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.
git clone --depth 1 https://github.com/SimonBlancoE/kanban-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/simonblancoe/kanban-mcp/help)<a href="https://agentmods.dev/commands/simonblancoe/kanban-mcp/help"><img src="https://agentmods.dev/badge/commands/simonblancoe/kanban-mcp/help/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/simonblancoe/kanban-mcp/help"><img src="https://agentmods.dev/badge/commands/simonblancoe/kanban-mcp/help.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00009 | $0.00772 |
| Opus 5.5 | $0.00004 | $0.00309 |
| Sonnet 5.5 | $0.00002 | $0.00154 |
| Haiku 4.5 | $0.00001 | $0.00077 |
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 1mo 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.
This is a copy
100% identical to help — 11 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.
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:
- Claude receives the SAME prompt
- Works on the task, modifying files
- Tries to exit
- Stop hook intercepts and feeds the same prompt again
- Claude sees its previous work in the files
- 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:
- Creates
.claude/.ralph-loop.local.mdstate file - You work on the task
- When you try to exit, stop hook intercepts
- Same prompt fed back
- You see your previous work
- 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.
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.
- 1mo ago First seen · 127 lines · 9 tokens per session scan A ffbe8965aa08
help is a command published in the GitHub repository SimonBlancoE/kanban-mcp (0 stars, last pushed 9mo ago), licensed MIT. It adds 9 tokens to every session and 772 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to help, differing in 11 lines, and is treated as a copy.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
speckit.bug.fix
Apply the remediation from a bug assessment and record what was changed.