Run N autonomous iterations optimizing a measurable metric with git history.
npx skills add https://github.com/DatTran26/KienTruThiHanh --skill ck-loop-dattran26
Please help me install this Agent Skill. Skill: ck:loop Source: https://github.com/DatTran26/KienTruThiHanh/tree/main/.agents/skills/ck-loop Command: npx skills add https://github.com/DatTran26/KienTruThiHanh --skill ck-loop-dattran26
Autonomous iterative optimization loop that runs N iterations against a measurable metric, learns from git history, and auto-keeps or discards changes, enabling repeatable improvement with traceable experiments.
Configure a Goal and Scope to start an autonomous optimization loop targeting your metric.
High-intent search queries and answers about installing and using this skill.
Autonomous iterative optimization executes isolated code changes against a measurable metric, committing each iteration to git. It learns from experiment history, auto-keeping improvements or rolling back regressions to ensure traceable metric gains.
Git-as-memory logs each guided experiment as a per-iteration commit. If an isolated change fails verification or optional guard checks, the loop discards it and rolls back to the previous committed state to preserve baseline stability.
Guarded verification runs an optional guard step before keeping isolated code changes, protecting against performance regressions. This deterministic protocol evaluates each iteration against baseline metrics, preventing degradation across the codebase.
Configuring an autonomous loop with a defined Goal and Scope executes isolated changes targeting bundle size. It applies per-iteration verification and auto-discards changes that fail to improve the target metric, ensuring guided experimentation.
Autonomous iteration uses a deterministic protocol with per-iteration verification rather than mandating a specific testing framework. Users configure the measurable mechanical metric and optional guard checks to evaluate code quality improvements.
An autonomous optimization loop discards changes that improve the target metric if they fail optional guard checks or per-iteration verification. This deterministic protocol prevents secondary regressions, maintaining overall codebase stability.
hotriluanRun iterative experiments to optimize measurable metrics in git repositories.
ScivorAnalyze commit history to generate per-person retrospective narratives.
djankiesExecute atomic multi-step database operations with automatic rollback via $transaction callback.
4lermanRun autonomous experiment loops to optimize code by a measurable metric.
