skill-improver

Solid

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, 7 runs/query, blinded test scores).

AI & Automation 3 stars 1 forks Updated yesterday MIT

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Quality Score: 79/100

Stars 20%
20
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Skill Improver — Autoresearch for SKILL.md > **Core Philosophy:** The human programs the researcher, not the research. > Apply Karpathy's autoresearch methodology — greedy hill climbing with > keep/discard against a scalar metric — to autonomously improve Claude Code > skills. ## Invocation Argument grammar: ``` /skill-improver <mode> <target> [--opts] ``` - `<mode>` — `improve` (default) | `score` | `freshen` | `trigger` | `philosophy` | `batch` - `<target>` — skill name (e.g. `gh-cli`), absolute SKILL.md path, `--all`, or glob (e.g. `vllm-*`) - `[--opts]` — mode-specific flags (e.g. `--iterations 15`, `--probe-budget 30`, `--runs-per-query 5`) Examples: ``` /skill-improver freshen autoresearch /skill-improver score gh-cli /skill-improver improve ~/.claude/skills/helm /skill-improver trigger vllm-caching /skill-improver trigger gh-cli --missed "find issue with label X" /skill-improver batch freshen --all /skill-improver freshen --group 'vllm-*' ``` If `<mode>` is omitted, default to `improve`. If `<target>` is omitted and mode is not `batch`, prompt the user. For `batch`, the target after `batch` selects the sub-mode (`freshen`, `improve`, `trigger`, or `philosophy`, default `improve`); the target list comes from `scripts/scan-skills.sh`. The `--missed "<phrase>"` flag (trigger mode only, repeatable) seeds the eval set with user-reported failures as gold should-trigger queries. ## The Improvement Loop ### Phase 0: Setup 1. Identify the target skill. Accept a pat...

Details

Author
air-gapped
Repository
air-gapped/skills
Created
3 months ago
Last Updated
yesterday
Language
Python
License
MIT

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