Run bounded iterations to improve a measurable metric in a git repository.
npx skills add https://github.com/vanducng/skills --skill optimize-loop
Please help me install this Agent Skill. Skill: optimize-loop Source: https://github.com/vanducng/skills/tree/main/skills/optimize-loop Command: npx skills add https://github.com/vanducng/skills --skill optimize-loop
This Skill automates autonomous improvement of a measurable metric by running a bounded sequence of iterations, committing each attempt, and automatically keeping or discarding changes based on a target metric.
Define your Goal/Scope/Verify, then start the optimize-loop to run bounded iterations against your metric.
High-intent search queries and answers about installing and using this skill.
To automate test coverage or bundle size optimization, you can run a bounded loop that iteratively applies changes, verifies the metric, and commits improvements. This autonomous loop keeps beneficial changes and discards regressions automatically.
An autonomous metric improvement loop runs a bounded sequence of iterations against a defined metric. It executes a verify command to measure a numeric value, commits successful attempts, and uses a guard to validate that no regressions occur during the process.
Yes, you need a git repository with a clean working tree to run iterative metric optimization. This requirement ensures that the automated commit history accurately tracks only the changes generated by the optimization loop without conflicting with existing uncommitted work.
Yes, you can use automated optimization loops to reduce p95 latency and lint errors. The process requires a verify command that prints a single numeric value, allowing the loop to measure, commit, and keep improvements for any quantifiable codebase metric.
The main limitation of bounded iterations is that the loop stops after reaching a defined iteration limit, regardless of whether the target metric is fully achieved. Additionally, the process strictly requires a verify command that outputs a single numeric value to function correctly.
To set up a verification guard, define an optional guard command alongside your verify command to validate changes before they are permanently committed. This ensures the autonomous optimization loop discards any iteration that causes a metric regression in your codebase.
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