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/hraness/wrench/query-kbnpx skills add hraness/wrench --skill query-kbgit clone --depth 1 https://github.com/hraness/wrenchWrote 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/hraness/wrench/query-kb)<a href="https://agentmods.dev/skills/hraness/wrench/query-kb"><img src="https://agentmods.dev/badge/skills/hraness/wrench/query-kb.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 | $0.00083 | $0.02472 |
| Opus 5 | $0.00042 | $0.01236 |
| Sonnet 5 | $0.00017 | $0.00494 |
| Haiku 4.5 | $0.00008 | $0.00247 |
Grade A, and why
query-kb 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 3d 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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Query the knowledge base
Use the cheapest precise view first, then broaden. Markdown files remain the authority; search scores, metadata rows, and graph results are derived views.
Locate the vault
- Resolve
<vault>to the directory containing its managed or authoredindex.md, then set the shell-localKB_ROOTto that path (KB_ROOT=kbfrom a typical repository root, orKB_ROOT=.from inside the vault). - Resolve
<repository>to the repository root when the question concerns a repository path (KB_REPO=.from that root). - Read the vault's applicable agent instructions and note conventions.
- Pass the resolved path to every
--root; do not scan a repository root merely because that is where the agent session started.
Choose the retrieval lane
- Repository file or directory: run
kb contextfirst. Read its inherited guides root to nearest, then inspect its maintained knowledge, active plans, dated research, reports, and separate historical-plan group. Open only useful context hubs or records. - Known frontmatter field or tag such as type, status, or area: use
kb list. - Known note title, path, or alias: use
kb linksorkb backlinks, which resolve note identities before returning authored relationships. - A whole-vault structural question or relationship audit: use
kb graph --json, then inspect the smallest relevant portion of its canonical output. - A phrase, identity, or concept expressed with different vocabulary: use
kb search, whose default hybrid result preserves exact and QMD evidence separately. - Direct provenance for one note or repository path: use
kb historyorkb history searchwithout changing authored metadata or links. - Recent captures awaiting maintained disposition: use the advisory
kb inboxview. - Broad orientation: read
index.md, then follow the smallest useful link trail. Usekb catalogwhen an exhaustive disposable inventory is actually needed.
kb context src/parser.ts --root "$KB_ROOT" --repo "$KB_REPO"
kb list --root "$KB_ROOT" --scope src/parser --where type=plan --json
kb list --root "$KB_ROOT" --where type=plan --where status=in-progress --sort area --json
kb list --root "$KB_ROOT" --tag retrieval --sort title --json
kb backlinks "Plan title or path" --root "$KB_ROOT" --json
kb links "Plan title or path" --root "$KB_ROOT" --direction both --depth 1 --limit 25 --json
kb relation list "Plan title or path" --root "$KB_ROOT" --json
kb graph --root "$KB_ROOT" --json
kb search "why browser capture uses the current tab" --root "$KB_ROOT" --json
kb search "accepted ingestion plans" --root "$KB_ROOT" --where type=plan --where status=accepted --tag ingestion --json
kb search "notes/write-path" --root "$KB_ROOT" --mode exact --no-history --json
kb history "notes/write-path" --root "$KB_ROOT" --repo "$KB_REPO" --json
kb history search src/parser.ts --root "$KB_ROOT" --repo "$KB_REPO" --json
kb inbox --root "$KB_ROOT" --limit 25 --json
What ships with it
2 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.
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.
- 3d ago First seen · 206 lines · 83 tokens per session scan A 982eea60ef02
query-kb is a skill published in the GitHub repository hraness/wrench (4 stars, last pushed 3d ago), licensed MIT. It adds 83 tokens to every session and 2,472 once invoked, about $0.0004 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.
Other skills, from other repositories
knowledge-base
Build and maintain a company knowledge base as a wiki of interlinked markdown notes in the workspace — a private, compounding Wikipedia. Use when the user wants to start or organize a knowledge base / wiki, ingest sources (URLs, documents, pasted notes) into it, ask questions answered from it, or audit (lint) it.…
gno
Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs…
kb
Operate a hraness/kb local-first Markdown knowledge base for coding-agent memory. Use when a user asks to search or query a KB or Obsidian vault; load repository context, plans, decisions, concepts, backlinks, semantic search, or Git provenance; save, clip, scrape, or archive a URL, article, social thread, signed-in…
context-canvas-memory
Use for compaction, coordination, or two complexity cues.
stats
Show Captain Memo's corpus statistics (chunks per channel, observation counts, indexing progress, embedder info). Use when the user types /captain-memo:stats.
search
Hybrid search across Captain Memo's local memory + skills + observations. Use when the user types /captain-memo:search to retrieve top hits without the model having to decide whether to call searchall on its own.