Skill: satvik374/qmd-2 (version 0.1.0)

--- name: qmd description: Search markdown knowledge bases, notes, and documentation using QMD. Use when users ask to search notes, find documents, or look up information. license: MIT compatibility: Requires qmd CLI or MCP server. Install via `npm install -g @tobilu/qmd`. metadata: author: tobi version: "2.0.0" allowed-tools: Bash(qmd:*), mcp__qmd__* --- # QMD - Quick Markdown Search Local search engine for markdown content. ## Status !`qmd status 2>/dev/null || echo "Not installed: npm install -g @tobilu/qmd"` ## MCP: `query` ```json { "searches": [ { "type": "lex", "query": "CAP theorem consistency" }, { "type": "vec", "query": "tradeoff between consistency and availability" } ], "collections": ["docs"], "limit": 10 } ``` ### Query Types | Type | Method | Input | |------|--------|-------| | `lex` | BM25 | Keywords — exact terms, names, code | | `vec` | Vector | Question — natural language | | `hyde` | Vector | Answer — hypothetical result (50-100 words) | ### Writing Good Queries **lex (keyword)** - 2-5 terms, no filler words - Exact phrase: `"connection pool"` (quoted) - Exclude terms: `performance -sports` (minus prefix) - Code identifiers work: `handleError async` **vec (semantic)** - Full natural language question - Be specific: `"how does the rate limiter handle burst traffic"` - Include context: `"in the payment service, how are refunds processed"` **hyde (hypothetical document)** - Write 50-100 words of what the *answer* looks like - Use the vocabulary you expect in the result **expand (auto-expand)** - Use a single-line query (implicit) or `expand: question` on its own line - Lets the local LLM generate lex/vec/hyde variations - Do not mix `expand:` with other typed lines — it's either a standalone expand query or a full query document ### Intent (Disambiguation) When a query term is ambiguous, add `intent` to steer results: ```json { "searches": [ { "type": "lex", "query": "performance" } ], "intent": "web page load times and Core Web Vitals" } ``` Intent affects expansion, reranking, chunk selection, and snippet extraction. It does not search on its own — it's a steering signal that disambiguates queries like "performance" (web-perf vs team health vs fitness). ### Combining Types | Goal | Approach | |------|----------| | Know exact terms | `lex` only | | Don't know vocabulary | Use a single-line query (implicit `expand:`) or `vec` | | Best recall | `lex` + `vec` | | Complex topic | `lex` + `vec` + `hyde` | | Ambiguous query | Add `intent` to any combination above | First query gets 2x weight in fusion — put your best guess first. ### Lex Query Syntax | Syntax | Meaning | Example | |--------|---------|---------| | `term` | Prefix match | `perf` matches "performance" | | `"phrase"` | Exact phrase | `"rate limiter"` | | `-term` | Exclude | `performance -sports` | Note: `-term` only works in lex queries, not vec/hyde. ### Collection Filtering ```json { "collections": ["docs"] } // Single { "collections": ["docs", "notes"] } // Multiple (OR) ``` Omit to search all collections. ## Other MCP Tools | Tool | Use | |------|-----| | `get` | Retrieve doc by path or `#docid` | | `multi_get` | Retrieve multiple by glob/list | | `status` | Collections and health | ## CLI ```bash qmd query "question" # Auto-expand + rerank qmd query $'lex: X\nvec: Y' # Structured qmd query $'expand: question' # Explicit expand qmd query --json --explain "q" # Show score traces (RRF + rerank blend) qmd search "keywords" # BM25 only (no LLM) qmd get "#abc123" # By docid qmd multi-get "journals/2026-*.md" -l 40 # Batch pull snippets by glob qmd multi-get notes/foo.md,notes/bar.md # Comma-separated list, preserves order ``` ## HTTP API ```bash curl -X POST http://localhost:8181/query \ -H "Content-Type: application/json" \ -d '{"searches": [{"type": "lex", "query": "test"}]}' ``` ## Setup ```bash npm install -g @tobilu/qmd qmd collection add ~/notes --name notes qmd embed ```


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