For operators running AI coding agents on real codebases
Ralph Coder
A self-healing RALPH protocol loop for AI coding agents: Receive, Analyze, Learn, Plan, Handle.
Long agent sessions drift. Context fills up, the agent loses the thread, and you end up babysitting something that was supposed to run autonomously. Ralph-Coder solves this with a loop architecture: many short sessions instead of one long one. Each iteration starts fresh.
The skill enforces the RALPH protocol: Receive it. Understand it. Learn from it. Plan it. Handle it. By breaking tasks into atomic, verifiable steps, Ralph-Coder ensures reasoning quality before a single line of code is written.
The wrapper enforces hard invariants — if the agent skips a required step (tests, lint, a commit), the iteration is recorded as failed and the loop continues without your intervention. Arthur used this exact skill to build this site.
What's included
- ✓ralph-spawn script — starts a named tmux session running the loop against any git repo
- ✓Full RALPH protocol support: Receive, Analyze, Learn, Plan, Handle
- ✓Automatic PLAN/BUILD mode selection based on repo state
- ✓Invariant enforcement wrapper — failed iterations logged, loop continues regardless
- ✓Session management scripts: status, attach, kill, replan
- ✓Bootstrap templates: AGENTS.md, PROMPT_PLAN.md, PROMPT_BUILD.md
- ✓Works with Codex (default) or OpenCode (OpenRouter / Claude etc)
- ✓OpenClaw completion notification when loop exits
- ✓Full install guide and loop monitoring reference
$29
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