qmd

Included with Lifetime

$97 forever

Local hybrid search for markdown notes and docs. Use BEFORE reading files to save tokens - search first, read only what's relevant. Provides 90% token savings on exploration tasks.

Writing & Docs

What this skill does


# qmd - Quick Markdown Search

Local search engine for Markdown notes, docs, and knowledge bases. **Use this to find relevant files BEFORE reading them** to dramatically reduce token usage.

## When to Use (IMPORTANT)

**ALWAYS prefer qmd search over reading files directly when:**
- Exploring a codebase or documentation
- Looking for specific functionality or concepts
- Finding related files to a topic
- Answering questions about the codebase

**Token savings:** Instead of reading 5 files (5000+ tokens), search first (50 tokens) and read only the relevant sections (200 tokens).

## Search Priority (follow this order)

1. **`qmd search "query"`** - Fast BM25 keyword search. Use this first, it's instant.
2. **`qmd vsearch "query"`** - Semantic similarity. Use only if keyword search fails.
3. **`qmd query "query"`** - Hybrid + reranking. Avoid unless user explicitly requests highest quality.

## Common Commands

```bash
# Fast keyword search (DEFAULT - use this first)
qmd search "authentication" -n 10

# Search specific collection
qmd search "api routes" -c my-project

# Get file paths only (for deciding what to read)
qmd search "database schema" --files

# JSON output for parsing
qmd search "error handling" --json

# Semantic search (slower, use as fallback)
qmd vsearch "how does the login flow work"
```

## Retrieve Documents

```bash
# Get specific file
qmd get "path/to/file.md"

# Get by document ID from search results
qmd get "#docid"

# Get multiple files
qmd multi-get "docs/*.md" --json
```

## Workflow Example

**Bad (token expensive):**
```
1. Read src/auth/login.ts (800 tokens)
2. Read src/auth/session.ts (600 tokens)
3. Read src/auth/middleware.ts (500 tokens)
4. Read src/auth/types.ts (400 tokens)
→ Found answer in middleware.ts
Total: 2300 tokens
```

**Good (token efficient):**
```
1. qmd search "authentication middleware" --files (response: 50 tokens)
   → Returns: src/auth/middleware.ts:45-62
2. Read only the relevant section (150 tokens)
Total: 200 tokens (90% savings!)
```

## Tips for Claude

- **Search before reading**: Always try qmd search first
- **Use --files flag**: Get paths without content to decide what to read
- **Be specific**: More specific queries = better results
- **Check collections**: Use `qmd status` to see indexed collections
- **Combine with cartographer**: CODEBASE_MAP.md gives structure, qmd gives content

## Maintenance

```bash
qmd status          # Check index health and collections
qmd update          # Re-index changed files (fast)
qmd embed           # Update vector embeddings (slower)
```

Files: 1

Size: 2.7 KB

Complexity: 6/100

Category: Writing & Docs

Source: https://github.com/iagocavalcante/claude-turbo-search/tree/main/skills/qmd

Related in Writing & Docs

jax-development

Included

Use this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.

Writing & Docsscripts

nature-article-writer

Included

Drafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.

Writing & Docsscripts

deckrd

Included

Document-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.

Writing & Docsscripts

clinical-decision-support

Included

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

Writing & Docsscripts

handling-sf-data

Included

Salesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).

Writing & Docsscripts

accelint-ac-to-playwright

Included

Convert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.

Writing & Docsscripts