📊
AI EngineeringTypeScript

Ralph Analytics

by jmagly

Ralph Analytics is an AI Engineering skill for Claude Code, published by jmagly in aiwg.

209 stars32 forkson jmagly/aiwgAdded 2026/09/04+1% in starsRepository updated 2026/09/03
View source on GitHubDownload repo ZIP
agentic-codingai-frameworkanthropicautonomous-agentsclaude-codecodexcopilotcursordeveloper-toolsfine-tuningmulti-agentmulti-platformorchestrationprompt-engineeringsdlctraining-datawarpworkflow-automation
Install in seconds
Install Ralph Analytics
Copy Ralph Analytics 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/jmagly/aiwg/tree/main/agentic/code/addons/agent-loop/skills/ralph-analytics ~/.claude/skills/ralph-analytics

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/jmagly/aiwg.git

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

In this catalog

Source file
agentic/code/addons/agent-loop/skills/ralph-analytics/SKILL.md in jmagly/aiwg
Installs to
~/.claude/skills/ralph-analytics
Collection
One of 25 skills cataloged from this repository
Category
AI Engineering — 2970 skills

What Ralph Analytics does

Ralph Analytics shows aggregate metrics from agent loop execution history. It is used to review success rates, iteration counts, stuck loops, reflections, and escalation patterns.

Ralph Analytics is cataloged under AI Engineering on DirSkills. Ralph Analytics comes from a repository tagged agentic-coding, ai-framework, anthropic, autonomous-agents and claude-code.

Documentation

README

Al Analytics Command

Display aggregate analytics and metrics from agent loop execution history.

Instructions

When invoked, analyze agent loop data and present metrics:

  1. Scan Loop History

    • Load all loop records from .aiwg/ralph/
    • Load reflections from .aiwg/ralph/reflections/
    • Load debug memory from .aiwg/ralph/debug-memory/

  2. Calculate Metrics

    • Success rate: % of loops that completed successfully
    • Average iterations: Mean iterations to completion
    • Reflection reuse rate: % of reflections applied in subsequent loops
    • Stuck loop rate: % of loops that hit stuck detection
    • Escalation rate: % requiring human intervention

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

Frequently asked about Ralph Analytics

  • What else does jmagly publish alongside Ralph Analytics?

    Ralph Analytics is one of 25 skills that DirSkills catalogs from jmagly/aiwg, the repository it ships in. Its siblings there include Agent Loop, Agent Loop and Agent Loop External. Each one is a separate skill with its own page in this directory, installs the same way Ralph Analytics does, and is maintained by jmagly in that same repository. The rest of the collection is listed on the jmagly/aiwg page.

  • How does Ralph Analytics compare to other AI Engineering skills?

    Ralph Analytics ranks #2729 by stars among the 2970 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 Ralph Analytics against them. Open each page to compare what they document and how they install.

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