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 lubochka/xiigen-general-skills --skill review-fix-loopgit clone --depth 1 https://github.com/lubochka/xiigen-general-skillsWrote 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/lubochka/xiigen-general-skills/review-fix-loop)<a href="https://agentmods.dev/skills/lubochka/xiigen-general-skills/review-fix-loop"><img src="https://agentmods.dev/badge/skills/lubochka/xiigen-general-skills/review-fix-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/lubochka/xiigen-general-skills/review-fix-loop"><img src="https://agentmods.dev/badge/skills/lubochka/xiigen-general-skills/review-fix-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 | $0.00031 | $0.00195 |
| Opus 5 | $0.00015 | $0.00097 |
| Sonnet 5 | $0.00006 | $0.00039 |
| Haiku 4.5 | $0.00003 | $0.00019 |
Grade A, and why
review-fix-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 11d 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
Review Fix Loop
Purpose
Close actionable feedback through repeated review and repair.
When to Use
Use after plan review, code review, content review, or release-gate review.
Inputs
Review comments, priority, affected files, acceptance criteria.
Steps
- Classify findings as actionable, question, or non-goal.
- Fix actionable findings.
- Re-run targeted checks.
- Re-review failed areas until pass or blocker.
Gates
All actionable findings are fixed, deferred with reason, or blocked.
Evidence
Updated files, recheck results, and review status table.
Anti-Patterns
Fixing one item and closing the whole review.
Related
generated-code-review, goal-delivery-completeness
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.
- 11d ago First seen · 34 lines · 31 tokens per session scan A 4f8da120bcbe
review-fix-loop is a skill published in the GitHub repository lubochka/xiigen-general-skills (1 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 195 once invoked, about $0.0002 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 2026-08-31.
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