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.
npx skills add shawnclybor/clybor-claude-tooling --skill ralph-loopgit clone --depth 1 https://github.com/shawnclybor/clybor-claude-toolingWrote 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/skills/shawnclybor/clybor-claude-tooling/ralph-loop)<a href="https://agentmods.dev/skills/shawnclybor/clybor-claude-tooling/ralph-loop"><img src="https://agentmods.dev/badge/skills/shawnclybor/clybor-claude-tooling/ralph-loop/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/skills/shawnclybor/clybor-claude-tooling/ralph-loop"><img src="https://agentmods.dev/badge/skills/shawnclybor/clybor-claude-tooling/ralph-loop.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 | $0.00110 | $0.01585 |
| Opus 5.5 | $0.00044 | $0.00634 |
| Sonnet 5.5 | $0.00022 | $0.00317 |
| Haiku 4.5 | $0.00011 | $0.00159 |
Grade A, and why
ralph-loop 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ralph Loop
Implementation of the Ralph Wiggum technique: a single prompt re-fed to Claude on every session-exit attempt via a Stop hook, until Claude emits an exact completion-promise string or max-iterations is reached.
Based on Anthropic's official ralph-loop plugin and Geoffrey Huntley's original technique.
Core concept
/ralph-loop "<prompt>" --completion-promise "DONE" --max-iterations 50
# Then Claude Code automatically:
# 1. Works on the task
# 2. Tries to exit
# 3. Stop hook (.claude/hooks/ralph-stop.sh) blocks exit
# 4. Hook checks transcript for completion-promise
# 5. If found → state cleared, exit allowed
# 6. If not + under budget → state incremented, exit blocked, prompt re-fed
# 7. If not + budget exhausted → state cleared, exit allowed with halt message
The loop is self-referential: the prompt never changes between iterations. Claude's previous work persists in files. Each iteration sees modified files and git history. The improvement comes from reading the result of the previous iteration.
When to use
Good for:
- Well-defined tasks with automatic verification (tests, linters, build, type-check)
- Tasks requiring iteration to refine (getting tests to pass, fixing a flaky integration)
- Greenfield projects you can walk away from
- Overnight unattended runs
Not good for:
- Tasks requiring human judgment or design decisions (use
quality-reviewinstead) - One-shot operations
- Tasks without a clear binary signal for completion
- Production debugging (use
/five-whysand thedebuggeragent)
State + safety
The Stop hook reads .ralph-loop/state.json:
{
"prompt": "<the original prompt>",
"completion_promise": "DONE",
"max_iterations": 50,
"current_iteration": 3,
"started_at": "<iso8601>",
"last_continued_at": "<iso8601>"
}
--max-iterations is the primary safety mechanism. The completion-promise uses exact-string matching so it cannot encode multiple completion conditions (no "SUCCESS" vs "BLOCKED"); always rely on max-iterations as the hard ceiling.
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.
- 4d ago Changed · +5 lines fb15ed407412
- 1mo ago First seen · 162 lines · 110 tokens per session scan A 2c67cd742f40
ralph-loop is a skill published in the GitHub repository shawnclybor/clybor-claude-tooling (6 stars, last pushed 5d ago), licensed MIT. It adds 110 tokens to every session and 1,585 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
autonomous
Run multiple phases hands-free. Chains discuss, plan, build, and verify automatically.
quick
Execute an ad-hoc task with atomic commits. Skips full plan/review.
audit
Review past Claude Code sessions for PBR workflow compliance and UX quality.
debug
Systematic debugging with hypothesis testing. Persistent across sessions.
explore
Explore ideas, think through approaches, and route insights to the right artifacts.
resume
Pick up where you left off. Restores context and suggests next action.