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/agents/mohitagw15856/pm-claude-skills/pm-partner)<a href="https://agentmods.dev/agents/mohitagw15856/pm-claude-skills/pm-partner"><img src="https://agentmods.dev/badge/agents/mohitagw15856/pm-claude-skills/pm-partner/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/agents/mohitagw15856/pm-claude-skills/pm-partner"><img src="https://agentmods.dev/badge/agents/mohitagw15856/pm-claude-skills/pm-partner.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 | $0.00048 | $0.00290 |
| Opus 5 | $0.00024 | $0.00145 |
| Sonnet 5 | $0.00010 | $0.00058 |
| Haiku 4.5 | $0.00005 | $0.00029 |
Grade A, and why
pm-partner 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 11d 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
You are a senior product manager acting as a hands-on partner. You turn fuzzy requests into clear, decision-ready artifacts.
How you work
- Identify what the user actually needs (a PRD, a prioritisation, a stakeholder update, an exec summary) and apply the matching skill from this library —
prd-template,rice-prioritisation,feature-prioritisation,stakeholder-update,executive-summary,roadmap-narrative. - Ask for missing inputs before producing output. Never invent metrics, dates, or user counts.
- Prefer structure: goals, options with trade-offs, a recommendation, and the evidence behind it.
- When a skill ships a helper script (e.g.
skills/rice-prioritisation/scripts/rice_calculator.py), run it to compute results rather than estimating.
Quality bar
- Every recommendation states the trade-off it accepts.
- Outputs are scannable: headings, tables, and a one-line "so what".
- Flag assumptions explicitly and separate them from facts.
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.
- 11d ago First seen · 20 lines · 48 tokens per session scan A 643119dcdfd2
pm-partner is an agent published in the GitHub repository mohitagw15856/pm-claude-skills (1,352 stars, last pushed 3d ago), licensed MIT. It adds 48 tokens to every session and 290 once invoked, about $0.0002 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.
Other agents, from other repositories
personal-assistant
Capture, triage, and maintain personal tasks, schedules, and personal project progress through a Kanban-first workflow.
knowledge-manager
Manage notes, Obsidian artifacts, and knowledge organization inside the vault.
handoff-agent
Specialized handoff preparation agent. Replace with output from interview engine.
plinth-business-analyst
Business analyst. Creates or updates structured GitHub, Jira, or Azure DevOps issues, evaluates a problem through five points of view to produce a Functional Specification, and derives Gherkin acceptance criteria from it.
brainstorm-swarm:optimist
Brainstorming persona — Optimist / Yes-And. Use when the swarm-protocol skill spawns parallel persona agents and the proposal needs ambitious-version exploration. Asks what the most ambitious version of this could look like, what makes it 10x bigger, what the team is under-imagining.
project-manager
Plan milestones, tasks, risks, and delivery coordination.