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/promotion-packet)<a href="https://agentmods.dev/rules/mohitagw15856/pm-claude-skills/promotion-packet"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/promotion-packet/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/promotion-packet"><img src="https://agentmods.dev/badge/rules/mohitagw15856/pm-claude-skills/promotion-packet.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 | $0.00080 | $0.00797 |
| Opus 5 | $0.00040 | $0.00398 |
| Sonnet 5 | $0.00016 | $0.00159 |
| Haiku 4.5 | $0.00008 | $0.00080 |
Grade A, and why
promotion-packet 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 7d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Promotion Packet Skill
Promotions reward demonstrated operation at the next level, not potential or tenure. The committee asks one question: is the evidence that they're already doing the next-level job? This skill builds the packet that answers it — mapping your work to each competency at the target level, surfacing the scope and impact that prove it, and honestly flagging the gaps so you submit when you'll actually win.
Required Inputs
Ask for these only if they aren't already provided:
- Current level → target level, and the ladder/rubric for the target level (the competencies it requires).
- Your evidence — accomplishments with impact (a
brag-docis ideal input). - Scope — the breadth of your influence (self → team → multi-team → org).
- Supporters — peers/stakeholders who can vouch, and for what.
Output Format
Promotion Packet — [name], [current] → [target]
1. Thesis — 2–3 sentences: you are already operating at [target], and here's the through-line of evidence. Promotion = recognition of current reality, framed this way.
2. Competency evidence — the core of the packet; one row per target-level competency:
| Target-level competency | Evidence (specific, with impact) | Scope |
|---|---|---|
| e.g. Drives multi-team initiatives | Led the X program across 3 teams → [outcome] | multi-team |
Every competency needs at least one strong, recent, evidenced example — gaps here are what sink packets.
3. Impact highlights — your 3–4 strongest wins, quantified, framed at the target level's expected scope.
4. Peer/stakeholder support — who will vouch and the specific thing each speaks to (leave quote slots).
5. Gap analysis (private, pre-submit) — competencies where the evidence is thin or stale, and a plan to close them. Submitting with visible gaps wastes a cycle; this section decides whether it's time.
Quality Checks
- The case is framed as "already operating at the next level", not "ready for / deserves it"
- Every target-level competency has at least one strong, recent, evidenced example
- Impact is quantified and framed at the target level's scope, not the current one
- Named supporters are mapped to specific competencies they can speak to
- A private gap analysis honestly flags weak spots and whether to submit now or next cycle
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.
- 7d ago First seen · 62 lines · 80 tokens per session scan A b9772197fc36
promotion-packet is a cursor rule published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 3d ago), licensed MIT. It adds 80 tokens to every session and 797 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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