AI & Machine Learning
Self Improvement Loops
This skill should be used when the harness, scaffold, workflow, or optimizer itself is the optimization target: recursive self-improvement (RSI) loops, meta-harnesses, self-improving harnesses that mine their own failures and propose bounded edits, evolutionary or population-based search over agent scaffolds, acceptance gates for self-modifying systems, and agentic context evolution where the mechanism that produces context is versioned and evolved. Route governance of a single autonomous loop (locked surfaces, durable logs, rollback, novelty gates, approval boundaries) to harness-engineering, measurement and quality-gate design to evaluation, judge design to advanced-evaluation, and remote sandbox infrastructure to hosted-agents.
- Publisher / source
- muratcankoylan/Agent-Skills-for-Context-Engineering (found on GitHub top repositories)
- Upstream record
- muratcankoylan/Agent-Skills-for-Context-Engineering
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
de088dd42e92de999da54c6d1a17bed7daf3404688888482735deaa4f482d846