Borrowing it
Nothing to install: this file belongs to Orinks/AccessiWeather. 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/Orinks/AccessiWeather/main/.codex/skills/autoresearch/SKILL.mdgit clone --depth 1 https://github.com/Orinks/AccessiWeatherWrote 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/orinks/accessiweather/autoresearch)<a href="https://agentmods.dev/skills/orinks/accessiweather/autoresearch"><img src="https://agentmods.dev/badge/skills/orinks/accessiweather/autoresearch.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.00595 |
| Opus 5 | $0.00009 | $0.00298 |
| Sonnet 5 | $0.00003 | $0.00119 |
| Haiku 4.5 | $0.00002 | $0.00060 |
Grade A, and why
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 8d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autoresearch
Autoresearch is the skill-first replacement for the deprecated omx autoresearch command.
It keeps the useful measured-research loop, but it now runs as a native-hook stateful workflow instead of a direct CLI or tmux launch surface.
Use when
- You want a Ralph-ish persistent research loop
- The task should keep nudging until explicit validation evidence exists
- You want init-time choice between script validation and prompt+architect validation
Do not use when
- You want the old
omx autoresearchcommand surface (hard-deprecated) - You want detached tmux or split-pane launch parity
- You have not decided the validation regime yet
Core contract
- Init chooses validation mode. Pick exactly one:
mission-validator-scriptprompt-architect-artifact
- Persist mode state in
.omx/state/.../autoresearch-state.jsonincluding:validation_modecompletion_artifact_pathmission_validator_commandorvalidator_prompt- optional
output_artifact_path
- Completion is artifact-gated. The loop does not stop because the model says “done”, because a stop hook fired once, or because several turns were no-ops.
- Direct CLI launch is gone. Use
$deep-interview --autoresearchfor intake and$autoresearchfor execution.
Completion artifact contract
mission-validator-script
The completion artifact must exist and record a passing validator result, for example:
{
"status": "passed",
"passed": true,
"summary": "metric improved beyond baseline"
}
prompt-architect-artifact
The completion artifact must include both an architect approval verdict and an output artifact path, for example:
{
"validator_prompt": "Review the research output against the mission.",
"architect_review": { "verdict": "approved" },
"output_artifact_path": ".omx/specs/autoresearch-demo/report.md"
}
Recommended flow
- Run
$deep-interview --autoresearchto clarify mission + evaluator. - Materialize
.omx/specs/autoresearch-{slug}/mission.md,sandbox.md, andresult.json. - Start
$autoresearchwith the chosen validation mode stored in mode state. - Let stop-hook / auto-nudge continue until the completion artifact satisfies the chosen validation mode.
- Finish only after the validator artifact is complete.
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.
- 8d ago First seen · 69 lines · 17 tokens per session scan A a6036b5efa10
autoresearch is a skill published in the GitHub repository Orinks/AccessiWeather (24 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 595 once invoked, about $0.0001 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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