Qmd Search

What it does

When your agent uses it

• The user asks to search my vault/notes
• Find notes about X
• What do my notes say about Y
• Do I have anything on Z

Example prompts

• “search my vault/notes”
• “find notes about X”
• “what do my notes say about Y”
• “/qmd-search”

Requirements

• A Bash shell

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1Search semantically first (query / vsearch).
2. 2Generate likely native-script spellings/stems and try them, e.g.
3. 3Run a literal pass before concluding absence: qmd-search.sh -m grep -n 20 "Зигги".
4. 4Use literal hits to disambiguate close names (e.g. Зигги the pet vs. Зигмунд Freud).
5. 5If everything fails, say "I didn't find it with these queries: …" and list the terms tried —

What it can do on your machine

Read from SKILL.md and the folder at commit 3b88261. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 3 files in scripts/ (Shell), which the agent can run.

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • github.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Qmd Search loads about 1.5k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 115 tokens; SKILL.md has 583 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~115

When it runs · the whole SKILL.md, loaded when a task matches

~1.5k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from glebis/claude-skills at commit 3b88261, republished under its MIT licence (© glebis). 583 words, ~1,516 tokens.

name

qmd-search

description

This skill should be used to search the local Obsidian vault / markdown knowledge base by meaning, not just keywords, using the on-device qmd engine (BM25 + vector + LLM rerank). Trigger when the user asks to "search my vault/notes", "find notes about X", "what do my notes say about Y", "do I have anything on Z", "semantic search my knowledge base", or wants concept/cross-lingual retrieval over markdown. Fully local — nothing leaves the machine.

~/.claude/skills/qmd-search/scripts/qmd-search.sh [-m query|search|vsearch|grep|find] [-n N] [-c COLLECTION] [--snippet] [--min-score X] [--json] [--full] <query...>

qmd-search.sh "what helps with anxiety"                 # hybrid (default)
qmd-search.sh -m vsearch -n 8 "behavioral health from photos"
qmd-search.sh -m search sensorium                       # BM25 keyword
qmd-search.sh -m grep -n 20 "Зигги"                     # literal native-spelling / absence check
qmd-search.sh -m find "Зигги собака"                    # fused: semantic + literal in one call
qmd-search.sh --snippet "agent orchestration"           # rows + matching snippets
qmd-search.sh --min-score 0.5 "quarterly planning"      # drop low-relevance hits
qmd-search.sh --json "agent orchestration"              # structured output for further processing

qmd collection add ~/Brains/brain --name brain        # index the vault
qmd context add qmd://brain "short description of the vault"
qmd embed                                              # build vectors; re-run until status shows 0 pending
qmd cleanup                                            # compact the index

{ "mcpServers": { "qmd": { "command": "qmd", "args": ["mcp"] } } }

© glebis, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in qmd-search of glebis/claude-skills.

• SKILL.md
• evals/BASELINE.md
• evals/fixture.example.json
• references/cli-reference.md
• scripts/qmd-search.sh
• scripts/run-evals.sh
• scripts/test_qmd_search.sh

Open the folder on GitHubat commit 3b88261