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.
npx agentmods add skills/w-winter/dot314/text-searchnpx skills add w-winter/dot314 --skill text-searchgit clone --depth 1 https://github.com/w-winter/dot314Wrote 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.
[](https://agentmods.dev/skills/w-winter/dot314/text-search)<a href="https://agentmods.dev/skills/w-winter/dot314/text-search"><img src="https://agentmods.dev/badge/skills/w-winter/dot314/text-search.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00022 | $0.03059 |
| Opus 5 | $0.00011 | $0.01529 |
| Sonnet 5 | $0.00004 | $0.00612 |
| Haiku 4.5 | $0.00002 | $0.00306 |
Grade A, and why
text-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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
text-search
Use qmd to search indexed text corpora such as session logs, notes, docs, and logs. For indexed content, use qmd for discovery instead of raw grep.
First checks
Before searching, confirm what is indexed:
qmd status
qmd collection list
qmd context list
Do not assume collection names, paths, or contexts.
Core rule
For indexed corpora, use qmd for discovery.
Do not use grep/find/jq/cat directly on indexed files to search for meaning. This is especially important for session JSONL, which is noisy and hard to interpret raw.
Shell usage is still fine for:
- filtering tool output after discovery
- housekeeping and file targeting
- non-indexed content
- helper scripts in this skill
Choose the right qmd command
For exact clues, start with qmd search.
- Use
qmd searchfor exact clues: tool names, error strings, repo names, JSON fields, literal phrases - Use
qmd querywhen lexical search is weak, the request is conceptual, or you want hybrid retrieval + reranking - Use
qmd vsearchonly when you specifically want pure semantic similarity
qmd search '"toolName":"rp_exec"'
qmd search 'apply_edits'
qmd query "OAuth redirect flow"
qmd vsearch "the session where we changed direction"
Operational notes:
qmd querymay trigger local model startup or model downloads, so it is not always the fastest first step- For session discovery, prefer
--filesfirst so you get compact path output instead of long snippets
Build better queries
Use --intent when the request is ambiguous
intent is a steering hint. Use it when the same words could refer to multiple things or when the user remembers the topic better than the exact wording.
qmd query --intent "Pi/Codex/Claude agent sessions about repo editing failures" \
-c sessions \
"apply_edits error"
Use structured query documents for important searches
Multi-line query documents are useful when you have both exact clues and fuzzy memory.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- scripts/analyze-sessions.sh 11 KB runs code
- scripts/claude-session-extract-with-tools.py 14 KB runs code
- scripts/codex-session-extract-with-tools.py 16 KB runs code
- scripts/pi-session-extract-with-tools.py 10 KB runs code
- scripts/rebuild-qmd-sessions-rendered.sh 7.7 KB runs code
- scripts/repoprompt-agent-session-extract.py 13 KB runs code
- scripts/session-view 9.7 KB
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.
- 5d ago First seen · 378 lines · 22 tokens per session scan A 18c1502440dd
text-search is a skill published in the GitHub repository w-winter/dot314 (125 stars, last pushed 10d ago), licensed MIT. It adds 22 tokens to every session and 3,059 once invoked, about $0.0001 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 2026-08-30.
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Load to render, check or adopt a repo's GitHub review-bot instruction files from the shared doctrine plus its bot-instructions.toml, or to read the doctrine, the TOML schema, the render rules and the validators.
harness-ci
Load to wire, tune, or debug a repo's harness-only skip.
my-skill
When to load this skill. Agents read this line to decide whether to load it, so be specific.
orch
PRIMARY AGENT ONLY. Load to orchestrate a Linear or GitHub work item from preparation through merge.