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/djblack1209-coder/openclaw-bot/gstack-reviewnpx skills add djblack1209-coder/OpenClaw-Bot --skill gstack-reviewgit clone --depth 1 https://github.com/djblack1209-coder/OpenClaw-BotWrote 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/djblack1209-coder/openclaw-bot/gstack-review)<a href="https://agentmods.dev/skills/djblack1209-coder/openclaw-bot/gstack-review"><img src="https://agentmods.dev/badge/skills/djblack1209-coder/openclaw-bot/gstack-review.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00811 |
| Opus 5 | $0.00017 | $0.00405 |
| Sonnet 5 | $0.00007 | $0.00162 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
gstack-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 3d 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
Gstack 多角色审查模式
参考 YC 总裁 Garry Tan 的 gstack 项目，提供多角色认知切换的开发审查能力。
可用模式
1. CEO 审查 (/review-ceo)
切换到创始人/产品思维:
- 不要照字面理解需求，问更重要的问题
- "这个功能的真正目的是什么？"
- "10 星版本是什么样的？"
- 找到需求背后隐藏的更大产品
输出: 产品方向建议、用户价值分析、竞品对比
2. 工程审查 (/review-eng)
切换到技术负责人思维:
- 架构设计、系统边界、数据流
- 状态转换、失败模式、边界情况
- 信任边界、测试覆盖
- 强制输出: 架构图、状态图、数据流图
输出: 技术方案文档 + 图表
3. 安全审查 (/review-security)
切换到偏执的资深工程师思维:
- N+1 查询、竞态条件、注入漏洞
- 信任边界、重试逻辑、不变量
- 测试通过但生产会爆的 bug
- 不要恭维，想象生产事故
输出: 按严重程度排序的问题列表
4. QA 审查 (/review-qa)
切换到 QA 工程师思维:
- 读取 git diff，识别受影响的页面和路由
- 用浏览器自动化测试每个受影响的页面
- 截图、检查控制台错误、验证表单
- 三个级别: Quick（30秒烟雾测试）、Standard、Exhaustive
输出: 健康分数 + 问题列表 + 截图
5. 发布 (/ship)
切换到发布工程师思维:
- 同步 main、运行测试、检查分支状态
- 更新 changelog/版本
- 推送、创建 PR
- 不要更多讨论，把飞机降落
输出: PR 链接
在 Telegram 中使用
严总: /review-ceo 我想给用户中心加一个批量筛选功能
Agent: 🎯 CEO 审查模式
"自动降价"不是真正的功能。真正的问题是: 如何让商品更快卖出去？
自动降价只是一个手段。10 星版本应该是:
1. 分析同类商品定价，给出最优初始价格
2. 监控浏览量/收藏量，智能调整曝光策略
3. 降价只是最后手段，先尝试优化标题/图片/描述
4. ...
要继续深入哪个方向？
与现有 skills 的关系
dev-todo-mode— 任务跟踪（执行层）superpowers-workflow— 完整开发流程（方法论层）gstack-review— 多角色审查（质量层）
三者互补: superpowers 定流程，gstack 保质量，dev-todo 跟进度。
触发条件
/review-ceo、/review-eng、/review-security、/review-qa、/ship- 严总 说 "帮我审查一下"、"这个方案怎么样"
- 开发任务的 review 阶段自动触发
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.
- 3d ago First seen · 94 lines · 35 tokens per session scan A 07439aca0487
gstack-review is a skill published in the GitHub repository djblack1209-coder/OpenClaw-Bot (5 stars, last pushed today), licensed Apache-2.0. It adds 35 tokens to every session and 811 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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