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/complete-manual-validation/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/complete-manual-validation)<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/complete-manual-validation"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/complete-manual-validation/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/complete-manual-validation"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/complete-manual-validation.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 | $0.00072 | $0.01830 |
| Opus 5.5 | $0.00029 | $0.00732 |
| Sonnet 5.5 | $0.00014 | $0.00366 |
| Haiku 4.5 | $0.00007 | $0.00183 |
Grade A, and why
complete-manual-validation 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 6d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
完成人工验证
--agent取值见.agents/rules/task-management.md「合作者 token 规范」。
事务协调器统一追加 lifecycle 事件和 PR 摘要最终状态。维护者提供的验证说明和 PR 摘要留言就是人工验证依据;事务回执负责保证状态转换和恢复一致性。
行为边界 / 关键规则
持久化报告证据
生成验证完成报告时,先读取 .agents/rules/evidence-reporting.md。状态核对和同步结果记录命令、范围、结构化结果、实际结论和未覆盖部分;继续遵守人工验证的 basename-only 与 sanitized result 脱敏边界。
- 本技能用于收尾已有 PR 摘要评论中的人工校验状态,不创建并行的普通验证留言。
- 必须写入
manual-validation.md或manual-validation-r{N}.md,让后续 PR 摘要刷新可复用人工验证结果。 - 找不到
sync-pr摘要评论时失败,不创建部分摘要兜底;receipt、通过日志和 final summary 未全部提交前,远端只允许 pending/non-pass 状态。 - 生成会由 task 评论和 PR 摘要引用的人工验证 artifact Markdown 前,先读取
.agents/rules/sync-content-generation.md并遵循其中的生成端约束;人工验证 artifact 保留在本地,不发布为 Issue artifact 评论。 - 执行本技能后必须立即更新
task.md。
版本戳规则:创建或更新 task.md frontmatter 时,先读取 .agents/rules/version-stamp.md,并写入或刷新 agent_infra_version。
第 0 步:状态核对(执行前硬约束)
在加载 workflow / skill / rules 指令之后、做任何任务状态判断或用户可见结论之前,必须先执行状态核对。指令类文件读取不算对外动作或结论。
运行以下命令,并在本轮产物的 ## 状态核对 段记录任务/产物范围、关键结果和未覆盖部分;正常成功不粘贴完整目录清单或 task.md 尾部。失败、阻塞、身份不一致或争议时,附决定性原文行:
agent-infra-internal task-snapshot {task-id} --format text
任务上下文解析
入口可省略 task ref;显式 task scope 仅接受
--task <ref>或-t <ref>,不再解释位置 task ref。保留其余业务操作数后调用agent-infra-internal task-context resolve {task-scope};{task-scope}为空或 task flag 之一。只读取结构化结果的taskId,后续把{task-id}绑定为完整TASK-YYYYMMDD-HHMMSS。解析失败时透传非零退出码,不自行扫描任务。
解析任务引用,并确认任务位于本技能支持的状态或目录且存在
task.md;无法定位时按未找到任务处理并停止。
执行步骤
1. 解析入参
输入格式:
complete-manual-validation [--task <ref> | -t <ref>] [{pr-ref}] {verification-summary}
- task scope 可省略;显式 scope 只接受
--task <ref>或-t <ref>。 {pr-ref}可选,支持#NN、NN或完整 PR URL。{verification-summary}必填。若缺失,立即停止并提示补充验证说明;不写产物、不更新 PR。
2. 验证前置条件
检查:
<task-workspace>/active/{task-id}/task.md- 有效 PR:优先使用显式
{pr-ref},否则读取 task.md frontmatter 的 verifiedpr_delivery_fact.identity.number
如果任务不存在、验证说明缺失,或无法解析有效 PR,立即停止。
3. 解析产物上下文
运行 agent-infra-internal task-artifact {task-id} inspect --family manual-validation。仅当结果为 ready 时继续;从 next.round / next.name 取得本轮 round 与 {manual-validation-artifact}。不得自行扫描轮次或拼装文件名。事务协调器负责 started 事件。
What ships with it
3 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.
- 6d ago Changed e05ba610c6c8
- 23d ago Changed · -1 lines 524b690072c8
- 24d ago Changed 7ea726ca3f45
- 1mo ago Changed 8b6a5a8b6279
- 1mo ago Changed 17a8fd0d93aa
- 1mo ago Changed 167e46fd0e00
- 1mo ago Changed · +12 lines 67ceb7228b19
- 1mo ago Changed · +4 lines d681268311e3
- 1mo ago Changed · +2 lines e274040f6907
- 1mo ago First seen · 123 lines · 72 tokens per session scan A 05245b4eb2f9
complete-manual-validation is a skill published in the GitHub repository fitlab-ai/agent-infra (86 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 1,830 once invoked, about $0.0003 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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