Borrowing it
Nothing to install: this file belongs to poteto/noodle. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/poteto/noodle/main/.agents/skills/refine/SKILL.mdgit clone --depth 1 https://github.com/poteto/noodleWrote 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/poteto/noodle/refine)<a href="https://agentmods.dev/skills/poteto/noodle/refine"><img src="https://agentmods.dev/badge/skills/poteto/noodle/refine/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/poteto/noodle/refine"><img src="https://agentmods.dev/badge/skills/poteto/noodle/refine.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 | $0.00038 | $0.00353 |
| Opus 5.5 | $0.00015 | $0.00141 |
| Sonnet 5.5 | $0.00008 | $0.00071 |
| Haiku 4.5 | $0.00004 | $0.00035 |
Grade A, and why
refine 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.
What it actually says
Refine
Read brain/todos.md and refine unclear items into actionable prompts through targeted questioning.
Workflow
Use Tasks to track progress. Create a task for each step below (TaskCreate), mark each in_progress when starting and completed when done (TaskUpdate). Check TaskList after each step.
- Read
brain/todos.mdand review items under## Open. - Triage each item: is it clear enough to act on without further context? A clear item specifies what is wrong, where it happens, and what the fix should be. Skip items that already meet this bar.
- Ask clarifying questions about unclear items using
AskUserQuestion. Group related questions — aim for one round of questions, not a back-and-forth (to minimize back-and-forth and user fatigue). Good clarifying questions target:- What — what exactly is the problem or desired behavior?
- Where — which part of the app, which component, which flow?
- How — how should it work instead? What does "fixed" look like?
- Rewrite unclear items in-place using
Edit, incorporating the user's answers. Each rewritten item should be a self-contained prompt that another agent could act on without additional context. - Remove any items the user says are already done or no longer relevant.
- Report a summary of what changed.
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 · 25 lines · 38 tokens per session scan A 81fd2f479cbd
refine is a skill published in the GitHub repository poteto/noodle (529 stars, last pushed 7mo ago), licensed MIT. It adds 38 tokens to every session and 353 once invoked, about $0.0002 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 2026-08-30.
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