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 halexzd686-cloud/SoloFlow --skill code-reviewergit clone --depth 1 https://github.com/halexzd686-cloud/SoloFlowWrote 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/halexzd686-cloud/soloflow/code-reviewer)<a href="https://agentmods.dev/skills/halexzd686-cloud/soloflow/code-reviewer"><img src="https://agentmods.dev/badge/skills/halexzd686-cloud/soloflow/code-reviewer/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/halexzd686-cloud/soloflow/code-reviewer"><img src="https://agentmods.dev/badge/skills/halexzd686-cloud/soloflow/code-reviewer.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 | $0.00024 | $0.00711 |
| Opus 5.5 | $0.00010 | $0.00284 |
| Sonnet 5.5 | $0.00005 | $0.00142 |
| Haiku 4.5 | $0.00002 | $0.00071 |
Grade A, and why
code-reviewer 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
代码审查 Skill
审查维度
1. 正确性 (Critical)
- 逻辑是否正确？边界条件是否处理？
- 是否有 off-by-one 错误？空值检查？
- 异常处理是否完备？
2. 安全性 (Critical)
- 是否有注入风险（SQL、命令、XSS）？
- 敏感信息是否暴露（密钥、密码、token）？
- 权限检查是否完备？
3. 性能 (Suggestion)
- 是否有不必要的循环或重复计算？
- 数据库查询是否有 N+1 问题？
- 内存使用是否合理？
4. 可维护性 (Suggestion)
- 命名是否清晰表达意图？
- 函数是否过长或做了太多事？
- 是否有重复代码可以提取？
输出格式
## 代码审查报告
### Critical（必须修改）
1. [问题描述]
- 风险: [具体风险]
- 修复: [代码示例]
### Suggestion（建议优化）
1. [优化建议]
- 原因: [为什么改]
- 改进: [代码示例]
### 总结
- Critical: N 项
- Suggestion: M 项
- 总体评价: [一句话]
失败模式
- 如果 diff 太大（超过 500 行），要求拆分成更小的 PR
- 如果缺少上下文（不知道这段代码的业务目的），先说明假设
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 · 82 lines · 24 tokens per session scan A 20d658cfb65b
code-reviewer is a skill published in the GitHub repository halexzd686-cloud/SoloFlow (0 stars, last pushed 3d ago), licensed MIT. It adds 24 tokens to every session and 711 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.
Other skills, from other repositories
dev-loop
Research → Execute → Dual-Review Loop (Code Quality + Issue Resolution) bis beide Reviews bestanden.
code-review
Review code for quality, maintainability, and correctness.
stage-coach
Consume CocoSentinel per-stage external coach requests and produce stage quality scores.
code-review
Reviewing code for defects: diff-first reading, severity classification, evidence over inference, finding caps, and terminal verdicts. Use when reviewing a diff, PR, or patch, or auditing someone else's work.
responding-to-review
Answering review findings: verify each claim before implementing, no performative agreement, per-item fix/reject/defer with evidence, one batched remediation round. Use when responding to review or remediation rounds.
coding
Use when five specialized coding agents (linter, perf, refactor, security, test) that enforce quality gates across the development lifecycle. From lint enforcement through performance profiling, refactoring, security auditing, and test coverage. Use when working with coding agents.