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 agentmods add skills/wellapp-ai/well/autonomous-loopnpx skills add WellApp-ai/Well --skill autonomous-loopgit clone --depth 1 https://github.com/WellApp-ai/WellWrote 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/wellapp-ai/well/autonomous-loop)<a href="https://agentmods.dev/skills/wellapp-ai/well/autonomous-loop"><img src="https://agentmods.dev/badge/skills/wellapp-ai/well/autonomous-loop.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.01054 |
| Opus 5 | $0.00010 | $0.00527 |
| Sonnet 5 | $0.00004 | $0.00211 |
| Haiku 4.5 | $0.00002 | $0.00105 |
Grade A, and why
autonomous-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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonomous Loop Skill (Ralph Wiggum)
Keep iterating until success without human intervention per attempt. Composes existing skills and respects Jidoka escalation.
When to Use
- User requests hands-off iteration
- Explicitly triggered with keywords
Trigger Phrases
- "ralph mode"
- "keep going"
- "iterate until done"
- "autonomous"
- "don't stop"
Parameters
| Param | Default | Description |
|---|---|---|
| max_iterations | 5 | Max attempts before pause |
| success_criteria | typecheck + lint + ReadLints clean | What defines success |
Phase 1: Initialize
- Acknowledge activation
- Invoke
session-statusskill for current state - Initialize counters:
- iteration = 0
- error_history = [] (shared with debug skill)
Output:
Entering autonomous loop. Max 5 iterations.
Current: [session-status header]
Phase 2: Execute Loop
FOR iteration IN 1..max_iterations:
2.1: Execute current task action
- Implement changes per commit plan
- Run npm run typecheck
- Run npm run lint
2.2: Invoke pr-review skill
- If BLOCK: proceed to 2.4
- If PASS: proceed to 2.3
2.3: Invoke qa-commit skill
- If GREEN: proceed to 2.5
- If RED: proceed to 2.4
2.4: Invoke debug skill
- Debug skill checks Jidoka tier internally
- If Tier 2/3 escalation: EXIT loop, return JIDOKA
- If Tier 1 fix attempted: CONTINUE loop
2.5: Success checkpoint
- Log iteration as SUCCESS
- Proceed to next commit or EXIT if done
Phase 3: Iteration Report
After each iteration, output:
## Iteration [N]/[max]
| Step | Skill | Result |
|------|-------|--------|
| Execute | (implementation) | [files changed] |
| Review | pr-review | PASS/BLOCK |
| Verify | qa-commit | GREEN/RED |
| Debug | debug | [if invoked] |
**Outcome:** [SUCCESS / CONTINUE / JIDOKA / MAX]
Phase 4: Exit and Report
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 First seen · 161 lines · 19 tokens per session scan A ab536376eb89
autonomous-loop is a skill published in the GitHub repository WellApp-ai/Well (339 stars, last pushed 27d ago), licensed MIT. It adds 19 tokens to every session and 1,054 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
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