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-autoresearchgit 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-autoresearch)<a href="https://agentmods.dev/skills/tomismeta/aperture/aperture-lab-autoresearch"><img src="https://agentmods.dev/badge/skills/tomismeta/aperture/aperture-lab-autoresearch/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-autoresearch"><img src="https://agentmods.dev/badge/skills/tomismeta/aperture/aperture-lab-autoresearch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 133 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 137 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00038 | $0.01732 |
| Opus 5 | $0.00019 | $0.00866 |
| Sonnet 5 | $0.00008 | $0.00346 |
| Haiku 4.5 | $0.00004 | $0.00173 |
Grade A, and why
aperture_lab_autoresearch 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 11d 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 — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Aperture Lab F-Stop
Use this skill when the task is to run Aperture's offline semantic improvement loop on a remote worker or long-running harness.
This skill is only for the Lab path.
Do not use it for live runtime behavior or product-surface work.
Load First
Before doing anything else, read:
packages/lab/research/autoresearch-program.mdpackages/lab/research/autoresearch-config.json
Those files are the source of truth for:
- allowed edit paths
- forbidden edit paths
- evaluation commands
- artifact chain
- expected outcomes
- non-goals
Follow them strictly.
Main Rule
Keep AI out of the hot path.
This loop may:
- import public trajectories
- prepare offline review artifacts
- run reviewer responses into disagreements and recommendation summaries
- promote selected disagreements into a frozen calibration corpus
- evaluate that corpus repeatably
- propose bounded semantic/importer changes
- run replay and release gates
This loop must not:
- change the live decision path to depend on AI
- edit planner or continuity logic
- auto-merge
Core Commands
Use the provider-neutral lab:fstop:* surface as the default operating path:
pnpm lab:fstop:run --provider <provider> --reviewer-provider <provider> --optimizer-provider <provider> --json
APERTURE_OPENCLAW_REVIEW_TIMEOUT=60 pnpm lab:fstop:review --dataset swe-smith --split tool --limit 3 --reviewer-provider <provider> --json
pnpm lab:fstop:propose --reviewer-provider <provider> --optimizer-provider <provider> --json
pnpm lab:fstop:cycle --json
pnpm lab:fstop:optimize --provider <provider> --json
pnpm judgment:battle
pnpm release:check
For the default short OpenClaw agent-run command, use:
pnpm lab:fstop:openclaw
If you need to debug one bundle manually, fall back to:
pnpm trajectory:import --dataset swe-smith --split tool --limit 3
pnpm lab:fstop:prepare --bundle <bundle-path> --json
pnpm lab:fstop:review:run --artifact <artifact-path> --reviewer-command "pnpm lab:fstop:reviewer --provider <provider>" --json
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.
- 11d ago First seen · 260 lines · 38 tokens per session scan A 5bc311c361b4
aperture_lab_autoresearch is a skill published in the GitHub repository tomismeta/aperture (24 stars, last pushed 4d ago), licensed MIT. It adds 38 tokens to every session and 1,732 once invoked, about $0.0002 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.
Other skills, from other repositories
pr-review
Review Cool Workflow pull requests or branch diffs. Use when Codex must inspect code changes for bugs, regressions, FreeBSD/POLA violations, missing tests, generated artifact drift, release-contract risk, or CI implications, and return findings first with file/line citations.
triage-contributor-pr
Triage open pull requests from external contributors to prisma/prisma and produce a per-PR verdict with evidence. Use when a maintainer asks to triage, evaluate, assess, or review the queue of incoming contributor PRs, to decide whether a fork PR is safe to run CI on, to check whether a PR is in scope for its version…
review-implement-phase
Implements triaged review actions, commits focused fixes, and posts Done plus resolves threads. Use when the user wants only the implementation phase of the review-framework workflow.
no-bare-casts
Writing as in TypeScript or TSX production code, modifying a file that contains a bare as cast, silencing a type error with a cast, encountering as unknown as, or reviewing a cast site.
update-pr
Update the pull request for the current session. Use when the user wants to push new changes to an existing PR.
remember
Review the current conversation and capture valuable knowledge — best practices, coding conventions, architecture decisions, workflows, and user feedback — into persistent memory (AGENTS.md) or reusable skills. Use when the user says: (1) remember this, (2) save what we learned, (3) update memory, (4) capture…