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 skills add jeremylongshore/bobs-big-brain-plugin --skill braingit clone --depth 1 https://github.com/jeremylongshore/bobs-big-brain-pluginWrote 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/jeremylongshore/bobs-big-brain-plugin/brain)<a href="https://agentmods.dev/skills/jeremylongshore/bobs-big-brain-plugin/brain"><img src="https://agentmods.dev/badge/skills/jeremylongshore/bobs-big-brain-plugin/brain/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/jeremylongshore/bobs-big-brain-plugin/brain"><img src="https://agentmods.dev/badge/skills/jeremylongshore/bobs-big-brain-plugin/brain.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 | $0.00066 | $0.02030 |
| Opus 5.5 | $0.00026 | $0.00812 |
| Sonnet 5.5 | $0.00013 | $0.00406 |
| Haiku 4.5 | $0.00007 | $0.00203 |
Grade A, and why
brain 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.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brain — cited answers from your governed knowledge base
Ask your knowledge brain a question and get an answer grounded in your governed corpus, where every claim carries a qmd:// citation. The brain does not paraphrase from memory — it retrieves governed memories and cites them, so any answer is verifiable after the fact.
Overview
This is the read surface of Bob's Big Brain: your files are compiled into
governed memories, governed by deterministic code, and retrieved with citations
through qmd BM25, native FTS5 and configured dense retrieval. The brain_search MCP tool fronts that retrieval. Your product
surround is INTKB govern + ICO compile + this plugin — not a fork of qmd.
The job here is to turn a natural-language question into a cited answer — and to refuse to answer beyond what the citations support.
Prerequisites
- The bobs-big-brain / governed-brain plugin is installed (MCP
governed-brain). - Mode is automatic. In local mode (default) search runs in-process
against your local
~/.teamkbindex — no remote brain service or API key; a compatible qmd binary must be available (prefer monorepo pin@tobilu/qmdvia the Registrar / installer). Operators can usescripts/bbb-qmdfrom bobs-big-brain-registrar so XDG points at the team index, not personal~/.cache/qmd. In team mode (TEAMKB_API_URLset) search proxies to the team brain. Every hit is aqmd://citation. - See the runtime contract for exact inputs, result shapes, authentication, and mode-specific failures.
Instructions
Step 1: Search the governed corpus
The source entrypoints at the Registrar revision in gsb.lock.json configure
Tobi's qmd BM25, native FTS5 and a
sqlite-vec dense arm, joined with reciprocal-rank fusion and a freshness/category rerank.
Dense is enabled by default in those entrypoints, but requires a built index and
the configured loopback query embedder; disabling it or an unavailable arm leaves
the lexical results. Team mode uses the deployed server's configuration.
Retrieval makes no query-time generative LLM call.
What ships with it
1 file 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.
- 2d ago Changed 9a618e9030f2
- 6d ago Changed · +9 lines 890a9f45131c
- 1mo ago Changed · +1 lines · -58 tokens per session 126ea9468b82
- 1mo ago First seen · 154 lines · 124 tokens per session scan A 28d409976271
brain is a skill published in the GitHub repository jeremylongshore/bobs-big-brain-plugin (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 66 tokens to every session and 2,030 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
mind-mem
User manual for the mind-mem persistent memory CLI (mm). Use when an agent needs to recall prior decisions, tasks or project facts from a mind-mem workspace, pack memory into context, check workspace health, review governed proposals, install or troubleshoot mind-mem, or answer questions about how mind-mem works …
memory-recall
Search across all structured memory files. Default backend: BM25 scoring with Porter stemming and domain-aware query expansion. Optional: graph-based cross-reference boosting (--graph). Optional: vector/embedding backend (configure in mind-mem.json). Returns ranked results with block ID, type, score, excerpt, and file…
apply-proposal
Review and apply intelligence proposals generated by /scan. Uses atomic operations with rollback safety.
integrity-scan
Run the intelligence scanner to detect contradictions, drift, dead decisions, and missing cross-references across the entire memory workspace.
liquefy-archive
Background compression and vault archival for OpenClaw workspaces — auto-packs sessions, memory, and artifacts into verified .null vaults with full MRTV proofs. Blocks credential and key leaks before archiving.
liquefy-openclaw
Use this skill when working with Liquefy around OpenClaw, including plugin scan/apply flows, native hook integration, session vaulting, search/restore, policy explanation, guarded runs, context gate, replay blocking, and state/history guard workflows.