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 agentmods add skills/jmstar85/oh-my-githubcopilot/autoresearchnpx skills add jmstar85/oh-my-githubcopilot --skill autoresearchgit clone --depth 1 https://github.com/jmstar85/oh-my-githubcopilotWrote 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/jmstar85/oh-my-githubcopilot/autoresearch)<a href="https://agentmods.dev/skills/jmstar85/oh-my-githubcopilot/autoresearch"><img src="https://agentmods.dev/badge/skills/jmstar85/oh-my-githubcopilot/autoresearch.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00208 |
| Opus 5 | $0.00015 | $0.00104 |
| Sonnet 5 | $0.00006 | $0.00042 |
| Haiku 4.5 | $0.00003 | $0.00021 |
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 6d 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
Autoresearch
OMG adapted scope: This workflow is driven by visible checkpoints and evaluator gates, not by an external OMC runtime loop.
Workflow
- Define the research mission, success criteria, constraints, and stop conditions.
- Break the mission into hypotheses or research questions.
- Gather evidence from local docs, code, and permitted web sources.
- Evaluate findings against the success criteria.
- Iterate only while the next pass is likely to improve the answer meaningfully.
- Record final decisions, rejected alternatives, and confidence.
Evaluator Gates
- Evidence sufficiency
- Contradiction check
- Confidence level
- Stop/continue decision
Rules
- Prefer primary sources.
- Label uncertainty clearly.
- Do not loop indefinitely without measurable improvement.
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.
- 6d ago First seen · 31 lines · 30 tokens per session scan A e3f544c7c7ae
autoresearch is a skill published in the GitHub repository jmstar85/oh-my-githubcopilot (154 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 208 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.
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