Borrowing it
Nothing to install: this file belongs to Lanzelot1/claw-brain. 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/Lanzelot1/claw-brain/main/.claude/commands/status.mdgit clone --depth 1 https://github.com/Lanzelot1/claw-brainWrote 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/commands/lanzelot1/claw-brain/status)<a href="https://agentmods.dev/commands/lanzelot1/claw-brain/status"><img src="https://agentmods.dev/badge/commands/lanzelot1/claw-brain/status/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/commands/lanzelot1/claw-brain/status"><img src="https://agentmods.dev/badge/commands/lanzelot1/claw-brain/status.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 | $0.00007 | $0.00602 |
| Opus 5.5 | $0.00003 | $0.00241 |
| Sonnet 5.5 | $0.00001 | $0.00120 |
| Haiku 4.5 | $0.00001 | $0.00060 |
Grade A, and why
status 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 2mo 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Give the user a quick overview of the brain's current state.
Steps
- Read
memory/_index.mdand count:- Number of knowledge areas
- Number of indexed files per area
- Any entries under "Recently Added"
- Check
drop/for unprocessed files - List the 5 most recent files in
output/ - Present a clean, concise summary
Health Score
Calculate a health score (0-100) from these metrics. Skip this section entirely if there are no .md files in knowledge/.
| Metric | Weight | How |
|---|---|---|
| Freshness | 25% | % of knowledge .md files with git commit <30 days |
| Source coverage | 25% | % with source: in YAML frontmatter |
| Index coverage | 20% | % referenced in memory/_index.md |
| Cross-references | 15% | % with ≥1 markdown link to another knowledge file |
| Inbox clear | 15% | 100 if drop/ is empty, 0 otherwise |
Display as: Brain Health: X/100 with a breakdown table showing each metric's score.
Health Checks
After the score, run detailed health checks:
| Check | How |
|---|---|
| Freshness | Run git log -1 --format="%ai" per knowledge .md file. Label: fresh (<30 days), aging (30-90 days), stale (>90 days) |
| Missing sources | Check each .md file in knowledge/ for source: in YAML frontmatter. List any files missing it. |
| Orphaned files | Find .md files in knowledge/ that are not referenced in memory/_index.md |
| Index coverage | Compare file count in knowledge/ vs entries in _index.md |
| Cross-references | Find knowledge files with no markdown links to other knowledge files |
Present health results as a compact table or list. Only highlight problems — don't list every file if everything is healthy.
Wiki Health
Only display this section if any type: wiki files exist in knowledge/.
| Check | How |
|---|---|
| Wiki coverage | Count wiki pages vs source files. Report ratio (not a score — there's no "right" number). |
| Stale wiki pages | Wiki pages whose source files have been modified more recently than the wiki page's updated: date. |
| Unlinked sources | Source files that aren't referenced in any wiki page's ## Sources section. |
| Contradictions | Note any contradictions flagged in memory/log.md that haven't been resolved. |
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.
- 2mo ago First seen · 57 lines · 7 tokens per session scan A 48d6027a00c0
status is a command published in the GitHub repository Lanzelot1/claw-brain (11 stars, last pushed 6mo ago), licensed MIT. It adds 7 tokens to every session and 602 once invoked, about $0.0000 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 2026-08-30.
Other commands, from other repositories
screenshot
Screenshot a URL or document and read it visually.
obsidian-checkin
Ask the owner whether old people and project notes still hold - shows what each note says and when it was last checked, re-asks until answered, saves the news.
rem_help
Each section is printed verbatim by --help for the command it names. The agreed design is issue #1656; change a page there and here together.
speckit.archive
Archive a feature specification into main project memory after merge, resolving gaps and conflicts.
memory-forget
Command "memory-forget" from waittim/MemoryCustodian, covering memory-forget and review the preview, then apply its plan id.
memory-query
Query an existing graphify graph before rereading the full corpus, using query, path, or explain flows.