Borrowing it
Nothing to install: this file belongs to fitlab-ai/agent-infra. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fitlab-ai/agent-infra/main/.agents/skills/import-dependabot/SKILL.mdgit clone --depth 1 https://github.com/fitlab-ai/agent-infraWrote 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/fitlab-ai/agent-infra/import-dependabot)<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/import-dependabot"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/import-dependabot/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/fitlab-ai/agent-infra/import-dependabot"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/import-dependabot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.01552 |
| Opus 5 | $0.00020 | $0.00776 |
| Sonnet 5 | $0.00008 | $0.00310 |
| Haiku 4.5 | $0.00004 | $0.00155 |
Grade A, and why
import-dependabot scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
导入 Dependabot 安全告警
导入指定的 Dependabot 安全告警并创建修复任务。
行为边界 / 关键规则
- 本技能仅负责导入告警并创建任务骨架 —— 不直接修改业务代码或关闭告警
- 不要自动提交。绝不自动执行
git commit或git add - 执行本技能后,你必须立即更新 task.md 中的任务状态
任务入参短号别名
如果
{task-id}入参匹配^[#]?[0-9]+$(裸数字或带#前缀),先读取.agents/rules/task-short-id.md的「SKILL 入参解析」段执行解析;后续命令视{task-id}为解析后的全长TASK-YYYYMMDD-HHMMSS形式。
步骤开始:记录开始时间
本技能会创建 task.md,开始时尚无文件可写。先在内存记录开始时间 started_at(date "+%Y-%m-%d %H:%M:%S%z" | sed 's/\([+-][0-9][0-9]\)\([0-9][0-9]\)$/\1:\2/');在最后写活动日志时一次性补两条——started 行用 started_at、done 行用完成时间,二者同基名(started 行 action 加 [started] 后缀、note 用 started):
- {started_at} — **Import Dependabot [started]** by {agent} — started
- {done_at} — **Import Dependabot** by {agent} — {完成说明}
ai task log 会按基名把两条配对成一行(进行中 → 已完成)。约定见 .agents/rules/task-management.md 的「Activity Log started / done 双标记约定」。
执行流程
1. 获取告警信息
执行前先读取 .agents/rules/security-alerts.md,然后运行 agent-infra-internal platform-security read --kind dependabot --number {alert-number},解析其 JSON 结果获取告警详情。
提取关键信息:
number:告警编号state:状态(open/dismissed/fixed)security_advisory:安全公告详情(ghsa_id、cve_id、severity、summary、description)dependency:受影响的依赖(包名、生态系统、清单路径)security_vulnerability:受影响版本范围、首个修复版本
2. 创建任务目录和文件
检查 .agents/workspace/active/ 中是否已存在该告警的任务。
- 如果找到,默认复用现有任务,不询问用户;在最终告知中明确「已复用现有任务
{task-id},未重新导入」。如需重新导入,需先归档/删除已有任务 - 如果未找到,创建新任务
创建目录:.agents/workspace/active/TASK-{yyyyMMdd-HHmmss}/
任务元数据需包含:
id: TASK-{yyyyMMdd-HHmmss}
security_alert_number: <alert-number>
cve_id: <CVE-ID>
ghsa_id: <GHSA-ID>
3. 更新任务状态
获取当前时间:
date "+%Y-%m-%d %H:%M:%S%z" | sed 's/\([+-][0-9][0-9]\)\([0-9][0-9]\)$/\1:\2/'
更新 task.md:current_step -> requirement-analysis。
- 追加到
## Activity Log(不要覆盖之前的记录):- {YYYY-MM-DD HH:mm:ss±HH:MM} — **Import Dependabot** by {agent} — Dependabot alert #{alert-number} imported
4. 完成校验
先调用短号分配(保证注册表 entry 已分配;完成校验阶段会读取):
node .agents/scripts/task-short-id.js alloc "$task_id"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed 0f7ef6c9cde0
- 7d ago Changed 80b366b7817f
- 11d ago First seen · 141 lines · 41 tokens per session scan A e758894a61e5
import-dependabot is a skill published in the GitHub repository fitlab-ai/agent-infra (83 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 1,552 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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