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kanban-video-orchestrator

将视频需求整理成制作计划,按风格组建专业智能体团队并配置制作环境。通过Hermes看板分配任务、查看进度,协助应对停滞或失败的任务。

原文查看原文说明

Plan and run multi-agent video production pipelines.

集成工具YouTube

实测评分 未实测

查看安装方法

适用场景

  • 管理简短产品介绍视频的制作
  • 让专业智能体分工制作剧情视频
  • 规划音乐视频的画面与音频
  • 查看制作进度并应对停滞任务

中文介绍

功能

将视频需求整理成制作计划,并建立由专业智能体分工完成的工作流程。先确认时长、画面比例、发布平台和风格,再把场景安排、音频及交付格式写入brief.md。根据需要选择角色与工具,配置Hermes配置文件、共享工作文件夹和任务看板,随后启动制作。还可查看进度,为停滞或失败的任务提供反馈并协助重新执行。

适用场景

适合产品介绍、剧情短片、音乐视频等需要多人分担画面与音频的制作。可按风格组建团队,管理任务交接与审核环节。

使用示例

  • “请让专业智能体分工制作一段用于YouTube的30秒产品介绍视频。”
  • “请设计短片结构和制作团队,并查看制作进度。”

注意事项

需要使用Hermes的配置文件和看板功能。本技能本身不生成视频画面,实际制作需要符合内容的其他技能或工具。使用外部API时,须提前准备相应密钥。制作计划须由用户确认后再设计团队。不适合简单的视频转换或单个技能即可完成的工作。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

文档检查

AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。

安全性发送数据、删除文件、执行命令等是否有说明
B部分不足要求确认制作计划,但未明确在setup.sh更改配置前进行确认。
安装难易度所需工具和 API 密钥是否少且有说明
B部分不足需要Hermes及制作工具,但未提供这些工具的安装步骤。

不计入评分。 由 AI(OpenAI Codex)于 2026年10月19日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

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包含的文件(12)

  • SKILL.md9.5 KB
  • assets/brief.md.tmpl2.1 KB
  • assets/setup.sh.tmpl8.2 KB
  • assets/soul.md.tmpl631 B
  • references/examples.md10.1 KB
  • references/intake.md7.8 KB
  • references/kanban-setup.md11.1 KB
  • references/monitoring.md7.3 KB
  • references/role-archetypes.md12.4 KB
  • references/tool-matrix.md13.4 KB
  • scripts/bootstrap_pipeline.py18.2 KB
  • scripts/monitor.py6.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Kanban Video Orchestrator

Wrap any video request — from a 15-second product teaser to a 5-minute narrative short to a music video to an ASCII loop — in a Hermes Kanban pipeline that decomposes the work to specialized agent profiles.

This skill does not render anything itself. It is a meta-pipeline that:

  1. Scopes the request through targeted discovery
  2. Designs an appropriate team (which roles, which tools per role) based on the style
  3. Generates a setup script that creates Hermes profiles, project workspace, and the initial kanban task
  4. Hands off to the director profile, which decomposes via the kanban
  5. Monitors execution, helps intervene when tasks stall or fail

The actual rendering happens inside the kanban once it's running, via whichever existing skills + tools fit the scenes — ascii-video, manim-video, p5js, comfyui, touchdesigner-mcp, songwriting-and-ai-music, heartmula, external APIs, or plain Python with PIL + ffmpeg.

When NOT to use this skill

  • The video is one continuous procedural project that needs no specialists. Just write the code directly.
  • The user wants a quick one-shot conversion (e.g. "convert this mp4 to a GIF") — use ffmpeg directly.
  • The output is a static image, GIF, or audio-only artifact — use the matching specific skill (ascii-art, gifs, meme-generation, songwriting-and-ai-music).
  • The work fits a single existing skill cleanly (e.g. a pure ASCII video — just use ascii-video).

Workflow

DISCOVER  →  BRIEF  →  TEAM DESIGN  →  SETUP  →  EXECUTE  →  MONITOR

Step 1 — Discover (ask the right questions)

The discovery process is adaptive: ask only what is actually needed. Always start with three questions to identify the broad shape:

  • What is the video? (one-sentence brief)
  • How long? (5-30s teaser / 30-90s short / 90s-3min explainer / 3-10min film / longer)
  • What aspect ratio + target platform? (1:1 / 9:16 / 16:9; X, IG, YouTube, internal, etc.)

From the answer, classify the style category. The style determines which follow-up questions to ask. Do not ask all questions at once. Ask 2-4 at a time, listen, then proceed. Make reasonable assumptions whenever the user implies an answer.

For complete intake patterns and per-style question banks, see references/intake.md.

Step 2 — Brief

Once enough is known, produce a structured brief.md using the template in assets/brief.md.tmpl. Stages:

  1. Concept — the one-sentence pitch + emotional north star
  2. Scope — duration, aspect, platform, deadline
  3. Style — visual references, brand constraints, tone
  4. Scenes — beat-by-beat breakdown (durations, content, target tool)
  5. Audio — narration / music / SFX / silent (per scene if needed)
  6. Deliverables — file format, resolution, optional alternates (vertical cut, GIF, etc.)

Show the brief to the user for confirmation before designing the team. The brief is the contract — every downstream task references it.

Step 3 — Team design

Pick role archetypes from the library that fit this video. Compose, don't clone. Most videos need 4-7 profiles. The director is always present; the rest are picked by what the brief actually requires.

For the role library and per-style team compositions, see references/role-archetypes.md.

For mapping role → which Hermes skills + toolsets it loads, see references/tool-matrix.md.

Step 4 — Setup

Generate a setup script (setup.sh) and run it. The script:

  1. Creates the project workspace (~/projects/video-pipeline/<slug>/)
  2. Copies any provided assets into taste/, audio/, assets/
  3. Creates each Hermes profile via hermes profile create --clone
  4. Writes per-profile SOUL.md (personality + role definition)
  5. Configures profile YAML (toolsets, always_load skills, cwd)
  6. Writes brief.md, TEAM.md, and taste/ content
  7. Fires the initial hermes kanban create task assigned to the director

Use scripts/bootstrap_pipeline.py to generate setup.sh from a brief + team-design JSON. See references/kanban-setup.md for the setup script structure, profile config patterns, and the critical "shared workspace" rule.

Step 5 — Execute

Run setup.sh. Then provide the user with monitoring commands:

hermes kanban watch --tenant <project-tenant>     # live events
hermes kanban list  --tenant <project-tenant>     # board snapshot
hermes dashboard                                   # visual board UI

The director profile takes over from here, decomposing the work and routing tasks to specialist profiles via the kanban toolset.

Step 6 — Monitor and intervene

Stay engaged — the kanban runs autonomously but a stuck task or bad output needs human (or AI) judgment.

Monitoring patterns: poll kanban list periodically, inspect any RUNNING task that exceeds its expected duration with kanban show <id>, and check heartbeats. When a worker's output fails review, the standard interventions are:

  1. Comment on the worker's task with specific feedback (kanban_comment)
  2. Create a re-run task with the original as parent
  3. Adjust the brief's scope and let the director re-decompose

For diagnostic patterns, intervention recipes, and the "task is stuck" playbook, see references/monitoring.md.

Reference: worked examples

Six concrete pipelines covering very different video styles — narrative film, product/marketing, music video, math/algorithm explainer, ASCII video, real-time installation — showing how the same workflow yields very different teams and task graphs. See references/examples.md.

Critical rules

  1. Discovery before action. Never start generating a brief or team without asking at least the three baseline questions. A bad brief cascades through the entire pipeline.

  2. Match the team to the video. Don't reuse the same 4-profile setup for every job. A music video that doesn't have a beat-analysis profile will misfire. A narrative film that doesn't have a writer profile will produce incoherent scenes. See references/role-archetypes.md.

  3. One workspace per project. All profiles for a given video share the same dir: workspace. Tasks pass artifacts via shared filesystem and structured handoffs. Every kanban_create call passes workspace_kind="dir" + workspace_path="<absolute project path>".

  4. Tenant every project. Use a project-specific tenant (--tenant <project-slug>). Keeps the dashboard scoped and prevents cross-pollination with other ongoing kanbans.

  5. Respect existing skills. When a scene fits an existing skill, the relevant renderer should load that skill via --skill <name> on its task or always_load in its profile. Do not re-derive what a skill already provides.

  6. The director never executes. Even with the full kanban + terminal + file toolset, the director's SOUL.md rules forbid it from executing work itself. It decomposes and routes only — every concrete task becomes a hermes kanban create call to a specialist profile. The kanban orchestration guidance auto-injected into every kanban worker's system prompt spells this out further.

  7. Don't over-decompose. A 30-second product video does NOT need 20 tasks. Aim for the smallest task graph that still parallelizes well and exposes the right human-review gates.

  8. Verify API keys BEFORE firing. External APIs (TTS, image-gen, image-to-video) need keys in ${HERMES_HOME:-~/.hermes}/.env or the user's secret store. A worker that hits a missing-key error wastes a task slot. The setup script's check_key helper aborts cleanly if a required key is missing.

File map

SKILL.md                            ← this file (workflow + rules)
references/
  intake.md                         ← discovery question banks per style
  role-archetypes.md                ← role library (writer, designer, animator, …)
  tool-matrix.md                    ← skill + toolset mapping per role
  kanban-setup.md                   ← setup script structure & profile config
  monitoring.md                     ← watch + intervene patterns
  examples.md                       ← six worked pipelines
assets/
  brief.md.tmpl                     ← brief skeleton
  setup.sh.tmpl                     ← setup script skeleton
  soul.md.tmpl                      ← profile personality skeleton
scripts/
  bootstrap_pipeline.py             ← generate setup.sh from brief + team JSON
  monitor.py                        ← polling + intervention helpers

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