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 tomismeta/aperture --skill aperture-lab-agentgit clone --depth 1 https://github.com/tomismeta/apertureWrote 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/tomismeta/aperture/aperture-lab-agent)<a href="https://agentmods.dev/skills/tomismeta/aperture/aperture-lab-agent"><img src="https://agentmods.dev/badge/skills/tomismeta/aperture/aperture-lab-agent/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/tomismeta/aperture/aperture-lab-agent"><img src="https://agentmods.dev/badge/skills/tomismeta/aperture/aperture-lab-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00050 | $0.00457 |
| Opus 5 | $0.00025 | $0.00229 |
| Sonnet 5 | $0.00010 | $0.00091 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
aperture_lab_agent 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 9d 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
Aperture Lab F-Stop Runtime
Use this skill when the goal is to run Aperture Lab F-Stop as a self-hosted runtime harness, not when working on the live product path.
The canonical command surface is provider-neutral:
pnpm lab:fstop:run --provider <provider> --reviewer-provider <provider> --optimizer-provider <provider> ...pnpm lab:fstop:review --reviewer-provider <provider> ...pnpm lab:fstop:propose --reviewer-provider <provider> --optimizer-provider <provider> ...pnpm lab:fstop:optimize --provider <provider> ...pnpm lab:fstop:reviewer --provider <provider>pnpm lab:fstop:optimizer --provider <provider>
Supported providers today:
openclawhermesgeneric
Provider-specific shortcuts such as lab:fstop:openclaw are conveniences, not
the core product surface.
Load First
Read:
packages/lab/research/autoresearch-program.mdpackages/lab/research/autoresearch-config.json
These define:
- allowed edit paths
- forbidden edit paths
- artifact flow
- promotion rules
- optimizer output contract
Main Rule
Keep AI out of the hot path.
This harness may:
- run the top-level agent-managed loop
- import public trajectories
- run offline review and disagreement capture
- promote repeated high-confidence disagreements
- optimize against the frozen calibration corpus
- return a reviewable proposal artifact
It must not:
- change live runtime behavior to depend on AI
- edit outside the allowed semantic/importer surface
- auto-merge code
Product Surface
Treat lab:fstop:* as the only supported CLI namespace.
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.
- 9d ago First seen · 67 lines · 50 tokens per session scan A 733b25b3cdb6
aperture_lab_agent is a skill published in the GitHub repository tomismeta/aperture (24 stars, last pushed yesterday), licensed MIT. It adds 50 tokens to every session and 457 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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