Agent skill

Kanban Video Orchestrator

by Luciole-Studio in Luciole-Studio/Misaka-Agent

Plan and run multi-agent video production pipelines. An agent skill from Luciole-Studio/Misaka-Agent.

MITAuto-check: notesProductivity & Automation

Install Kanban Video Orchestrator

skills CLI
$ npx skills add Luciole-Studio/Misaka-Agent --skill kanban-video-orchestrator -a claude-code

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

GitHub CLI
$ gh skill install Luciole-Studio/Misaka-Agent kanban-video-orchestrator --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/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/misaka/core/skills/assets/optional/creative/kanban-video-orchestrator .claude/skills/kanban-video-orchestrator && 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
kanban-video-orchestrator
GitHub stars
171
Used in
2 other repos
Token cost
~2.4k tokens
SKILL.md length
1,028 words
Files
12 (incl. scripts, references, assets)
Skills in repo
77
Repo updated
First seen
Licence
MIT

At a glance

Plan and run multi-agent video production pipelines. An agent skill from Luciole-Studio/Misaka-Agent.

  • Works in 6 steps: Discover (ask the right questions) → Brief → Team design → …
  • Tasks that involve Task management
  • SKILL.md covers When NOT to use this skill, Workflow, Reference: worked examples and Critical rules, plus 1 more section
  • Runs Python scripts from its folder

What it does

Kanban Video Orchestrator is an agent skill from Luciole-Studio/Misaka-Agent. Plan and run multi-agent video production pipelines.

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts, reference files and assets (for example `references/examples.md`, `references/intake.md` and `references/kanban-setup.md`).

It sits in Productivity & Automation, covering Task management, Video production and Multi-agent orchestration. The repository describes itself as: A multi-agent research system for the humanities and social sciences. The licence is MIT.

When your agent uses it

  • Tasks that involve Task management
  • Tasks that involve Video production
  • Tasks that involve Multi-agent orchestration

Example prompts

  • “/kanban-video-orchestrator”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

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

  1. Discover (ask the right questions)
  2. Brief
  3. Team design
  4. Setup
  5. Execute
  6. Monitor and intervene

What it can do on your machine

Read from SKILL.md and the folder at commit 3bcf7a3. 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 2 files in scripts/ (Python), 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

Kanban Video Orchestrator loads about 2.4k tokens when it runs, and up to ~18k if it reads all its reference files. Until then it costs about 20 tokens; SKILL.md has 1,028 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~18k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:186
    need keys in `${HERMES_HOME:-~/.hermes}/.env` or the user's secret store.

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 Luciole-Studio/Misaka-Agent at commit 3bcf7a3, republished under its MIT licence (© Luciole-Studio). 1,028 words, ~2,428 tokens.

Download SKILL.mdSave it as .claude/skills/kanban-video-orchestrator/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
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

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:

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.

Show full SKILL.md (426 more words)Show less
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

© Luciole-Studio, MIT. 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 11 other files (scripts, references, assets) in misaka/core/skills/assets/optional/creative/kanban-video-orchestrator of Luciole-Studio/Misaka-Agent.

  • SKILL.md
  • assets/brief.md.tmpl
  • assets/setup.sh.tmpl
  • assets/soul.md.tmpl
  • references/examples.md
  • references/intake.md
  • references/kanban-setup.md
  • references/monitoring.md
  • references/role-archetypes.md
  • references/tool-matrix.md
  • scripts/bootstrap_pipeline.py
  • scripts/monitor.py

Open the folder on GitHubat commit 3bcf7a3

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in Luciole-Studio/Misaka-Agent, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Kanban Video Orchestrator 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.

Kanban Video Orchestrator compared with similar skills
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Kanban Video Orchestrator this skillLuciole-Studio/Misaka-Agent1712 repos~2.4kAutomated safety check: NotesMIT
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Pi Messenger Crewnicobailon/pi-messenger719—~3.7kAutomated safety check: PassNone
AgentRQ Supervisoragentrq/agentrq1.1k—~3.1kAutomated safety check: PassAGPL-3.0
AI Fleet Project ExecutionSzotasz/marveen117—~14kAutomated safety check: PassMIT
Omh Agent Boardrlaope/oh-my-hermes3.2k—~1.9kAutomated safety check: PassMIT

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Questions about Kanban Video Orchestrator

What does Kanban Video Orchestrator do?

Plan and run multi-agent video production pipelines. An agent skill from Luciole-Studio/Misaka-Agent. Kanban Video Orchestrator is an agent skill from Luciole-Studio/Misaka-Agent. Plan and run multi-agent video production pipelines.

When should I use Kanban Video Orchestrator?

Kanban Video Orchestrator fits situations like: tasks that involve Task management; tasks that involve Video production; tasks that involve Multi-agent orchestration.

How do I install Kanban Video Orchestrator in Claude Code?

Run `npx skills add Luciole-Studio/Misaka-Agent --skill kanban-video-orchestrator -a claude-code`. Or copy the skill folder (misaka/core/skills/assets/optional/creative/kanban-video-orchestrator in Luciole-Studio/Misaka-Agent) into .claude/skills/kanban-video-orchestrator in your project. Claude Code loads it when a task matches its description.

How do I install Kanban Video Orchestrator in Codex?

Run `npx skills add Luciole-Studio/Misaka-Agent --skill kanban-video-orchestrator -a codex`. Or copy the skill folder (misaka/core/skills/assets/optional/creative/kanban-video-orchestrator in Luciole-Studio/Misaka-Agent) into .agents/skills/kanban-video-orchestrator in your project. Codex loads it when a task matches its description.

Can I use Kanban Video Orchestrator 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 Luciole-Studio/Misaka-Agent --skill kanban-video-orchestrator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kanban-video-orchestrator, .gemini/skills/kanban-video-orchestrator, .github/skills/kanban-video-orchestrator and .opencode/skills/kanban-video-orchestrator in your project.

What does Kanban Video Orchestrator need to run?

Going by SKILL.md and its folder, Kanban Video Orchestrator needs Python for the scripts in its folder. Our summary lists: Python 3; A Bash shell.

Does Kanban Video Orchestrator 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 Kanban Video Orchestrator safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. 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 Kanban Video Orchestrator use?

Kanban Video Orchestrator is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Kanban Video Orchestrator use?

About 2.4k tokens (SKILL.md is roughly 9.7k 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 16k tokens, read only when the agent opens those files.

What are the alternatives to Kanban Video Orchestrator?

Skills that share tags, products or a category with Kanban Video Orchestrator: Superset Agent Standup (superset-sh/superset, 15k stars), Pi Messenger Crew (nicobailon/pi-messenger, 719 stars), AgentRQ Supervisor (agentrq/agentrq, 1.1k stars) and AI Fleet Project Execution (Szotasz/marveen, 117 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Kanban Video Orchestrator?

Luciole-Studio (a GitHub organization) maintains it in Luciole-Studio/Misaka-Agent, which has 171 GitHub stars. The repository holds 77 skills in this directory. The repository was last updated on October 8, 2026.

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