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/commands/mohitagw15856/pm-claude-skills/cn-career-ladder)<a href="https://agentmods.dev/commands/mohitagw15856/pm-claude-skills/cn-career-ladder"><img src="https://agentmods.dev/badge/commands/mohitagw15856/pm-claude-skills/cn-career-ladder/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/commands/mohitagw15856/pm-claude-skills/cn-career-ladder"><img src="https://agentmods.dev/badge/commands/mohitagw15856/pm-claude-skills/cn-career-ladder.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 | $0.00000 | $0.00420 |
| Opus 5.5 | $0.00000 | $0.00168 |
| Sonnet 5.5 | $0.00000 | $0.00084 |
| Haiku 4.5 | $0.00000 | $0.00042 |
Grade A, and why
cn-career-ladder 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.
What it actually says
Run the 职场晋升线 (Chinese workplace: report to promotion) workflow recipe for: $ARGUMENTS
This is a chain of skills. Run each stage in order and carry every stage's output forward as context for the next. Open with a one-line plan of the 5 stages, then ask once for any essential missing inputs. Don't re-ask between stages.
Run each stage under a clear ## Stage N: <name> heading:
- 周报: apply the
cn-weekly-reportskill to turn the raw notes into 周报 that lead with results and numbers, flag risks early and state next steps. - 复盘: apply the
cn-fupanskill to run a 复盘 on the year's biggest project: goals against results, causes, the lessons that transfer. - 年终总结: apply the
cn-year-end-reviewskill to write the 年终总结, achievements ranked by impact with numbers, honest problems and next year's measurable plan. - 述职: apply the
cn-shuzhi-deckskill to outline the 述职 deck page by page with a timed script built from the review. - 晋升答辩: apply the
cn-promotion-defenceskill to map the evidence against the target level, name the gaps, and rehearse the committee's hardest questions.
Write in Simplified Chinese unless the user asks otherwise. Do not invent numbers, projects or titles: work with what is given and mark assumptions. After the last stage, end with a 5-bullet "What you now have" recap linking each artifact to the stage that produced it, and a one-line next step.
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 · 19 lines · 0 tokens per session scan A 5b53787db6a0
cn-career-ladder is a command published in the GitHub repository mohitagw15856/pm-claude-skills (1,463 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 420 tokens. 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 2026-10-06.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.