labautoresearch
SolidSelf-improving loop for plugin skills. Reads program.md, proposes one mutation per iteration, evaluates against deterministic scorer, keeps improvements via git, reverts failures. Targets weakest skill+dimension. Use with /loop for overnight runs.
Install
Quality Score: 95/100
Skill Content
Details
- Author
- oliver-kriska
- Repository
- oliver-kriska/claude-elixir-phoenix
- Created
- 3 months ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
autoresearch
Scaffold and run Karpathy-style autoresearch loops in any git repo. This skill should be used when setting up autonomous code improvement, generating adversarial eval harnesses, running hypothesis-implement-eval-keep/discard loops, or checking autoresearch progress. Triggers on "autoresearch", "autonomous improvement", "eval loop", "hypothesis loop", "self-improvement loop".
autoresearch
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.
autoresearch
Karpathy's autoresearch: autonomous ratcheting optimization loops for any artifact. A human writes program.md, the agent runs experiments with git-backed keep/revert. Trigger on "optimize this", "make this better", "iterate on", "autoresearch", "loop on this", "A/B test", "find the best version", Karpathy's loop, experiment loops, hill climbing, the ratchet pattern, or program.md workflows. Works across code, prompts, content, models, and configs.
eval-autoresearch-fit
Trigger with "evaluate autoresearch fit", "score this skill for karpathy loop", "is this a good autoresearch candidate", "assess autoresearch viability for", "which skills are best for autonomous loop optimization", "score skills for 3-file architecture", or when the user wants to determine if a skill is a good candidate for applying the Karpathy autoresearch autonomous optimization loop pattern.
skill-improver
Autoresearch loop for Claude Code skills — greedy keep/discard hill climbing on a 10-dimension quality rubric, with blind subagent validation for self-scoring bias, plus a `freshen` mode that probes external references (release notes, docs, deprecation signals) and applies verified updates, plus a `trigger` mode that measures and tunes the skill's frontmatter description until it reliably fires when it should and stays silent when it shouldn't (60/40 train/test split, 3 runs/query, blinded test scores).