or research findings? 5 min — Next week priorities: What are the 3 things that matter most?
Output Format
PM Weekly Review — Week of [Date]
Product Area: [What you own] Written by: [PM Name] Time to read: ~3 minutes
📊 Metrics This Week
| Metric | This Week | Last Week | Target | Trend |
|---|---|---|---|---|
| [Primary metric] | [Value] | [Value] | [Target] | ↑ / ↓ / → |
| [Secondary metric] | [Value] | [Value] | [Target] | ↑ / ↓ / → |
| [Health metric] | [Value] | [Value] | [Target] | ↑ / ↓ / → |
Notable movement:
- [What changed and why — 1 sentence each]
Concern to watch:
- [Anything trending in the wrong direction]
🚢 This Week's Progress
Shipped:
- ✅ [What went live] — [1-line impact or observation]
In Progress:
- 🔄 [Feature/initiative] — [% complete or current status]
Slipped / Blocked:
- ⚠️ [What didn't happen] — Reason: [brief] — Action: [who's unblocking it]
Carry-forward to next week:
- [Item + why it's carrying over]
💡 Insights & Signals
Customer feedback:
- "[Quote or paraphrase]" — Source: [user/channel] — Theme: [tag]
Support signals:
- [Top ticket category this week + volume]
- [Anything that signals a product gap]
Research / data:
- [Any discovery from user interviews, analytics, or experiments]
🎯 Next Week — Top 3 Priorities
| # | Priority | Why This Week | Owner | Done = |
|---|---|---|---|---|
| 1 | [Most important thing] | [Reason it can't wait] | [Name] | [Clear definition of done] |
| 2 | [Second priority] | [Why] | [Name] | [Done criteria] |
| 3 | [Third priority] | [Why] | [Name] | [Done criteria] |
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 · 142 lines · 64 tokens per session scan A dea32bd5ed3b
pm-weekly-review is a skill published in the GitHub repository mohitagw15856/pm-claude-skills (1,449 stars, last pushed today), licensed MIT. It adds 64 tokens to every session and 1,239 once invoked, about $0.0003 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.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…