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ralph-wiggum-codex

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Ralph Wiggum For Codex

Codex-native long-running refinement loop.

This skill is designed to be invoked as a Codex skill ($ralph-wiggum-codex). The loop runner script is an internal execution engine for the skill, not the primary user-facing entrypoint.

When To Use

Use this skill when:

  • The task is unlikely to finish in one turn.
  • You need repeated implement -> validate -> refine cycles.
  • You want schema-based completion signaling with resumable state.
  • You need unattended or semi-attended long-running execution with drift resistance.

Do not use this skill when:

  • The request is a quick one-shot edit or explanation.
  • No meaningful validation loop exists.
  • The user wants manual step-by-step control each turn.

Companion Prompt Generator (Recommended Handoff)

When objectives are ambiguous or missing loop configuration, invoke $ralph-prompt-generator first to produce a ready-to-run block for this skill.

Use the companion first when:

  • Validation commands are unknown or incomplete.
  • Scope/progress paths are unclear.
  • Model/reasoning/iteration caps are not specified.
  • The task is high risk and you want stronger guardrails before execution.

Companion handoff pattern:

  1. Run $ralph-prompt-generator with the raw request.
  2. Answer its required question about suggested output sections.
  3. Confirm any inferred validations/scopes it proposes (or provide your own).
  4. Provide any additional targeted clarifications it requests.
  5. Execute the generated block, which should start with:
    • /skills
    • $ralph-wiggum-codex

You can skip the companion when you already have a complete, validated prompt with explicit flags and checks.

Skill-First Operating Contract

When this skill is invoked, execute this flow:

  1. Collect or infer:
  • cwd
  • Objective text
  • Validation commands (fastest checks first)
  • Progress scopes (--progress-scope) for meaningful edits
  • Codex runtime binary/path (--codex-bin) for deterministic runtime selection
  • Event stream artifact format (--events-format <tsv|jsonl|both>, default both)
  • Whether to persist per-iteration progress artifacts (--progress-artifact)
  • Runtime caps (max-iterations, max-stagnant-iterations, timeout settings)
  • Completion promise only if compatibility mode is required (deprecated)
  1. Prepare loop files under <cwd>/.codex/ralph-loop/:
  • objective.md (objective to reload every iteration)
  • feedback.md (optional operator steering)
  1. Start the loop runner with objective/feedback files and validations.

  2. Monitor run artifacts (events.log, run-summary.md, iteration-history.md, validation logs) and report concise progress.

  3. If blocked, update feedback.md with corrective guidance and continue (--resume) instead of restarting from scratch.

Execution Command Template

~/.codex/skills/ralph-wiggum-codex/scripts/ralph-loop-codex.sh \
  --cwd /path/to/repo \
  --codex-bin codex \
  --objective-file /path/to/repo/.codex/ralph-loop/objective.md \
  --feedback-file /path/to/repo/.codex/ralph-loop/feedback.md \
  --events-format both \
  --progress-artifact \
  --completion-promise "DONE" \
  --max-iterations 40 \
  --max-stagnant-iterations 6 \
  --progress-scope "src/" \
  --idle-timeout-seconds 900 \
  --hard-timeout-seconds 7200 \
  --timeout-retries 1 \
  --validate-cmd "npm run lint" \
  --validate-cmd "npm run test"

Long-Run Refinement Features

The runner supports long-running autonomy with iterative correction:

  • Dynamic objective reload each iteration (--objective-file)
  • Live operator feedback ingestion (--feedback-file)
  • Auto-generated corrective feedback when codex/validation fails (auto-feedback.md)
  • Iteration memory (iteration-history.md) injected into future prompts
  • Stagnation detection (--max-stagnant-iterations)
  • Scoped no-op prevention (--progress-scope + no_change_justification)
  • Default-on watchdog timeouts with controlled retries
  • Resumable state and lock-based single-run protection with stale lock recovery

Output Contract

Completion is accepted when all of the following are true:

  • codex exec output conforms to .codex/ralph-loop/completion-schema.json
  • status is COMPLETE
  • Validation commands pass
  • Scoped progress gate passes (or includes no_change_justification)
  • If compatibility mode is enabled, completion_promise equals --completion-promise

Schema fields:

  • status: IN_PROGRESS, BLOCKED, COMPLETE
  • evidence: non-empty array of concrete evidence
  • next_step: one highest-impact next step
  • no_change_justification: required key; non-empty only for justified no-change iterations, else empty string
  • completion_promise: required key; compatibility value when configured, else empty string

Core Files

  • .codex/ralph-loop/state.env
  • .codex/ralph-loop/prompt.txt
  • .codex/ralph-loop/events.log
  • .codex/ralph-loop/events.jsonl (with --events-format jsonl|both; default both)
  • .codex/ralph-loop/completion-schema.json
  • .codex/ralph-loop/iteration-history.md
  • .codex/ralph-loop/feedback.md
  • .codex/ralph-loop/auto-feedback.md
  • .codex/ralph-loop/last-message.txt
  • .codex/ralph-loop/run-summary.md
  • .codex/ralph-loop/progress/ (when --progress-artifact is enabled)
  • .codex/ralph-loop/validation/
  • .codex/ralph-loop/codex/iteration-<n>-attempt-<m>.jsonl
  • .codex/ralph-loop/.lock/meta.env (while active)

events.log remains compatible for existing consumers; JSONL events are additive.

Resume And Stop

Resume:

~/.codex/skills/ralph-wiggum-codex/scripts/ralph-loop-codex.sh \
  --cwd /path/to/repo \
  --resume

Stop safely:

touch /path/to/repo/.codex/ralph-loop/STOP

References

  • Harness principles: references/harness-principles.md
  • Operational runbook: references/runbook.md
  • Reliability vNext: references/reliability-vnext.md

Source

git clone https://github.com/MattMagg/ralph-wiggum-codex/blob/main/skills/ralph-wiggum-codex/SKILL.mdView on GitHub

Overview

Ralph Wiggum Codex enables long-running, multi-turn coding tasks with explicit completion criteria, validation checks, and resumable loop state. It supports schema-based progress signaling and drift-resistant unattended execution, ensuring repeated refine cycles converge to a defined outcome.

How This Skill Works

Used as a Codex skill, it collects cwd, objective text, validation commands, and progress scopes, then runs a loop under <cwd>/.codex/ralph-loop/. It creates objective.md and feedback.md, launches the loop runner, and emits artifacts like events.log, run-summary.md, and iteration-history.md to track progress and enable resume capability.

When to Use It

  • The task is unlikely to finish in one turn and needs iterative refine cycles.
  • You require implement -> validate -> refine cycles with explicit completion criteria.
  • You want schema-based completion signaling with resumable state and per-iteration context.
  • You need unattended or semi-attended long-running execution with drift resistance.
  • Avoid for quick one-shot edits or when there is no meaningful validation loop.

Quick Start

  1. Step 1: Prepare your workspace and create objective.md; optionally include initial feedback.md.
  2. Step 2: Start the loop with the real script (e.g., ~/.codex/skills/ralph-wiggum-codex/scripts/ralph-loop-codex.sh) and provide validation commands.
  3. Step 3: Monitor artifacts (events.log, run-summary.md, iteration-history.md); update feedback.md and use --resume to continue when blocked.

Best Practices

  • Define objective.md and at least the initial validation commands before starting the loop.
  • Keep progress scopes narrow and measurable (e.g., subset of code, tests, or specs).
  • Use feedback.md to steer corrections; update it when the loop stalls and you want to resume.
  • Leverage iteration-history.md to preserve context and improve future iterations.
  • Run validations frequently (lint, tests) and capture artifacts (events.log, run-summary.md) for auditing.

Example Use Cases

  • Incrementally refactor a legacy module with automated validation after each change.
  • Implement a new feature via iterative build -> test -> refine cycles with clear criteria.
  • Migrate dependencies or configs and auto-detect drift with structured feedback.
  • Auto-generate or complete a large spec by validating intermediate outputs at each step.
  • Pause and resume performance tuning with per-iteration state carried forward.

Frequently Asked Questions

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