Agent skill

Afk Team Workflow

by ArcReel in ArcReel/ArcReel

把一个 Spec 的全部子 issue(或一组显式 issue)组建团队无人值守跑到全部合并或明确暂停. An agent skill from ArcReel/ArcReel.

AGPL-3.0Auto-check passedMedia & Creative

Install Afk Team Workflow

skills CLI
$ npx skills add ArcReel/ArcReel --skill afk-team-workflow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ArcReel/ArcReel afk-team-workflow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ArcReel/ArcReel.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/afk-team-workflow .claude/skills/afk-team-workflow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
afk-team-workflow
GitHub stars
5.4k
Token cost
~794 tokens
SKILL.md length
296 words
Files
13 (incl. scripts, references)
Skills in repo
18
Repo updated
First seen
Licence
AGPL-3.0

At a glance

把一个 Spec 的全部子 issue(或一组显式 issue)组建团队无人值守跑到全部合并或明确暂停. An agent skill from ArcReel/ArcReel.

  • Works in 4 steps: 计划批次 → 执行 task graph → 暂停边界 → …
  • Tasks that involve AI video generation
  • SKILL.md covers 1. 计划批次, 2. 执行 task graph, 3. 暂停边界 and 4. 收尾
  • Runs Shell scripts from its folder

What it does

Afk Team Workflow is an agent skill from ArcReel/ArcReel. 把一个 Spec 的全部子 issue(或一组显式 issue)组建团队无人值守跑到全部合并或明确暂停。

Its SKILL.md is about 790 tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/handoff.md` and `references/herdr-teammate.md`).

It sits in Media & Creative, covering AI video generation. The repository describes itself as: AI Agent 驱动的开源可自部署视频工作台:将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿,支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video production. The licence is AGPL-3.0.

When your agent uses it

  • Tasks that involve AI video generation

Example prompts

  • “/afk-team-workflow”

Requirements

  • A Bash shell

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 计划批次
  2. 执行 task graph
  3. 暂停边界
  4. 收尾

What it can do on your machine

Read from SKILL.md and the folder at commit 08ab3b3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Shell), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Afk Team Workflow loads about 794 tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 18 tokens; SKILL.md has 296 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~18
When it runs · the whole SKILL.md, loaded when a task matches
~794
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from ArcReel/ArcReel at commit 08ab3b3, republished under its AGPL-3.0 licence (© ArcReel). 296 words, ~794 tokens.

Download SKILL.mdSave it as .claude/skills/afk-team-workflow/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.
name
afk-team-workflow
description
把一个 Spec 的全部子 issue(或一组显式 issue)组建团队无人值守跑到全部合并或明确暂停。
disable-model-invocation
true

AFK 团队执行流程

你是 team-lead:把一个 Spec 的子 issue 或一组显式 issue 无人值守推进到全部合并或明确暂停。你负责计划、调度、集成与裁决,不写代码。开工后持续运行到批次终态;中途不把调度问题升级给用户,真实业务取舍例外。

1. 计划批次

  1. 生成唯一 batch-id:Spec 批次用 spec-<N>-<UTC YYYYMMDD-HHMMSS>-<6 位随机十六进制>,显式 issue 批次用同格式的简短 slug。若 .afk/ 已有同一范围且未 closed 的账本,暂停并让用户选择接管或重开;两者均先读 recovery.md。
  2. 按批次运行 scripts/batch-poll.sh --repo-root <repo-root> --spec <N> 或 --issues <N,...>,然后逐个通读 issue 正文与评论,得到真实的验收边界、canonical dependency graph、triage 与认领状态。只有 OPEN issue 可进入 stage 与 PR Closes 清单;其中 ready-for-agent、无他人认领且 blockers 已完成的 issue 进入 frontier,无标签时按语义裁决。ready-for-human 及其被阻塞下游不进入 frontier。
  3. 将依赖图划成最少的、可独立审查和合入的交付 stage;小批次保持单 stage。按 model-selection.md 为各角色选模型与 effort。
  4. 向用户展示 stage、依赖、模型理由、跳过项及下游影响,并一次性请求:全部 stage PR 的 rebase merge 授权;最终清尾轮中对符合范围的真缺陷自行立 issue 的授权。未授权的清尾候选只转呈。
  5. 用 scripts/ledger.sh 创建薄账本,记录 scope、计划裁决与授权;账本只记 Git / GitHub 无法重推的事实。

2. 执行 task graph

组建团队并按 spawn-prompts.md 委派。HERDR_ENV=1 时先读 herdr-teammate.md;否则使用当前 harness 的原生团队能力。

严格串行执行各 stage:

  1. 从最新 origin/main 创建 afk/<batch-id>/stage-<K> 与专属 worktree,并 push stage branch。
  2. 将依赖已满足且改动面可安全并发的 frontier 认领并委派。每个 issue 使用独立 worktree,implementer 按 implementer.md 交付一个 issue commit。
  3. team-lead 在 stage worktree 串行 cherry-pick 交付的 issue commits 并 push。冲突时 abort,由原 implementer 基于最新 stage branch 解决、验证并重新交付。带 Refs #<N> 的 commit 出现在远程 stage branch 后,该 issue 才算完成并可解锁新 frontier。
  4. 最后一个 stage 先聚合全批 handoff 的 follow-up:只处理经验证存在、属于批次范围且无需业务取舍的真缺陷;清尾 issue 创建后,Spec 批次按 issue-tracker 约定 挂接父 Spec,并沿用同一接力;其余转呈。
  5. 全部 issues 集成后,由未参与本 stage 实现的 stage-reviewer 按 stage-reviewer.md 审查整个 stage diff 并交付 green HEAD。随后创建 draft PR,用 Closes #<N> 覆盖本 stage issues;Spec 批次另用 Refs #<Spec> 引用 Spec,不自动关闭它。启动 review-looper 收敛 AI 审查与 commit history。agent 回报达标 HEAD 后,核对其等于当前 headRefOid 且 mergeable=MERGEABLE,以该 headRefOid 为 expected-head 执行 rebase merge;不匹配则重入审查循环。下一 stage 从最新 origin/main 开始。

3. 暂停边界

实现或审查暴露真实业务取舍,或发现 Spec 要求没有 issue 覆盖时,暂停受影响事项及其下游并询问用户。quiesce first:停止受影响 agents 并废弃未集成 handoff;stage-reviewer 或 review-looper 运行时,先停止它并核对 worktree、branch、remote HEAD 与 handoff。然后为已有 issue 移除 ready-for-agent、添加 ready-for-human,记录原因,并将暂停范围移出当前 stage。其余 frontier 继续执行。用户决定继续时:已有 issue 恢复标签;Spec gap 先创建并挂为 sub-issue,再重新编排。决定保留暂停时,仅当相关 commit 已进入 stage branch 才重建 stage,排除该 issue 及其下游;已有 PR 同步更新 Closes 清单。重建后重新运行集成审查与审查循环。

可吸收的运行故障、reviewer 重复噪声与无需业务选择的技术裁决由 team-lead 处理并记账;阻断 green HEAD 且无法自行恢复的故障按上文暂停。review-looper 硬停汇报后由 team-lead 裁决未决事项并交给新 looper 接力,给出延长的 rounds,裁定驳回的意见随委派交其回复;涉业务取舍一律转呈用户。

4. 收尾

在 Spec issue 发布按已合并 stage 组织的人工 QA 清单,列出 PR、用户可感知的验收路径、暂停/跳过项与转呈事项;显式 issue 批次则并入收尾汇报。移除已认领 issue 的 assignee,清理本批的 agents、worktrees、本地 branches 与 Herdr workspace,最后 append closed 账本行。

收尾汇报中给出 batch-id、账本与 handoff 路径,并保留这些批次记录。用户此后对转呈事项的裁决仍以 decision 追加到本批账本。

© ArcReel, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 12 other files (scripts, references) in .agents/skills/afk-team-workflow of ArcReel/ArcReel.

  • SKILL.md
  • agents/openai.yaml
  • references/handoff.md
  • references/herdr-teammate.md
  • references/implementer.md
  • references/model-selection.md
  • references/recovery.md
  • references/review-looper.md
  • references/spawn-prompts.md
  • references/stage-reviewer.md
  • scripts/batch-poll.sh
  • scripts/ledger.sh
  • scripts/repo-context.sh

Open the folder on GitHubat commit 08ab3b3

Compare with similar skills

Afk Team Workflow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Afk Team Workflow compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Afk Team Workflow this skillArcReel/ArcReel5.4k—~794Automated safety check: PassAGPL-3.0
Video Generationbytedance/deer-flow84k3 repos~1.4kAutomated safety check: PassMIT
Video Cover Imageitwanger/toBeBetterJavaer18k—~3.3kAutomated safety check: PassNone
Seedancesongguoxs/seedance-prompt-skill2.9k1 repos~2.5kAutomated safety check: PassNone
HyperFrames Video Entry Pointheygen-com/hyperframes59k3 repos~5.2kAutomated safety check: PassApache-2.0
Lanshu Create AI Presenter Videocclank/lanshu-create-ai-presenter-video2.6k—~3.6kAutomated safety check: PassMIT

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Questions about Afk Team Workflow

What does Afk Team Workflow do?

把一个 Spec 的全部子 issue(或一组显式 issue)组建团队无人值守跑到全部合并或明确暂停. An agent skill from ArcReel/ArcReel. Afk Team Workflow is an agent skill from ArcReel/ArcReel.

When should I use Afk Team Workflow?

Afk Team Workflow fits situations like: tasks that involve AI video generation.

How do I install Afk Team Workflow in Claude Code?

Run `npx skills add ArcReel/ArcReel --skill afk-team-workflow -a claude-code`. Or copy the skill folder (.agents/skills/afk-team-workflow in ArcReel/ArcReel) into .claude/skills/afk-team-workflow in your project. Claude Code loads it when a task matches its description.

How do I install Afk Team Workflow in Codex?

Run `npx skills add ArcReel/ArcReel --skill afk-team-workflow -a codex`. Or copy the skill folder (.agents/skills/afk-team-workflow in ArcReel/ArcReel) into .agents/skills/afk-team-workflow in your project. Codex loads it when a task matches its description.

Can I use Afk Team Workflow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ArcReel/ArcReel --skill afk-team-workflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/afk-team-workflow, .gemini/skills/afk-team-workflow, .github/skills/afk-team-workflow and .opencode/skills/afk-team-workflow in your project.

What does Afk Team Workflow need to run?

Going by SKILL.md and its folder, Afk Team Workflow needs a shell for the scripts in its folder. Our summary lists: A Bash shell.

Does Afk Team Workflow access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Afk Team Workflow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Afk Team Workflow use?

Afk Team Workflow is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Afk Team Workflow use?

About 794 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3k tokens, read only when the agent opens those files.

What are the alternatives to Afk Team Workflow?

Skills that share tags, products or a category with Afk Team Workflow: Video Generation (bytedance/deer-flow, 84k stars), Video Cover Image (itwanger/toBeBetterJavaer, 18k stars), Seedance (songguoxs/seedance-prompt-skill, 2.9k stars) and HyperFrames Video Entry Point (heygen-com/hyperframes, 59k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Afk Team Workflow?

ArcReel (a GitHub organization) maintains it in ArcReel/ArcReel, which has 5,399 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on October 9, 2026.

Source: ArcReel/ArcReel on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.