query

A question-and-answer workflow for a compiled personal wiki, with answers based on its stored pages rather than memory and accompanied by citations.

In plain words
What is it for?
Use it for questions, briefings, and comparisons covered by the vault, and to identify missing or conflicting knowledge.
Why use it?
It avoids repeatedly searching the whole knowledge vault and preserves each answer so later work can build on it. A wiki is a collection of linked pages for organized notes.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/superhero-tech/super-brain/query
Any agent
npx skills add superhero-tech/super-brain --skill query
Clone the repo
git clone --depth 1 https://github.com/superhero-tech/super-brain

Made for: Claude Code, Codex.

Per session 56 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 897 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00056 $0.00897
Opus 5 $0.00028 $0.00449
Sonnet 5 $0.00011 $0.00179
Haiku 4.5 $0.00006 $0.00090

Measured 2d ago against content hash 0aaa25d1d6d1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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.

.agents/skills/query/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Query

Answer from the wiki, not from memory, and keep the answer so the next question starts further along.

Write the answer and every file you produce in the language the human is using.

How to invoke

  • Any question the vault plausibly covers
  • "What do we know about X?"
  • "Compare X and Y from what I have"
  • "Write me a briefing on X"
  • /query

How it works

1. Find the pages

Read 4-Knowledge/index.md first. It is the map, and it exists so you do not have to read every page to find three.

Pick the pages that bear on the question, entity pages included when the question names a person, company or tool.

If the index promises a page that is not on disk, or you find a page the index never lists, tell the human. Both are real findings.

2. Read them

Read the pages you picked, in full. Follow [[links]] one hop out when the question sits between two topics.

3. Answer

Cite every claim with [source: page-name.md], naming the wiki page you actually read.

Where the wiki disagrees with itself, show both sides and name the sources. A > CONTRADICTION: marker is a finding to surface, not noise to smooth over.

Where the wiki is thin, say so in the answer. If you add something from outside the vault, mark it plainly as outside knowledge so the human can tell the two apart.

4. Save the output

Write 9-Outputs/[YYYY-MM-DD]-[short-slug].md:

---
question: [the question, as asked]
date: [YYYY-MM-DD]
pages: [wiki pages used]
filed_back: [page name, or: no]
---

# [Question as a title]

[The answer, with [source: page-name.md] citations]

## What this is built on
- [[Page A]] - what it contributed
- [[Page B]] - what it contributed

## Gaps
[What the wiki could not answer. The most useful section in the file: it tells
the human what to read next.]

A one-line lookup does not need a file. Say out loud that you skipped it, so the human knows this answer was not kept.

When the answer has a shape that prose flattens - a comparison across dimensions, a timeline, a distribution - offer the better format and save it beside the markdown under the same slug. The format rules are in 8-System/brain.md under Conventions.

Read the full file on GitHub · 94 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. 2d ago First seen · 94 lines · 56 tokens per session scan A 0aaa25d1d6d1

Subscribe to this mod's changes

query is a skill published in the GitHub repository superhero-tech/super-brain (106 stars, last pushed 7d ago), licensed MIT. It adds 56 tokens to every session and 897 once invoked, about $0.0003 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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