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Tobi qmd qmd 1.0.2

Skill VRIL-LABS/skill-jam/skills/document-processing/tobi-qmd-qmd-1.0.2

Search markdown knowledge bases, notes, and documentation using QMD. Use when users ask to search notes, find documents, or look up information.From its SKILL.md

Install
npx -y skills add VRIL-LABS/skill-jam --skill tobi-qmd-qmd-1.0.2

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

3.4 KB, 869 tokens by cl100k_base, as published. Nobody here has run it

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

{
  "searches": [
    { "type": "lex", "query": "CAP theorem consistency" },
    { "type": "vec", "query": "tradeoff between consistency and availability" }
  ],
  "collections": ["docs"],
  "limit": 10
}

Query Types

TypeMethodInput
lexBM25Keywords — exact terms, names, code
vecVectorQuestion — natural language
hydeVectorAnswer — 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

Combining Types

GoalApproach
Know exact termslex only
Don't know vocabularyUse a single-line query (implicit expand:) or vec
Best recalllex + vec
Complex topiclex + vec + hyde

First query gets 2x weight in fusion — put your best guess first.

Lex Query Syntax

SyntaxMeaningExample
termPrefix matchperf matches "performance"
"phrase"Exact phrase"rate limiter"
-termExcludeperformance -sports

Note: -term only works in lex queries, not vec/hyde.

Collection Filtering

{ "collections": ["docs"] }              // Single
{ "collections": ["docs", "notes"] }     // Multiple (OR)

Omit to search all collections.

Other MCP Tools

ToolUse
getRetrieve doc by path or #docid
multi_getRetrieve multiple by glob/list
statusCollections and health

CLI

qmd query "question"              # Auto-expand + rerank
qmd query $'lex: X\nvec: Y'       # Structured
qmd query $'expand: question'     # Explicit expand
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

curl -X POST http://localhost:8181/query \
  -H "Content-Type: application/json" \
  -d '{"searches": [{"type": "lex", "query": "test"}]}'

Setup

npm install -g @tobilu/qmd
qmd collection add ~/notes --name notes
qmd embed

What ships with it: 1 file

1.9 KB alongside SKILL.md

references/

Keep looking

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