iterative-refinement
iterative-refinement is an Execution & autonomous loops skill for AI agents, published by sammcj in the agentic-coding repository on GitHub. Skillspace rates iterative-refinement D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Disciplined, measurable iteration for a substantial refinement or investigation: loop against verifiable pass/fail conditions, fan work out to subagents, and keep the main context lean. Use when improving something measurable over repeated cycles (tuning a metric or detector, refactoring against a regression bar), chasing a surprising or suspicious number, or driving a long multi-step task where delegation and context discipline matter. Not for one-shot edits or quick lookups that don't warrant a loop.
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 150
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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