Prompt Optimization Loop

Prompt Optimization Loop is an AI Engineering skill for Claude Code, published by gaasher in Agent-Loop-Skills.

166 stars19 forkson gaasher/Agent-Loop-SkillsAdded 2026/09/08+2% in starsRepository updated 2026/06/30

agent-skillsagentic-loopsagentic-workflowsai-agentsanthropicautoresearchclaudeclaude-codedata-analysisliterature-reviewllm-agentsmachine-learningml-autoresearchopen-sourceprompt-engineeringred-teamingscientific-writingskillssubagents

Install in seconds

Install Prompt Optimization Loop

Copy Prompt Optimization Loop into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/prompt-optimize ~/.claude/skills/prompt-optimize

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/gaasher/Agent-Loop-Skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: loops/prompt-optimize/SKILL.md in gaasher/Agent-Loop-Skills
Installs to: ~/.claude/skills/prompt-optimize
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 3670 skills

What Prompt Optimization Loop does

Prompt Optimization Loop improves an existing prompt by making one targeted edit at a time and re-running a user-provided eval command to see whether the score rises. It is for prompts that already have a measurable metric, not for writing prompts from scratch or changing model settings.

Prompt Optimization Loop is cataloged under AI Engineering on DirSkills. Prompt Optimization Loop comes from a repository tagged agent-skills, agentic-loops, agentic-workflows, ai-agents and anthropic.

Documentation

README

Excerpt

Prompt Optimize Loop

An evolutionary optimizer for a prompt (OpenEvolve / AlphaEvolve-style). The artifact is a prompt that feeds the user's system; the feedback signal is a scalar metric printed by the user's own evaluation command. Each iteration proposes one quality-focused edit, re-runs the eval, and keeps the edit only if the metric improves — evolving the prompt toward higher scores. The eval is a black-box oracle the loop runs but never edits, so the optimization tracks what actually matters rather than gaming a number.

When to use

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Prompt Optimization Loop

What else does gaasher publish alongside Prompt Optimization Loop?
Prompt Optimization Loop is one of 25 skills that DirSkills catalogs from gaasher/Agent-Loop-Skills, the repository it ships in. Its siblings there include Alpha Evolve, Anomaly Investigation and Blue Team. Each one is a separate skill with its own page in this directory, installs the same way Prompt Optimization Loop does, and is maintained by gaasher in that same repository. The rest of the collection is listed on the gaasher/Agent-Loop-Skills page.
How does Prompt Optimization Loop compare to other AI Engineering skills?
Prompt Optimization Loop ranks #3341 by stars among the 3670 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Prompt Optimization Loop against them. Open each page to compare what they document and how they install.