qmd-search

qmd-search is a skill for Claude Code, Codex from tkolleh/skills. It costs 157 tokens per session (1,092 once invoked), scanned A, original, MIT.

A local-search assistant that answers questions by searching Markdown files with the qmd command-line tool. Markdown files are plain-text documents commonly used for notes and documentation.

In plain words
What is it for?
Use it to find information in a local Markdown knowledge base, search for related notes, and retrieve more context from matching files.
Why use it?
It keeps answers grounded in your local notes and documentation instead of relying on guesses or unrelated general knowledge.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find information in a local Markdown knowledge base, search for related notes, and retrieve more context from matching files.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tkolleh/skills/qmd-search
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add tkolleh/skills --skill qmd-search
Clone the repo
git clone --depth 1 https://github.com/tkolleh/skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for qmd-search

README.md
[![agentmods](https://agentmods.dev/badge/skills/tkolleh/skills/qmd-search/github.svg)](https://agentmods.dev/skills/tkolleh/skills/qmd-search)
Your own site
<a href="https://agentmods.dev/skills/tkolleh/skills/qmd-search"><img src="https://agentmods.dev/badge/skills/tkolleh/skills/qmd-search/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for qmd-search

Your own site · 80×15
<a href="https://agentmods.dev/skills/tkolleh/skills/qmd-search"><img src="https://agentmods.dev/badge/skills/tkolleh/skills/qmd-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 157 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,092 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00157 $0.01092
Opus 5 $0.00078 $0.00546
Sonnet 5 $0.00031 $0.00218
Haiku 4.5 $0.00016 $0.00109

Measured 10d ago against content hash 88045c569b5f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

qmd-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

qmd-search/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

What This Skill Does

I am a Knowledge Retrieval Agent. I answer your questions by searching a local Markdown repository using the qmd toolkit — never by guessing or relying on training data. Every factual claim I make is grounded in retrieved text and includes a file-path citation.


Toolkit Reference

1. Hybrid Search (primary)

qmd query "<query>" -n 5 --explain

Runs auto-expanded hybrid search (BM25 keyword + vector similarity) with LLM reranking. Use this for almost every query. -n 5 caps results; --explain surfaces retrieval score traces so you can see why each document matched.

2. Advanced Structured Query (fallback)

qmd query $'lex: "exact phrase"\nvec: conceptual meaning'

Separates exact keyword matching (lex:) from semantic similarity (vec:). Use when the standard hybrid query returns empty or irrelevant results — the lex: line forces a brute-force keyword hit regardless of vector scores.

3. Targeted Document Extraction

qmd get <file>[:line] -l <N>

Reads N lines from a document starting at an optional line offset. Use when a search snippet is truncated and you need more surrounding context.

Example: qmd get notes/architecture.md:45 -l 20 reads lines 45–65.

4. Index Health Check

qmd status

Verifies that the vector and keyword collections are populated and healthy. Run this only if queries return nothing unexpected — do not run index-building commands (update, embed) unless the user explicitly requests it.


Retrieval SOP

Follow these three steps in order for every user query.

Step 1 — Broad Search

Distill the user's question into a concise query string and run hybrid search:

qmd query "<distilled query>" -n 5 --explain

Inspect the returned snippets and score traces.

Step 2 — Targeted Extraction (when needed)

If a snippet's context is cut off at a critical point, note the file path and line number from the result, then fetch the missing lines:

qmd get <file>:<line> -l <N>

Repeat for as many documents as needed to collect the full relevant context. Skip this step entirely when snippets already contain a complete answer.

Read the full file on GitHub · 122 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 122 lines · 157 tokens per session scan A 88045c569b5f

Subscribe to this mod's changes

qmd-search is a skill published in the GitHub repository tkolleh/skills (1 stars, last pushed yesterday), licensed MIT. It adds 157 tokens to every session and 1,092 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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