Kanban Video Orchestrator
Plan, set up, and monitor a multi-agent video production pipeline backed by Hermes Kanban. Use when the user wants to make ANY video — narrative film, product/marketing, music video, explainer, ASCII/terminal art, abstract/generative loop, comic, 3D, real-time/installation — and the work warrants decomposition into specialized profiles (writer, designer, animator, renderer, voice, editor, etc.) coordinated through a kanban board. Performs adaptive discovery to scope the brief, designs an appropriate team for the requested style, generates the setup script that creates Hermes profiles + initial kanban task, then helps monitor execution and intervene when tasks stall or fail. Routes scenes to whichever Hermes rendering / audio / design skill fits each beat (`ascii-video`, `manim-video`, `p5js`, `comfyui`, `touchdesigner-mcp`, `blender-mcp`, `pixel-art`, `baoyu-comic`, `claude-design`, `excalidraw`, `songsee`, `heartmula`, …) plus external APIs for TTS, image-gen, and image-to-video as needed.
MCP get_skill({ skillId: "kanban-video-orchestrator-f8c002a3" })Use this skill with your agent
Create a free account and connect via MCP
# 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`, `blender-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](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](references/role-archetypes.md)**.
For mapping role → which Hermes skills + toolsets it loads, see
**[references/tool-matrix.md](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](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:
```bash
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](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](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-orchestrator` skill 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
```Related Skills
More skills in Agent Orchestration
1. Product type search — what design patterns fit this product?
Design UI/UX systems with style guides, palettes, typography, and component specs for new interfaces
Acp Router
Route plain-language requests for Claude Code, Cursor, Copilot, OpenClaw ACP, OpenCode, Gemini CLI, Qwen, Kiro, Kimi, iFlow, Factory Droid, Kilocode, or explicit ACP harness work into either OpenClaw ACP runtime sessions or direct acpx-driven sessions ("telephone game" flow). For coding-agent thread requests, read this skill first, then use only `sessions_spawn` for thread creation. Codex chat binding defaults to the native Codex app-server plugin unless ACP is explicit or background spawn needs ACP.
Add New Safe Output Type
Adding a New Safe Output Type to GitHub Agentic Workflows
Agent Governance
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
Agentic Development
Build AI agents with Pydantic AI (Python) and Claude SDK (Node.js)
Agentic Workflows
Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
Explore Other Categories
Skills from other categories with shared topics
1password
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
Architecture Diagram
Dark-themed SVG architecture/cloud/infra diagrams as HTML.
Ascii Art
ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.