self-evolution

self-evolution is a Skill evaluation & testing skill for AI agents, published by stellarlinkco in the skills repository on GitHub. Skillspace rates self-evolution C (74/100) and it passed the safety scan; the rating is based on static analysis only.

Iteratively evolve any measurable artifact (prompt, skill, code, idea, configuration, document, benchmarked experiment) through autonomous mutation-evaluate-gate loops. Supports both GT case suites and autoresearch-style scalar metric loops where a fixed command prints one score. Uses 8-phase iteration, 3-layer evaluation, deterministic keep/discard gates, trace-driven diagnosis, and layered mutation. Trigger on "evolve this", "optimize iteratively", "self-improve", "train this prompt", "iterate on this code", "make this better through iteration", "run evolution loop", "self-evolution", "evolve this skill", "train this skill", "optimize skill quality", "autonomous research", "autoresearch", or whenever the user has a measurable artifact that needs data-driven improvement with automatic keep/revert decisions.

Grade
C
Quality
74 / 100
Safety
Passed
GitHub stars
24

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

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
Not declared. Check the repository before reusing it.
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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