Agent skill
skillsmp-skill-recommender
Recommend best-fit SkillsMP skills for a project's stack and delivery goals. Use when building a production skill set for a new project, replacing weak skills with stronger alternatives, auditing current skill coverage, or comparing candidate skills before installation.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/skillsmp-skill-recommender
SKILL.md
SkillsMP Skill Recommender
Select high-fit SkillsMP skills for a specific project and return a practical keep / replace / add plan.
When to Use This Skill
- Building a production skill set for a new project
- Replacing low-quality or low-fit skills in an existing stack
- Comparing candidate skills for the same capability
- Auditing whether current skills cover required delivery areas
- Creating a focused install list from a broad project description
Invocation
User invokes this skill by describing the project they want to build.
Examples:
- "Use $skillsmp-skill-recommender to build a production skill stack for my project."
- "Use $skillsmp-skill-recommender and suggest skills even if my stack is not finalized yet."
Input Contract (Required)
Extract these fields before ranking:
- target product type
- stack and frameworks (or enough constraints to select them)
- priority outcomes (e.g., speed, security, UX, CI/CD maturity)
- team level (solo/small team/enterprise-like)
- existing skill list (optional but preferred)
If enough context is present, continue to search.
If context is insufficient, ask clarifying questions before recommending.
Clarifying Questions (If Needed)
Ask up to 5 short questions, only for missing critical inputs.
Prioritize in this order:
- what exactly to build
- required stack/constraints (or whether stack selection is needed first)
- expected production level
- must-have areas (security/testing/release/etc.)
- current skills to replace (if any)
Do not ask questions when the request is already sufficiently specific.
Stack Selection (Required Before Search)
If the user did not provide a finalized stack, you must select one first.
Rules:
- infer the best-fit implementation stack from the product description, goals, constraints, and team size
- prefer practical production-ready defaults over exotic combinations
- state the chosen stack explicitly before skill search
- only after stack selection, run capability discovery and search queries for that chosen stack
- do not ask the user to choose stack unless there is a hard technical constraint conflict
Do not skip stack selection when stack is missing or vague.
Capability Discovery (Dynamic)
Build groups from the user intent, not from a fixed preset.
Method:
- extract nouns (tools/platforms/domains)
- extract verbs (build/test/deploy/secure/monitor/optimize)
- merge overlaps into implementation-oriented groups
- add cross-cutting groups only when needed
Use references/goal-query-map.md only as a seed source.
Never force platform- or stack-specific groups unless they are requested or clearly implied.
Search Strategy
Preferred sources:
- SkillsMP website UI in MCP Playwright browser
- Public SkillsMP docs pages only for orientation, not API querying
Run 2-6 focused queries per discovered group in the site search UI.
Execution method (required):
- open SkillsMP site with MCP Playwright browser
- navigate to the skills/catalog search interface
- if authentication is required, complete it via browser login/session flow
- type each query manually in the web search input and submit
- collect candidate skills from rendered UI results
- do not request or use API tokens for this workflow
- do not call API endpoints directly from terminal or HTTP client
- after collecting results, close the Playwright browser session before returning recommendations
Hard restriction:
- never use
curl,fetch, or direct calls to SkillsMP API endpoints such as/api/v1/skills/searchor/api/v1/skills/ai-search(token-protected)
Search quality rules:
- keep queries short and concrete
- avoid broad mega-queries
- collect at least top 5 candidates per group
- deduplicate by
idandgithubUrl
Filtering and Ranking
Reject candidates when:
- they are repo-internal maintenance only
- they are stack-incompatible
- they are mirrors of a better canonical source
- description is vague and non-actionable
Use relevance tiers:
- Tier A: direct fit for high-priority groups
- Tier B: useful adjacent support
- Tier C: generic fallback
Rank with this priority:
- relevance tier
- practical stack fit
- stars/forks as quality signal
- recency signal if available
Never let stars override relevance.
Decision Rules
For each current skill slot:
- Replace: clearly better relevance and quality
- Keep: already strong or no meaningful upgrade
- Add: missing capability not covered today
When no strong upgrade exists, explicitly keep.
Output Format (Required Order)
Return sections in this exact order:
Discovered Capability GroupsTop Install/Replace ListReplace MatrixKeep As-IsCoverage CheckSource Notes
Each recommended skill must include:
- name
- source repo/author
- stars
- fit rationale
- priority (
P0/P1/P2) - source note from web UI search context
Quality Bar
- Prefer canonical upstream sources.
- Prefer workflow-driven skills over vague guidance.
- Prefer reusable cross-project skills over one-repo internals.
- Mark uncertain recommendations explicitly.
- If context is still insufficient after clarification, say so.
Reference
- Seed query map (non-exhaustive):
references/goal-query-map.md
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