Borrowing it
Nothing to install: this file belongs to nimbus-agent/Nimbus. 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/nimbus-agent/Nimbus/main/.claude/commands/nimbus-implicit-knowledge-extraction.mdgit clone --depth 1 https://github.com/nimbus-agent/NimbusWrote 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/nimbus-agent/nimbus/nimbus-implicit-knowledge-extraction)<a href="https://agentmods.dev/commands/nimbus-agent/nimbus/nimbus-implicit-knowledge-extraction"><img src="https://agentmods.dev/badge/commands/nimbus-agent/nimbus/nimbus-implicit-knowledge-extraction/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/nimbus-agent/nimbus/nimbus-implicit-knowledge-extraction"><img src="https://agentmods.dev/badge/commands/nimbus-agent/nimbus/nimbus-implicit-knowledge-extraction.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 | $0.00279 | $0.05011 |
| Opus 5.5 | $0.00112 | $0.02004 |
| Sonnet 5.5 | $0.00056 | $0.01002 |
| Haiku 4.5 | $0.00028 | $0.00501 |
Grade A, and why
nimbus-implicit-knowledge-extraction 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 yesterday.
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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- yesterday Changed · +24 lines 9876427310cf
- 22d ago Changed · +3 lines · -2 tokens per session 567b658f13f4
- 1mo ago Changed · +13 lines 822bb6463825
- 1mo ago First seen · 265 lines · 281 tokens per session scan A 3c29d1abdee3
nimbus-implicit-knowledge-extraction is a command published in the GitHub repository nimbus-agent/Nimbus (7 stars, last pushed yesterday), licensed AGPL-3.0. It adds 279 tokens to every session and 5,011 once invoked, about $0.0011 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 commands, from other repositories
build-corpus
Use when the user invokes /goal-flight build-corpus to build or refresh the private Goal Flight dispatch-context corpus.
retrieval
Search the user's Ryu memory and knowledge Spaces (RAG).
init-workspace-flow-questions
Phase 8 Questions of init-workspace-flow.
compact-prep
Ask the agent to prepare for conversation compaction by updating any relevant state and providing guidance for the compaction agent and to kick off the session there after.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.
slm-bot-memory
Cross-bot memory on a shared computer (Grok Bot, Cursor plugin, any host where several agents share one machine). Explains agentid attribution vs. profile/scope access, how to namespace by agentid + profile + scope, and what must never be written to memory. Read this before the first remember/recall on a new…