What is a 'Ralph loop' in the context of this skill?

A Ralph loop refers to a structured agentic execution cycle where an AI agent follows a plan, uses specific skills, and tracks its progress and outcomes in a dedicated directory.

What files does the Agent Loop Evaluator analyze?

The skill reviews GENERATED.md for project lists, and then dives into loop-specific files like PLAN.md, PROGRESS.md, report history JSON files, and execution logs.

How does the skill distinguish between critical and nice-to-have issues?

Critical issues are those that block success or waste budget, such as repeating errors or missing progress data. Nice-to-haves are optimizations like standardizing formats or adding validation steps.

Can this skill help me reduce my AI token costs?

Yes. It specifically identifies steps with high iteration counts or cost blow-ups, suggesting more efficient skill combinations or step splits to save budget.

What commands trigger this analysis?

You can activate the skill by telling Claude to 'eval projects', 'evaluate loops', 'review ralph loops', or 'analyze project loops'.

Agent Loop Evaluator

Name: Agent Loop Evaluator
Author: mattwoodco

bymattwoodco

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Analíticas y Monitorización

Analyzes agentic workflow execution data to identify performance bottlenecks and suggest optimizations for automated project loops.

Agent Loop Evaluator is a specialized skill designed to audit the performance of 'Ralph loops' by reviewing execution logs, progress reports, and cost metrics. It automatically parses structured data from project directories to identify why specific steps fail, where budgets are being wasted, and how skill combinations can be refined. By generating actionable reports categorized into critical fixes and secondary optimizations, it helps developers increase the reliability and efficiency of their automated agentic workflows.

Características Principales

01Deep log parsing for identifying circuit breakers and flaky steps

02Automated analysis of project loop structures and step granularity

03Structured reporting of critical and nice-to-have project improvements

04Auditing of skill combinations to identify failure hotspots

05Tracking of cost and iteration counts to prevent budget overruns

063 GitHub stars

Casos de Uso

01Standardizing progress tracking and documentation consistency across complex development loops

02Auditing resource usage and cost efficiency across multiple concurrent automated projects

03Optimizing failing agentic workflows by identifying repetitive error patterns and circuit breaker triggers

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add mattwoodco/skills eval-projects

For use in Claude.ai and ChatGPT