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/update-agent-infra/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/update-agent-infra)<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/update-agent-infra"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/update-agent-infra/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/update-agent-infra"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/update-agent-infra.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 109 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00029 | $0.01743 |
| Opus 5 | $0.00015 | $0.00872 |
| Sonnet 5 | $0.00006 | $0.00349 |
| Haiku 4.5 | $0.00003 | $0.00174 |
Grade A, and why
update-agent-infra 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 11d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
更新项目
执行约束
-
确定性步骤脚本化：managed / ejected 文件处理、注册表同步、配置更新 全部由
sync-templates.js脚本执行，不得逐文件手工处理。 脚本保证原子性和幂等性。 -
禁止委托子代理：阶段 B（merged 文件智能合并）必须在主会话中直接执行， 不得委托给子代理。子代理上下文有限，容易误判文件内容。
阶段 A：运行同步脚本（确定性）
执行以下命令，一次性处理所有确定性步骤：
node .agents/skills/update-agent-infra/scripts/sync-templates.js
脚本读取 .agents/.airc.json，并通过 npm 自动定位已安装的 @fitlab-ai/agent-infra/templates/ 目录。同步前会合并 templates.sources 中配置的外部模板源；相同文件以内置模板为准，多个外部源之间后者覆盖前者，冲突会写入报告。然后自动完成：
- 检测模板源版本
- 同步文件注册表（
defaults.json→.agents/.airc.json） - 处理所有 managed 文件（语言选择 → 排除 merged/ejected → 占位符渲染 → 写入；内建 guarded managed 文件使用来源基线三方比较）
- 处理 ejected 文件（仅首次安装时创建）
- 更新
.agents/.airc.json（templateVersion、文件列表）
脚本输出 JSON 到 stdout，解析并记录报告内容。
关键字段：
error：错误信息（如非空则停止并报告）templateVersion：模板源包的精确v前缀 SemVer（可包含 prerelease 或 build metadata）templateRoot：模板文件根目录绝对路径templateSources.conflicts：外部模板源冲突列表；报告中必须显式展示，说明哪些文件因内置模板或后续外部源获胜而被忽略managed.written/managed.created：已更新/新建的 managed 文件managed.protected：检测到用户单边修改或删除、因此保留本地状态的 guarded managed 文件managed.conflicts：来源未知、双边修改或平台切换时无法证明官方所有权的 guarded managed 冲突；必须逐项展示 target、reason 与三方哈希managed.removed：被删除的 managed 文件（包括模板迁移时移除的旧路径）managed.skippedPlatform：因归属其他平台而被跳过的 managed / merged 条目managed.skippedTUI：因对应内建 Agent Client 的agentClients[].enabled为false而被跳过的 managed / merged 条目（落在同一路径前缀下的 customTUI 命令文件会被保留）merged.pending：需要 AI 处理的 merged 文件列表- 每项包含
target（项目中的目标路径）和template（模板根目录下的相对路径）
- 每项包含
registryAdded：新增的文件注册条目configUpdated：.agents/.airc.json是否已更新
如果 managed.conflicts 非空，输出全部冲突并立即停止，不进入阶段 B；禁止覆盖冲突文件或推进其 files.managedBaselines。
阶段 B：处理 merged 文件（AI 智能合并）
根据报告中 merged.pending 列表，逐个文件处理。对于每个条目：
- 从
<templateRoot>/<template>读取模板文件 - 渲染占位符：将双花括号包裹的
project和org占位符替换为 .agents/.airc.json 中的实际值 - 读取本地当前文件（
<项目根>/<target>）
如果本地文件不存在（首次安装），直接写入渲染后的模板，跳过合并。
如果本地文件存在，执行以下合并算法：
B.1 以模板为基底
使用渲染后的新模板作为输出的基底。模板代表最佳实践，其结构和内容具有权威性。
What ships with it
2 files 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.
- 11d ago First seen · 144 lines · 29 tokens per session scan A e0ed9523ae72
update-agent-infra is a skill published in the GitHub repository fitlab-ai/agent-infra (83 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 1,743 once invoked, about $0.0001 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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sw-do
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done
Close an increment: ledger check, specweave verify, optional review, then specweave complete. Use when all tasks are done and saying "close increment", "we are done", or "finish up".
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