Claude ai
PMM Sherpa MCP. Senior product marketing advisor across Claude.ai, Claude Code, ChatGPT, Codex, Gemini CLI, Antigravity. Four tools backed by a 38K-chunk corpus.From the repository description
npx -y skills add boommark/pmmsherpa-mcp --skill claude-aiAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
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SKILL.md
1.3 KB, 347 tokens by cl100k_base, as published. Nobody here has run it
name: pmm-sherpa description: > Calling guide for the PMM Sherpa MCP, a senior product marketing advisor with a curated 38K-chunk corpus (PMM books, podcasts, AMAs, practitioner blogs). Sherpa exposes four tools: ask_sherpa (advisory dialogue), draft_artifact (39 named PMM deliverables), get_feedback (pressure-test user work), and scope_pmm_research (Deep Research planner). This skill prescribes orchestration, voice, and Deep Research phasing. Tool descriptions handle what each tool does. trigger: auto auto_trigger_patterns:
- positioning
- messaging framework
- go-to-market
- GTM
- launch plan
- launch readiness
- competitive analysis
- battlecard
- ICP
- buyer persona
- value proposition
- product marketing
- pricing strategy
- sales enablement
- landing page copy
- landing page audit
- homepage critique
- narrative
- category
- win/loss
- analyst relations
- brand messaging
- thought leadership
- PMM advice
- PMM judgment
- PMM research
- product marketing research
(See pmm-sherpa-skill.zip for the installable artifact. The full skill body lives inside the zip.)
What ships with it: 2 files
6.5 KB alongside SKILL.md
- pmm-sherpa-skill.zip4.0 KB
- README.md2.5 KB
Gives 0 of the 12 instructions most context ai engineering skills give in 347 tokens
Counted across 1,193 of the 1,976 authors here whose files we hold, read 2026-08-07
- Dispatch a fresh implementer subagent per taskin 48 of 1193, across 19 files
- Dispatch a final code reviewer after all tasksin 33 of 1193, across 8 files
- Provide full task text to the subagentin 30 of 1193, across 9 files
- Review spec compliance before code qualityin 27 of 1193, across 10 files
- Make the hook script executablein 26 of 1193, across 8 files
- Re-snapshot after navigation or DOM changesin 25 of 1193, across 19 files
- Read files before editing themin 22 of 1193, across 11 files
- Answer subagent questions before proceedingin 22 of 1193, across 7 files
- Mark task complete in TodoWrite after approvalin 22 of 1193, across 6 files
- Merge hook into existing settingsin 21 of 1193, across 3 files
- Ask if installation is global or projectin 20 of 1193, across 2 files
- Copy the hook script to target locationin 20 of 1193, across 2 files
Said here and by no other author read
- use the pmm sherpa mcp tool
- call ask_sherpa for advisory dialogue
- call draft_artifact for named deliverables
- call get_feedback to pressure-test work
- call scope_pmm_research to plan research
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.