help

A help command that explains the Ralph Wiggum technique, a method that repeats the same AI prompt while the AI improves the files left by earlier runs.

In plain words
What is it for?
Use it to learn how the repeated-work cycle functions and how to use commands such as starting a loop with an iteration limit or completion phrase.
Why use it?
It gives users an overview of the technique and the commands available for starting and controlling its loops.

Command

Part of the ralph-wiggum plugin — 3 commands, 1 hook shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/simonblancoe/kanban-mcp/help
Clone the repo
git clone --depth 1 https://github.com/SimonBlancoE/kanban-mcp

Or install ralph-wiggum, the plugin that ships this one along with the rest of its 3 commands, 1 hook.

Per session 9 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 772 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00009 $0.00772
Opus 5 $0.00005 $0.00386
Sonnet 5 $0.00002 $0.00154
Haiku 4.5 $0.00001 $0.00077

Measured 2d ago against content hash ffbe8965aa08, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

help scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to help — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

ralph/plugin/commands/help.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ralph Wiggum Plugin Help

Please explain the following to the user:

What is the Ralph Wiggum Technique?

The Ralph Wiggum technique is an iterative development methodology based on continuous AI loops, pioneered by Geoffrey Huntley.

Core concept:

while :; do
  cat PROMPT.md | claude-code --continue
done

The same prompt is fed to Claude repeatedly. The "self-referential" aspect comes from Claude seeing its own previous work in the files and git history, not from feeding output back as input.

Each iteration:

  1. Claude receives the SAME prompt
  2. Works on the task, modifying files
  3. Tries to exit
  4. Stop hook intercepts and feeds the same prompt again
  5. Claude sees its previous work in the files
  6. Iteratively improves until completion

The technique is described as "deterministically bad in an undeterministic world" - failures are predictable, enabling systematic improvement through prompt tuning.

Available Commands

/ralph-loop [OPTIONS]

Start a Ralph loop in your current session.

Usage:

/ralph-loop "Refactor the cache layer" --max-iterations 20
/ralph-loop "Add tests" --completion-promise "TESTS COMPLETE"

Options:

  • --max-iterations <n> - Max iterations before auto-stop
  • --completion-promise <text> - Promise phrase to signal completion

How it works:

  1. Creates .claude/.ralph-loop.local.md state file
  2. You work on the task
  3. When you try to exit, stop hook intercepts
  4. Same prompt fed back
  5. You see your previous work
  6. Continues until promise detected or max iterations

/cancel-ralph

Cancel an active Ralph loop (removes the loop state file).

Usage:

/cancel-ralph

How it works:

  • Checks for active loop state file
  • Removes .claude/.ralph-loop.local.md
  • Reports cancellation with iteration count

Key Concepts

Completion Promises

To signal completion, Claude must output a <promise> tag:

<promise>TASK COMPLETE</promise>

The stop hook looks for this specific tag. Without it (or --max-iterations), Ralph runs infinitely.

Read the full file on GitHub · 127 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 127 lines · 9 tokens per session scan A ffbe8965aa08

Subscribe to this mod's changes

help is a command published in the GitHub repository SimonBlancoE/kanban-mcp (0 stars, last pushed 7mo ago), licensed MIT. It adds 9 tokens to every session and 772 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to help, differing in 0 lines, and is treated as a copy.