SkillSearch
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SkillSearchfind a skill to improve my writing"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SkillSeek
Find and surface the right Claude Code skill — automatically. Indexes every skill across all your installed plugins, searched instantly at every prompt.
(demo GIF coming soon)
The problem
Claude Code ships with 1700+ skills — but your agent sees only a fraction of them.
Two limits cut most skills out of view:
skillListingBudgetFractioncaps the skill listing at roughly 1% of the context window. On a 200k-token model that is ~2000 tokens — enough for maybe 60–80 skills, not 1700+.Description truncation: least-recently-used skills get their descriptions dropped entirely. The agent sees the name but not what the skill does.
Result: skills like impeccable, stop-slop, deep-research, and hundreds of plugin-bundled skills are invisible to the agent unless it happens to know the exact name.
SkillSeek fixes this by building a complete local index and routing skill lookups through BM25 search — so the agent finds impeccable when it needs copy polish, not just when someone types /impeccable.
Related MCP server: skillsmp-mcp-server
What SkillSeek does
One index. Three surfaces.
~/.claude/skills/
~/.agents/skills/ ──► buildIndex() ──► SKILLS-INDEX.json
installed_plugins.json / │
plugin caches │
┌────────────┴────────────┐
│ │
MCP tool CLI
skill_search skillseek search
(agent calls it) (you call it)
│
hooks (auto)
SessionStart + UserPromptSubmit
inject top matches into contextIndex — scans
~/.claude/skills,~/.agents/skills, and plugin caches discovered viainstalled_plugins.json. Deduplicates, namespaces plugin skills, parses YAML frontmatter.BM25 search — MiniSearch with name-boosted scoring. Finds
impeccablefor "polish prose",stop-slopfor "remove filler",deep-researchfor "thorough web research".MCP tool —
skill_search(query, top_k?)— the agent calls this when it needs to find a skill. Returns a text list of matching skills with name, description, and source.CLI —
skillseek search "<task>"for humans.skillseek index [--if-changed]to refresh.Hooks —
SessionStartprints a rotating generic nudge to use skill_search and fire-and-forget refreshes the index if stale;UserPromptSubmitruns BM25 on the actual prompt and injects up to 3 matching skill pointers into the system prompt (no injection when no match clears the pollution-guard threshold).
Install
On npm as
skillseek. The index is built locally from your installed skills on first run; nothing is bundled, so your skill inventory never leaves your machine.
Option A — Claude Code plugin (recommended)
# Clone + install deps (needed so hooks and the MCP server have their Node deps at runtime)
git clone https://github.com/TheQmaks/skillseek
cd skillseek && npm install
# Register as a plugin marketplace, then install
/plugin marketplace add https://github.com/TheQmaks/skillseek
/plugin install skillseekThe plugin wires up the MCP skill_search server and both hooks via .mcp.json and hooks/hooks.json. The SessionStart hook builds the index on first run and refreshes it when it goes stale.
Option B — standalone CLI + MCP (any project)
git clone https://github.com/TheQmaks/skillseek
cd skillseek && npm install
node bin/cli.mjs index # build the index for your machine
claude mcp add skillseek node "$PWD/src/mcp-server.mjs" # expose skill_search to the agentUsage
# Search for a skill
skillseek search "product copy review"
# | skill | description |
# | --- | --- |
# | `impeccable` | Polish prose and remove filler words |
# | `stop-slop` | Ruthless filler-word removal |
# | `copy-editing` | Line-level editing for clarity |
# Rebuild the index (full)
skillseek index
# Rebuild only if skills have changed since last index
skillseek index --if-changed
# Ask "which skill should I use for X?"
skillseek which "thorough web research"MCP tool (called by the agent):
skill_search(query: string, top_k?: number) → text listing matching skills (name, description, source)Hooks — no configuration needed after install. Control injection verbosity:
| Behavior |
| No per-prompt injection |
| Inject only the single strongest match (very high threshold) |
| Inject up to 3 strong matches; nothing on weak/irrelevant prompts |
Injection is deliberately high-precision: the per-prompt hook stays silent unless a match
clears a conservative BM25 threshold (filler words are filtered out first), so it never pollutes
context on chatty or off-topic prompts. Borderline relevance is left to the skill_search tool.
Config
Env var | Default | Description |
|
| Hook injection level: |
| preset default | Override the BM25 score floor for injection (tune for your corpus size) |
|
| Override index file path |
How it works
Every prompt Agent tool call CLI / human
│ │ │
▼ ▼ ▼
UserPromptSubmit hook MCP skill_search skillseek search
│ │ │
└──────────────────────────────►│◄─────────────────────────┘
▼
loadIndex(SKILLS-INDEX.json)
│
BM25 search (MiniSearch)
name boost × 2, top-k results
│
┌───────┴───────────────┐
│ │
inject into return to caller
system prompt (tool / CLI output)
(seen-skill filter,
pollution guard)The index is built once and loaded from disk on each search call. On a warm file-system cache, search latency is under 10 ms for 1684 skills.
License
MIT
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