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/the-understudy)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/the-understudy"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/the-understudy/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/the-understudy"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/the-understudy.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 | $0.00110 | $0.01123 |
| Opus 5 | $0.00055 | $0.00562 |
| Sonnet 5 | $0.00022 | $0.00225 |
| Haiku 4.5 | $0.00011 | $0.00112 |
Grade A, and why
the-understudy 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 10d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The Understudy Skill
"Write it in my style" usually gets tone cosplay: the em-dashes copied, the judgment absent. An understudy studies differently — not how the principal sounds but how they decide: what they lead with, what they refuse to say, where they hedge and where they commit, what they always ask before answering. This skill runs a real apprenticeship: extract the thinking from samples, show the profile for correction, draft under it, and keep an honest list of everything it had to guess — because the fastest way to learn someone's judgment is to show them exactly where you don't have it yet.
What This Skill Produces
- A thinking profile built from samples: decision patterns, argument structure, commitments and hedges, taboos, signature moves — each with the evidence line it came from
- An understudy draft of the requested piece, written under that profile
- The couldn't-infer list: judgment calls the samples didn't cover, with the guess made and the question that would settle it
- A profile file the user can save and hand back next time (works with the Professional Brain convention)
Required Inputs
Ask for (if not already provided):
- 3–5 samples of the user's real work — ideally the same genre as the ask (their exec updates to draft an exec update), including at least one they're proud of and, if possible, one with visible edits or a decision they reversed
- The new piece to draft: audience, situation, what they want to happen
- Anything the samples predate: new role, new company, changed opinions
Process
- Study decisions, not diction. For each sample extract: what it leads with · what it conspicuously omits · where certainty lives vs where hedges live · how bad news is carried · what gets numbers and what gets narrative · the asks it makes and how bluntly. Note tone last.
- Write the profile in falsifiable lines. "Leads with the decision, then two reasons, never three" is checkable; "clear and concise" is horoscope. Every line cites its sample. Show the profile and invite corrections — corrections are the highest-value input this skill gets.
- Draft under the profile. Apply the decision patterns first, the voice second. Where the new piece demands a judgment the samples never made, make the closest-fit call, mark it inline with ⚠, and add it to the list.
- Deliver the couldn't-infer list. Each entry: the gap, the guess made, the one question that would close it. This list shrinking over sessions IS the apprenticeship.
- Offer the profile as a file (
understudy-profile.md) so the study cost is paid once.
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.
- 10d ago First seen · 102 lines · 110 tokens per session scan A c4e66f44188c
the-understudy is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,345 stars, last pushed 2d ago), licensed MIT. It adds 110 tokens to every session and 1,123 once invoked, about $0.0006 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 2026-08-30.
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