Borrowing it
Nothing to install: this file belongs to MetamusicX/zissa-wiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MetamusicX/zissa-wiki/main/.claude/skills/query/SKILL.mdgit clone --depth 1 https://github.com/MetamusicX/zissa-wikiWrote 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/metamusicx/zissa-wiki/query)<a href="https://agentmods.dev/skills/metamusicx/zissa-wiki/query"><img src="https://agentmods.dev/badge/skills/metamusicx/zissa-wiki/query/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.
<a href="https://agentmods.dev/skills/metamusicx/zissa-wiki/query"><img src="https://agentmods.dev/badge/skills/metamusicx/zissa-wiki/query.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00036 | $0.00103 |
| Opus 5.5 | $0.00014 | $0.00041 |
| Sonnet 5.5 | $0.00007 | $0.00021 |
| Haiku 4.5 | $0.00004 | $0.00010 |
Grade A, and why
query 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 1mo 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.
What it actually says
Answer this question by following Workflow 2: QUERY in AGENTS.md:
$ARGUMENTS
To show how the pages you used connect, python3 scripts/wiki.py graph --around <page> prints a Mermaid diagram you can include.
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.
- 1mo ago First seen · 12 lines · 36 tokens per session scan A dc3c5054e351
query is a skill published in the GitHub repository MetamusicX/zissa-wiki (61 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 103 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-27.
Other skills, from other repositories
llm-wiki
Build and maintain a persistent, interlinked Obsidian-compatible markdown wiki using Karpathy's LLM Wiki pattern. Extension-backed with auto-generated metadata, guardrails, and 14 custom tools (+3 opt-in agent-trajectory tools).
mindbase
Maintain a persistent AI-tended research wiki. Activates when the user wants to ingest a source (PDF, URL, article, paste), capture a thought, build the wiki context, query what's already known, lint for orphans/contradictions, or maintain page conventions. Phrases include "add this to my wiki", "today I decided…"…
llm-wiki-pm
Persistent PM knowledge base, competitive intel, customer notes, strategy, roadmap, AI market. Markdown wiki with entities, concepts, comparisons. Ingest sources, query, update with diffs, lint. Fires on "remember that / note that / don't forget / what do we know about X / what am I missing / blind spots".
llm-wiki-brief
Structured daily/weekly briefs, tag digests, and check-ins from the PM wiki. Richer output than core catch-me-up.
llm-wiki-research
Research sprints, competitive deep dives, and auto-enrichment of stub wiki pages. Captures sources to raw/ with the core ingest step. Files all findings back into the wiki.
set-wiki-path
Change the active wiki directory for llm-wiki-pm.