agent-infra: Skill for Claude Code

.agents/skills/complete-task/SKILL.md

complete-task is a skill for Claude Code, Codex from fitlab-ai/agent-infra. It costs 43 tokens per session (4,625 once invoked), scanned A, original, MIT.

A task-closing tool that marks a work item as finished and archives its task records after the work has been checked.

In plain words
What is it for?
Use it to resolve a task reference, verify its state, update task metadata, and move the completed task into its archive.
Why use it?
It provides a controlled way to finish a task without accidentally archiving work that still has unfinished steps.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is fitlab-ai/agent-infra's own configuration. It tells Claude Code and Codex how to work on agent-infra itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything agent-infra configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/fitlab-ai/agent-infra/main/.agents/skills/complete-task/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/fitlab-ai/agent-infra

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for complete-task

README.md
[![agentmods](https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/complete-task/github.svg)](https://agentmods.dev/skills/fitlab-ai/agent-infra/complete-task)
Your own site
<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/complete-task"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/complete-task/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.

agentmods 80×15 button for complete-task

Your own site · 80×15
<a href="https://agentmods.dev/skills/fitlab-ai/agent-infra/complete-task"><img src="https://agentmods.dev/badge/skills/fitlab-ai/agent-infra/complete-task.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,625 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.04625
Opus 5.5 $0.00017 $0.01850
Sonnet 5.5 $0.00009 $0.00925
Haiku 4.5 $0.00004 $0.00462

Measured 3d ago against content hash 5ff4dd573940, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

complete-task 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.

.agents/skills/complete-task/SKILL.md · 241 lines

How it starts

The opening of the file, as written. The whole thing — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.

完成任务

--agent 取值见 .agents/rules/task-management.md「合作者 token 规范」。

宿主 finalization 使用 receipt v4(不可变 receiptId、单调 revision、摘要暂存和 canonical warnings)。生命周期/身份/required PR 等硬失败返回 result: failed|blocked;生命周期完成后,只重试 receipt 指出的 pending 外围步骤或 open backfill warning。逐检查 verification warning 以 observed target 为单位转换:新观察替代旧 code 时保留旧行 resolved 历史,未观察的 target 不变。

行为边界 / 关键规则

持久化报告证据

生成收尾报告或同步内容时,先读取 .agents/rules/evidence-reporting.md。成功检查记录命令、范围、状态/结构化结果、实际结果和未覆盖部分;失败、阻塞或争议保留复现入口、准确位置和决定性摘录。

  • 本命令由宿主更新任务元数据并原子移动任务目录
  • 入口接受可选 --external-pr <N>;仅用于外部交付候选歧义时的显式选择,不绕过身份或平台门禁

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

状态核对完成前,禁止任何关于外部状态的断言(例如“代码没变”“测试已通过”“没有其他引用”),包括思考阶段。本门禁只提供结构下限;逐条证据配对和真实性仍需按报告模板与审查要求核对。

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。

步骤开始:本地生命周期边界

正常完成路径在 active 阶段完成业务更新、平台同步和预完成门禁后,才由步骤 6 的单次 finalization intent 按固定顺序原子推进生命周期、终态 task 评论和完成校验;不得提前手工写入这些机械状态。已归档任务只允许进入 finalization-retry 场景,不回迁目录或重新执行 lifecycle。

执行步骤

1. 验证任务存在

检查任务是否存在于 <task-workspace>/active/{task-id}/。

注意:{task-id} 格式为 TASK-{yyyyMMdd-HHmmss},例如 TASK-20260306-143022

如果在 active/ 中未找到,检查 blocked/ 和 completed/:

  • 如果在 completed/ 且 task.md 存在匹配的 Complete Task Activity Log:进入场景 B finalization-retry,跳过步骤 2-6,直接执行步骤 7
  • 如果在 completed/ 但缺少匹配日志:告知用户任务已完成但终态身份不完整并停止,不手工修补
  • 如果在 blocked/:告知用户任务被阻塞;建议先解除阻塞

场景 A 为 active 任务的正常完成路径;场景 B finalization-retry 重试允许的 artifact 回填、终态 task 评论、完成校验和摘要封口,不回迁生命周期。

Read the full file on GitHub · 241 lines

Files

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.

Changes

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.

  1. 3d ago Changed 5ff4dd573940
  2. 5d ago Changed · -15 lines 6b7610874f70
  3. 6d ago Changed 3f4e0918cbc2
  4. 9d ago Changed 9f59bdd746e5
  5. 14d ago Changed · +8 lines · -3 tokens per session 36ab3d3fa622
  6. 17d ago Changed · -18 lines 8a3020bbbf59
  7. 23d ago Changed · -3 lines b8a4f288013e
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  9. 28d ago Changed · +2 lines 5d7d118c93d7
  10. 1mo ago First seen · 266 lines · 46 tokens per session scan A d2da7b159aed

Subscribe to this mod's changes

complete-task is a skill published in the GitHub repository fitlab-ai/agent-infra (86 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 4,625 once invoked, about $0.0002 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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