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/release/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/release)<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/release"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/release/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/release"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/release.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 | $0.00027 | $0.00607 |
| Opus 5.5 | $0.00011 | $0.00243 |
| Sonnet 5.5 | $0.00005 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00061 |
Grade A, and why
release 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 1mo 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
版本发布
在单次调用中准备发布、展示最新事实快照并请求一次远端发布授权。状态由外部事实重建；具体以 Git、代码托管平台与包发布渠道为准，不维护第二套 journal。
1. 验证输入与人工检查点
验证唯一参数 {version} 是规范 SemVer，并确认 entropy 人工检查点已满足。为此读取最新 entropy 报告；报告存在未处置高风险项时停止，不得替用户批准发布。
2. 准备并检查发布事实
agent-infra-internal release-workflow inspect {version}
必须保留并展示该命令的完整非空 stdout。blocked 表示外部事实不可确认，不得当作 missing。未 prepared 时执行 prepare 并重新 inspect；已准备或部分发布时复用当前事实。unknown 必须 blocked。
agent-infra-internal release-workflow prepare {version} --entropy-report {path}
必须展示 prepare 的 status、error 和 operations，其中包括关闭当前版本里程碑及创建后续规划里程碑的结果。failed 或 blocked 时停止，不得请求发布授权；只有 prepare 成功且重新 inspect 得到的最新快照才可进入下一步。
prepare 后必须重新 inspect；不得重复已满足动作。
3. 展示快照并确认
展示最新 snapshot 的完整 JSON，包括 facts 中的所有渠道状态。只有当前会话中针对该快照的无歧义明确肯定答复才授权发布；否定、调整、疑问、歧义或中断均停止，不得 publish。快照变化后重新展示并重新确认。
4. 发布并复核
agent-infra-internal release-workflow publish {version}
逐 ref 普通 push；部分成功可重放，禁止 force push。core 保留已成功事实并返回 degraded，重跑只补未满足事实。操作后重新 inspect；unknown 必须 blocked。发布后的 inspect 必须展示完整快照；如果平台 Release、npm、Homebrew 或 smoke 仍为 pending，明确标出未完成项，不得把 Git ref 推送成功表述为完整发布。
5. 输出事实摘要
完整发布后渲染携带版本的下一步，不显示内部 action，也不直接跳到 post-release：
agent-infra-internal agent-client next-steps \
--skill create-release-note \
--version {version}
输出完整快照和 helper 的非空 stdout。
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.
- 1mo ago Changed · +2 lines 38211c66e557
- 1mo ago First seen · 53 lines · 27 tokens per session scan A 3efc3cb47cdb
release is a skill published in the GitHub repository fitlab-ai/agent-infra (86 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 607 once invoked, about $0.0001 per session on Opus 5.5. 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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