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 Rockielab/rockie-codex --skill self-criticgit clone --depth 1 https://github.com/Rockielab/rockie-codexWrote 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/rockielab/rockie-codex/self-critic)<a href="https://agentmods.dev/skills/rockielab/rockie-codex/self-critic"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-codex/self-critic/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/rockielab/rockie-codex/self-critic"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-codex/self-critic.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 | $0.00040 | $0.00304 |
| Opus 5.5 | $0.00016 | $0.00122 |
| Sonnet 5.5 | $0.00008 | $0.00061 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
self-critic 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 self-critic — 0 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.
What it actually says
self-critic — the agent's internal adversarial flow
This skill is wired in by default (the agent-builder is biased to emit self-adversarial agents). Before this agent returns ANY deliverable for the goal below, harden it here.
Goal under guard
Turn a list of merged pull requests into a clear, user-facing release-notes section grouped by Added / Changed / Fixed, with one plain-language line per change.
How to run
- Produce a draft deliverable.
- Run
critic_loop.pywith the domain critic (domain-critic.md) as a fresh, no-memory reviewer of the draft. - On any CRITICAL: apply the cited fixes, re-run. The clean-pass counter resets to zero on any failed round.
- Converge only on TWO consecutive zero-CRITICAL passes (cap: MAX_ROUNDS=6). Never return a deliverable that has not converged.
Prefer the subagent mode (a fresh subagent per round). When the agent cannot spawn subagents, use the single-process fallback with a hard context reset between rounds — weaker isolation, same termination rules.
Prove the loop logic any time with critic_loop.py --selftest.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 31 lines · 40 tokens per session scan A a8f0057feac8
self-critic is a skill published in the GitHub repository Rockielab/rockie-codex (20 stars, last pushed 12d ago), licensed Apache-2.0. It adds 40 tokens to every session and 304 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to self-critic, differing in 0 lines, and is treated as a copy.
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