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/modelengine-group/fit-framework/analyze-dependabotnpx skills add ModelEngine-Group/fit-framework --skill analyze-dependabotgit clone --depth 1 https://github.com/ModelEngine-Group/fit-frameworkWrote 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/modelengine-group/fit-framework/analyze-dependabot)<a href="https://agentmods.dev/skills/modelengine-group/fit-framework/analyze-dependabot"><img src="https://agentmods.dev/badge/skills/modelengine-group/fit-framework/analyze-dependabot.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 | $0.00049 | $0.00292 |
| Opus 5 | $0.00024 | $0.00146 |
| Sonnet 5 | $0.00010 | $0.00058 |
| Haiku 4.5 | $0.00005 | $0.00029 |
Grade A, and why
analyze-dependabot 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 4d 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
分析安全告警
分析指定的 Dependabot 安全告警，评估安全风险并创建修复任务。
执行步骤
-
获取安全告警信息:
gh api repos/{owner}/{repo}/dependabot/alerts/<alert-number>提取: severity, summary, package name, vulnerable version range, first patched version
-
创建任务目录和文件，基于 .agents/templates/task.md 模板。
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分析受影响范围:
- 搜索项目中使用该依赖的所有位置
- 分析是否直接使用了漏洞代码路径
- 识别依赖关系（直接依赖 vs 传递依赖）
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评估安全风险（可利用性、触发条件、影响程度）。
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输出分析文档到 analysis.md。
-
更新任务状态。
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提示下一步: plan-task 设计修复方案，或 close-dependabot 关闭告警。
注意: Critical/High 级别立即处理，Medium 计划处理，Low 可延后。
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.
- 4d ago First seen · 34 lines · 49 tokens per session scan A 356ddbb859c4
analyze-dependabot is a skill published in the GitHub repository ModelEngine-Group/fit-framework (2,116 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 292 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 2026-08-30.
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