Kanban Video OrchestratorSAFE

The agent that grows with you

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: kanban-video-orchestrator
description: Plan and run multi-agent video production pipelines.
version: 1.0.0
author: [SHL0MS, alt-glitch]
license: MIT
platforms: [linux, macos, windows]
metadata:
  hermes:
    tags: [video, kanban, multi-agent, orchestration, production-pipeline]
    related_skills: [ascii-video, manim-video, p5js, comfyui, pixel-art, ascii-art, songwriting-and-ai-music, heartmula, songsee, youtube-content, claude-design, excalidraw, architecture-diagram, concept-diagrams, baoyu-comic, baoyu-infographic, humanizer, gif-search, meme-generation]
    credits: |
      The single-project workspace layout, profile-config patching pattern,
      SOUL.md-per-profile model, TEAM.md task-graph convention, and
      `--workspace dir:/abs/path` discipline are adapted from alt-glitch's
      original multi-agent video pipeline at
      https://github.com/NousResearch/kanban-video-pipeline.
---

# 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](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 outp

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

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Gates applied: no_behavioural_pass.