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/xspoonai/spoon-bot/code_reviewnpx skills add XSpoonAi/spoon-bot --skill code_reviewgit clone --depth 1 https://github.com/XSpoonAi/spoon-botWhat 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 | $0.00016 | $0.00340 |
| Opus 5 | $0.00008 | $0.00170 |
| Sonnet 5 | $0.00003 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
code_review 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 2d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 2d ago First seen · 66 lines · 16 tokens per session scan A bc121d97a605
code_review is a skill published in the GitHub repository XSpoonAi/spoon-bot (5 stars, last pushed 7d ago), with no licence file. It adds 16 tokens to every session and 340 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 2026-08-31.
Other skills, from other repositories
code-review
Automated code review with checklist and quality gates.
code-review
代码审查和质量分析技能。用于审查代码、发现潜在问题、提供改进建议。当用户请求代码审查、代码质量分析或最佳实践建议时使用。.
review-loop
Iterative code review — fix all P1/P2/P3 findings until clean.
code-review
Code review for issues, style consistency, best practices—use for full code evaluation; not for debugging specific errors or fixing individual style violations.
code-review
Reviews code changes using CodeRabbit AI. Use when user asks for code review, PR feedback, code quality checks, security issues, or wants autonomous fix-review cycles.
code-review
Reviews code snippets and provides improvement suggestions.