hermes-agent/optional-skills/creative/kanban-video-orchestrator/SKILL.md
Teknium db22efbe88 feat(optional-skills): declare platforms frontmatter for all 63 undeclared skills
Extends the Windows-gating work to the optional-skills/ tree. Every
SKILL.md that previously omitted the platforms: field now carries an
explicit declaration, which Hermes's loader (agent.skill_utils.
skill_matches_platform) honors to skip-load on incompatible OSes.

58 skills declared cross-platform (platforms: [linux, macos, windows]):
  autonomous-ai-agents/blackbox, autonomous-ai-agents/honcho
  blockchain/base, blockchain/solana
  communication/one-three-one-rule
  creative/blender-mcp, creative/concept-diagrams, creative/hyperframes,
  creative/kanban-video-orchestrator, creative/meme-generation
  devops/cli (inference-sh-cli), devops/docker-management
  dogfood/adversarial-ux-test
  email/agentmail
  finance/3-statement-model, finance/comps-analysis, finance/dcf-model,
  finance/excel-author, finance/lbo-model, finance/merger-model,
  finance/pptx-author
  health/fitness-nutrition, health/neuroskill-bci
  mcp/fastmcp, mcp/mcporter
  migration/openclaw-migration
  mlops/accelerate, mlops/chroma, mlops/clip, mlops/guidance,
  mlops/hermes-atropos-environments, mlops/huggingface-tokenizers,
  mlops/instructor, mlops/lambda-labs, mlops/llava, mlops/modal,
  mlops/peft, mlops/pinecone, mlops/pytorch-lightning, mlops/qdrant,
  mlops/saelens, mlops/simpo, mlops/stable-diffusion
  productivity/canvas, productivity/shop-app, productivity/shopify,
  productivity/siyuan, productivity/telephony
  research/domain-intel, research/drug-discovery, research/duckduckgo-search,
  research/gitnexus-explorer, research/parallel-cli, research/scrapling
  security/1password, security/oss-forensics, security/sherlock
  web-development/page-agent

5 skills gated from Windows (platforms: [linux, macos]):
  mlops/flash-attention   - Flash Attention wheels are Linux-first; Windows
                            install requires building from source with CUDA
  mlops/faiss             - faiss-gpu has no Windows wheel; gate rather than
                            leak partial (faiss-cpu) support
  mlops/nemo-curator      - NVIDIA NeMo ecosystem has no first-class Windows path
  mlops/slime             - Megatron+SGLang RL stack is Linux-only in practice
  mlops/whisper           - openai-whisper + ffmpeg setup on Windows is
                            non-trivial; gate until Windows install stanza lands

Methodology: scanned every SKILL.md for Windows-hostile signals
(apt-get, brew, systemd, osascript, ptrace, X11 binaries, POSIX-only
Python APIs, Docker POSIX $(pwd) bind-mounts, explicit 'linux-only' /
'macos-only' text). 3 skills flagged as having hard signals on review:
docker-management and qdrant only had POSIX $(pwd) docker examples and
the tools themselves (Docker Desktop, Qdrant) run fine on Windows —
declared ALL. whisper had an apt/brew ffmpeg install path and nothing
else but the openai-whisper Windows install story is rough enough to
warrant gating.

Strict-over-lenient policy: when in doubt, gate. Easier to un-gate after
verified Windows support lands than to leak partial support that
manifests as mid-task failures for Windows users.
2026-05-08 14:27:40 -07:00

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Markdown

---
name: kanban-video-orchestrator
description: 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.
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: [kanban-orchestrator, kanban-worker, ascii-video, manim-video, p5js, comfyui, touchdesigner-mcp, blender-mcp, pixel-art, ascii-art, songwriting-and-ai-music, heartmula, songsee, spotify, 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:<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`, `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/.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
```