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 Approaching-AI/AIMA --skill aima-controlgit clone --depth 1 https://github.com/Approaching-AI/AIMAWrote 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/approaching-ai/aima/aima-control)<a href="https://agentmods.dev/skills/approaching-ai/aima/aima-control"><img src="https://agentmods.dev/badge/skills/approaching-ai/aima/aima-control/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/approaching-ai/aima/aima-control"><img src="https://agentmods.dev/badge/skills/approaching-ai/aima/aima-control.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 | $0.00021 | $0.00249 |
| Opus 5.5 | $0.00008 | $0.00100 |
| Sonnet 5.5 | $0.00004 | $0.00050 |
| Haiku 4.5 | $0.00002 | $0.00025 |
Grade A, and why
aima-control 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.
What it actually says
AIMA Control Plane
Use AIMA MCP tools for local inference operations on this device.
Preferred tools
system.statusfor overall device and runtime statehardware.detectandhardware.metricsfor capability and live load checksmodel.listandengine.listbefore planning changesdeploy.list,deploy.status,deploy.apply,deploy.delete, anddeploy.logsfor deployment workknowledge.resolvebefore changing engine/model combinationsbenchmark.runafter major deployment changesopenclawwithaction=status|sync|claimfor OpenClaw integration drift
Operating rules
- Prefer MCP tools over shell commands when both are available.
- Treat
tools/listas discovery only; use the listed tools as the supported day-to-day surface. - Before deploying or replacing a model, inspect the current deployment state.
- After changing deployments, verify readiness with
deploy.statusordeploy.list.
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 · 27 lines · 21 tokens per session scan A b6e40607effb
aima-control is a skill published in the GitHub repository Approaching-AI/AIMA (19 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 249 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 2026-08-30.
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