Add autoresearch#1060
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Pull request overview
Adds a new “autoresearch” Agent Skill to enable an autonomous, metric-driven experimentation loop (baseline → iterative edits → measure → keep/discard) for optimizing programming tasks, and registers it in the skills index.
Changes:
- Introduce a new
skills/autoresearchskill with detailed setup, loop, logging, and reporting instructions. - Add the new skill to the skills catalog table in
docs/README.skills.md.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 3 comments.
| File | Description |
|---|---|
| skills/autoresearch/SKILL.md | New skill content defining the autonomous experimentation workflow and operating rules. |
| docs/README.skills.md | Adds the autoresearch entry to the skills listing. |
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| description: >- | ||
| Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. | ||
| DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric. |
| ``` | ||
| experiment commit metric status description | ||
| ``` | ||
| Add `results.tsv` and `run.log` to `.gitignore` (append if not already present) so they stay untracked. |
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| - IMPROVED: Keep the commit. Update the "best" baseline. | ||
| Log status = "keep". | ||
| - SAME OR WORSE: Revert. `git reset --hard HEAD~1`. | ||
| Log status = "discard". | ||
| - CRASH: Attempt a quick fix (typo, import, simple error). | ||
| If unfixable after 2 attempts, revert and log status = "crash". |
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Pull Request Checklist
npm startand verified thatREADME.mdis up to date.Description
Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch.
Type of Contribution
Additional Notes
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By submitting this pull request, I confirm that my contribution abides by the Code of Conduct and will be licensed under the MIT License.