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Agent skill

Ralph Wiggum

by xenitV1 in xenitV1/claude-code-maestro

Surgical Debugger & Code Optimizer. An agent skill from xenitV1/claude-code-maestro.

MITAuto-check: notesDevelopment

Install Ralph Wiggum

skills CLI
$ npx skills add xenitV1/claude-code-maestro --skill ralph-wiggum -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install xenitV1/claude-code-maestro ralph-wiggum --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/xenitV1/claude-code-maestro.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ralph-wiggum .claude/skills/ralph-wiggum && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ralph-wiggum
GitHub stars
229
Token cost
~795 tokens
SKILL.md length
370 words
Files
4 (incl. scripts)
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

Surgical Debugger & Code Optimizer. An agent skill from xenitV1/claude-code-maestro.

  • Works in 4 steps: Forensic Investigation (Phase 1) → The Harness Loop → Reflection Loop (Generate → Reflect →… → …
  • Tasks that involve Root cause analysis
  • SKILL.md covers � AUTONOMOUS DEBUGGING (THE…, ✨ CODE INTEGRITY & REFLECTION, 🛡️ STRATEGIC RECOVERY and � COGNITIVE AUDIT CYCLE, plus 1 more section
  • Runs JavaScript scripts from its folder; calls node

What it does

Ralph Wiggum is an agent skill from xenitV1/claude-code-maestro. Surgical Debugger & Code Optimizer. Autonomous root-cause investigation, persistence-loop fixing, and high-fidelity code reflection. No new features, only fixes.

Its SKILL.md is about 800 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `scripts/js/ralph-harness.js`, `scripts/js/ralph-qa-engine.js` and `scripts/js/reflection-loop.js`).

It sits in Development, covering Root cause analysis. The licence is MIT.

When your agent uses it

  • Tasks that involve Root cause analysis

Example prompts

  • “/ralph-wiggum”

Requirements

  • Node.js
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Glob, Grep, Bash

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Forensic Investigation (Phase 1)
  2. The Harness Loop
  3. Reflection Loop (Generate → Reflect → Refine)
  4. Algorithmic Hygiene

What it can do on your machine

Read from SKILL.md and the folder at commit 924315b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Glob
    • Grep
    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ralph Wiggum loads about 795 tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 370 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~795

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Glob, Grep, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from xenitV1/claude-code-maestro at commit 924315b, republished under its MIT licence (© xenitV1). 370 words, ~795 tokens.

Download SKILL.mdSave it as .claude/skills/ralph-wiggum/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
ralph-wiggum
description
Surgical Debugger & Code Optimizer. Autonomous root-cause investigation, persistence-loop fixing, and high-fidelity code reflection. No new features, only fixes.
allowed-tools
Read, Write, Edit, Glob, Grep, Bash

<domain_overview>

🔄 RALPH WIGGUM: SURGICAL FIXER

Philosophy: "I'm helping!" — Rational: Fix the root, not the symptom. ROOT CAUSE SURGERY MANDATE (CRITICAL): Ralph is not a feature developer. He is a surgical specialist for existing logic failures. You MUST NOT propose fixes without completed Phase 1 (Forensic Root Cause). Every fix MUST address the architectural flaw that allowed the bug to manifest. Reject any patch that merely hides a symptom or adds "Maybe this works" logic. </domain_overview> <autonomous_debugging>

� AUTONOMOUS DEBUGGING (THE HARNESS)

Ralph uses the ralph-harness.js to ruthlessly pursue and eliminate error signals.

1. Forensic Investigation (Phase 1)
  • Trace Back: Use @debug-mastery to find the bad value origin.
  • Reproduce: Never fix what you haven't broken first with a test.
  • State Check: Check .maestro/brain.jsonl for historical context on why this logic was built.
2. The Harness Loop

Run fix attempts through the persistent orchestrator:

bash
node scripts/js/ralph-harness.js "npm test" --elite
  • Max Iterations: 50 loops (Stop after 3 same errors).
  • Circuit Breaker: If 3 failures occur, STOP and question the architecture. </autonomous_debugging> <code_improvement_loop>

✨ CODE INTEGRITY & REFLECTION

Ralph ensures all existing code meets the @clean-code standard.

1. Reflection Loop (Generate → Reflect → Refine)

Before finalizing any code optimization:

bash
node scripts/js/reflection-loop.js
  • Checklist: Edge cases, Input validation, Security, Completeness.
  • Rule: If the reflection finds MAJOR issues, the code is rejected immediately.
2. Algorithmic Hygiene
  • Naming: Every variable and function must reveal its intent.
  • Modularity: No "Logic Slabs". Break code into testable, single-responsibility slices. </code_improvement_loop> <recovery_and_pivots>
Show full SKILL.md (141 more words)Show less

🛡️ STRATEGIC RECOVERY

When basic fixes fail, Ralph triggers intelligent pivots.

  • Strategy: Different Algorithm: Delete it and start with a fresh mental model.
  • Strategy: Divide & Conquer: Break the complex fix into 3 smaller, testable steps.
  • Strategy: Rollback: If regressions occur, return to the last stable git commit.
  • Strategy: Ask Clarification: If 50 iterations fail, stop and ask the Architect for new context. </recovery_and_pivots> <audit_and_reference>

� COGNITIVE AUDIT CYCLE

  1. Did I find the ROOT CAUSE or just a symptom?
  2. Did I write a test that fails without my fix?
  3. Did my fix introduce "Blast Radius" damage in unrelated files?
  4. Did the Reflection Loop pass with zero major issues?

� INTEGRATION

  • Surgical Tool: Called when tests fail or code is "smelly".
  • Pairing: Works with @debug-mastery (Investigation) and @clean-code (Standard).
  • No Feature Mode: Ralph is explicitly forbidden from designing new business requirements. </audit_and_reference>

© xenitV1, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in skills/ralph-wiggum of xenitV1/claude-code-maestro.

  • SKILL.md
  • scripts/js/ralph-harness.js
  • scripts/js/ralph-qa-engine.js
  • scripts/js/reflection-loop.js

Open the folder on GitHubat commit 924315b

Compare with similar skills

Ralph Wiggum next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ralph Wiggum compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ralph Wiggum this skillxenitV1/claude-code-maestro229—~795Automated safety check: NotesMIT
OpenLogi macOS Permissions TriageAprilNEA/OpenLogi23k—~2.5kAutomated safety check: NotesApache-2.0
Bug Finder for daisyUIsaadeghi/daisyui43k—~2.3kAutomated safety check: PassMIT
Root Cause Debugginggarrytan/gstack136k—~1.4kAutomated safety check: PassMIT
Review PRapache/shardingsphere21k—~6.5kAutomated safety check: PassApache-2.0
Graph-Based Bug Tracingtirth8205/code-review-graph32k1 repos~287Automated safety check: PassMIT

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Categories

Questions about Ralph Wiggum

What does Ralph Wiggum do?

Surgical Debugger & Code Optimizer. An agent skill from xenitV1/claude-code-maestro. Ralph Wiggum is an agent skill from xenitV1/claude-code-maestro. Surgical Debugger & Code Optimizer.

When should I use Ralph Wiggum?

Ralph Wiggum fits situations like: tasks that involve Root cause analysis.

How do I install Ralph Wiggum in Claude Code?

Run `npx skills add xenitV1/claude-code-maestro --skill ralph-wiggum -a claude-code`. Or copy the skill folder (skills/ralph-wiggum in xenitV1/claude-code-maestro) into .claude/skills/ralph-wiggum in your project. Claude Code loads it when a task matches its description.

How do I install Ralph Wiggum in Codex?

Run `npx skills add xenitV1/claude-code-maestro --skill ralph-wiggum -a codex`. Or copy the skill folder (skills/ralph-wiggum in xenitV1/claude-code-maestro) into .agents/skills/ralph-wiggum in your project. Codex loads it when a task matches its description.

Can I use Ralph Wiggum in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xenitV1/claude-code-maestro --skill ralph-wiggum -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ralph-wiggum, .gemini/skills/ralph-wiggum, .github/skills/ralph-wiggum and .opencode/skills/ralph-wiggum in your project.

What does Ralph Wiggum need to run?

Going by SKILL.md and its folder, Ralph Wiggum needs JavaScript for the scripts in its folder and the command-line tools its instructions call (node). Our summary lists: Node.js. Its frontmatter pre-approves these tools: Read, Write, Edit, Glob, Grep, Bash.

Does Ralph Wiggum access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ralph Wiggum safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Ralph Wiggum use?

Ralph Wiggum is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ralph Wiggum use?

About 795 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ralph Wiggum?

Skills that share tags, products or a category with Ralph Wiggum: OpenLogi macOS Permissions Triage (AprilNEA/OpenLogi, 23k stars), Bug Finder for daisyUI (saadeghi/daisyui, 43k stars), Root Cause Debugging (garrytan/gstack, 136k stars) and Review PR (apache/shardingsphere, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ralph Wiggum?

xenitV1 (a GitHub user) maintains it in xenitV1/claude-code-maestro, which has 229 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on January 24, 2026.

Source: xenitV1/claude-code-maestro on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.