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/chentao326/vibe-code/vibe-learn-fromnpx skills add chentao326/vibe-code --skill vibe-learn-fromgit clone --depth 1 https://github.com/chentao326/vibe-codeWrote 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/chentao326/vibe-code/vibe-learn-from)<a href="https://agentmods.dev/skills/chentao326/vibe-code/vibe-learn-from"><img src="https://agentmods.dev/badge/skills/chentao326/vibe-code/vibe-learn-from.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 5.1 | $0.00054 | $0.00594 |
| Opus 5 | $0.00027 | $0.00297 |
| Sonnet 5 | $0.00011 | $0.00119 |
| Haiku 4.5 | $0.00005 | $0.00059 |
Grade A, and why
vibe-learn-from 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 5d 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
vibe-learn-from — 对标项目学习
从优秀开源项目提取代码质量标准，写入 benchmark.md。
Workflow
Phase 1: 获取项目
- GitHub URL → clone 到临时目录或直接通过 GitHub API 分析
- 本地路径 → 直接分析
Phase 2: 分析代码质量特征
逐项分析并记录：
目录结构规律：
- 模块如何组织？
- 测试文件放哪里？
- 配置文件管理方式？
测试覆盖模式：
- 测试文件命名（
*.test.ts/*_test.py/test_*.go）？ - 测试覆盖率风格（单元/集成/E2E 比例）？
- Mock/Fixture 管理方式？
命名规范：
- 函数/变量命名风格？
- 文件命名约定？
- 类型/接口命名？
错误处理模式：
- 如何处理错误？（throw / Result type / error return）
- 边界情况处理方式？
- 日志/监控方式？
API 设计风格：
- 函数签名偏好（参数数量/类型/返回值）？
- 模块间接口设计？
- 配置 vs 约定？
Phase 3: 写入 benchmark.md
# 对标项目参考
**项目**: react
**仓库**: https://github.com/facebook/react
**导入日期**: 2026-05-24
## 代码质量特征
### 目录结构规律
- packages/ 下每个包独立
### 测试覆盖模式
- __tests__/ 目录 + *-test.js 文件
...
Phase 4: 关联到 rubric
分析完后提示：
✅ 对标分析完成。
你当前的 rubric 是 v0 等权起步。以下 feature 可能值得在你的 rubric 里增加权重或细化：
- 测试覆盖：对标项目有严格的测试规范，建议关注 TE 维度
- 错误处理：对标项目的错误边界设计值得学习，当前 rubric 无对应维度
建议：跑 5 个任务后，对比你的数据和对标标准，再决定是否 bump。
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.
- 5d ago First seen · 84 lines · 54 tokens per session scan A 949c8089ef17
vibe-learn-from is a skill published in the GitHub repository chentao326/vibe-code (2 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 594 once invoked, about $0.0003 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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