Borrowing it
Nothing to install: this file belongs to Cyruskraad/codex-claude-mcp. 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/Cyruskraad/codex-claude-mcp/main/.agents/skills/reporting-noodle-feedback/SKILL.mdgit clone --depth 1 https://github.com/Cyruskraad/codex-claude-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/skills/cyruskraad/codex-claude-mcp/reporting-noodle-feedback)<a href="https://agentmods.dev/skills/cyruskraad/codex-claude-mcp/reporting-noodle-feedback"><img src="https://agentmods.dev/badge/skills/cyruskraad/codex-claude-mcp/reporting-noodle-feedback/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/cyruskraad/codex-claude-mcp/reporting-noodle-feedback"><img src="https://agentmods.dev/badge/skills/cyruskraad/codex-claude-mcp/reporting-noodle-feedback.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 | $0.00031 | $0.00358 |
| Opus 5.5 | $0.00012 | $0.00143 |
| Sonnet 5.5 | $0.00006 | $0.00072 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
reporting-noodle-feedback 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 2mo 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
reporting-noodle-feedback
Preview one sanitized feedback proposal and submit it once only after informed explicit approval.
Use when
- Report a Noodle Seed bug or documentation gap.
- Propose a concrete Noodle product improvement.
Do not use when
- Do not use for generic project bugs.
- Do not send customer code, identifiers, logs, or secrets.
Required inputs
- One distinct finding.
- Sanitized observed and expected behavior.
- User approval for the exact dry-run preview and live command.
Workflow
Read and follow the canonical playbook references/feedback.md at ../noodle-seed/references/feedback.md. It owns the workflow; do not recreate it here or load the command catalog speculatively.
Verification evidence
The user saw the exact sanitized preview, diagnostics, destination, and live command; only a returned reference proves submission.
Recovery paths
If login or rate limits block the one live submission, report that nothing was sent. A recording failure has an unknown outcome: report no reference and never auto-login or retry-loop.
Stop conditions
Stop after the local dry-run and before the live command until the user explicitly approves it.
Handoff contract
Pass the selected outcome, explicit target, changed files, commands run, passing evidence, first unproven evidence layer, sanitized failure, remaining authority, and exact next action. The receiving skill continues from that layer; do not restart discovery or discard prior proof.
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.
- 2mo ago First seen · 47 lines · 31 tokens per session scan A eea2382fb9cd
reporting-noodle-feedback is a skill published in the GitHub repository Cyruskraad/codex-claude-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 358 once invoked, about $0.0001 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.
reporting-noodle-feedback compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| reporting-noodle-feedbackCyruskraad/codex-claude-mcp | Skill | 0 | 2mo ago | MIT | A | 31 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |