Agent skill
create-cast
Multi-round character casting orchestrator for the Horus movie pipeline. Extracts characters from scripts, discovers reference actors, generates identity images, and assigns voices. Runs as Phase 2.5 in create-movie.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/create-cast
Metadata
Additional technical details for this skill
- short description
- Character casting with identity packs for Veo
SKILL.md
Create Cast Skill
Multi-round collaborative workflow for casting characters in AI-generated movies.
Quick Start
cd .pi/skills/create-cast
# Start a new casting session
./run.sh start path/to/script.json
# Continue with answers to questions
./run.sh continue --session casting-20260204-abc123 --answers '{"q1": "approve"}'
# Check session status
./run.sh status --session casting-20260204-abc123
# Export identity packs
./run.sh export --session casting-20260204-abc123 --output ./characters
Philosophy
Casting is collaborative. The skill extracts characters, proposes specs, discovers reference actors, generates identity images, and assigns voices - but asks questions at each step to ensure alignment with the creator's vision.
Identity consistency is the goal. The output is a set of "identity packs" that Veo can use to maintain character consistency across multiple shots.
Casting Rounds
Round 1: Script Analysis
├── Parse script for character mentions
├── Extract dialogue to identify speakers
├── Infer physical descriptions from action text
├── Estimate screen time per character
└── Questions: Confirm character list and traits
Round 2: Reference Discovery (optional)
├── Call discover-talent for each main character
├── Build mood board of reference actors
└── Questions: Select reference actors or skip
Round 3: Identity Generation
├── Generate candidate looks via create-image
├── 3-5 options per character
└── Questions: Select best look or iterate
Round 4: Identity Pack Build
├── Generate front view (neutral lighting)
├── Generate 3/4 view (same lighting)
├── Generate full-body (outfit reference)
└── Questions: Approve angles or regenerate
Round 5: Voice Casting
├── Search existing voice models (learn-artist/tts-train)
├── Match voice type to available models
└── Questions: Approve voice or queue training
Commands
Start Casting Session
./run.sh start <script.json> [--json] [--auto-approve]
Begins a new casting session from a script file. Returns questions for Round 1.
Options:
--json: Output structured JSON for agent parsing--auto-approve: Skip questions and use defaults (for automation)
Continue Session
./run.sh continue --session <ID> --answers '<JSON>'
Provide answers to questions and advance to the next round.
The answers JSON maps question IDs to responses:
{
"confirm_characters": "approve",
"sarah_trait_age": "early 30s",
"villain_reference": "skip"
}
Check Status
./run.sh status --session <ID> [--json]
Get current session status: phase, pending questions, completed characters.
Export Identity Packs
./run.sh export --session <ID> --output <directory>
Export completed identity packs to a directory:
characters/
├── SARAH/
│ ├── identity_pack/
│ │ ├── front.png
│ │ ├── three_quarter.png
│ │ └── full_body.png
│ ├── character_bible.yaml
│ └── mood_board/
└── VILLAIN/
└── ...
List Sessions
./run.sh list
List all active and completed casting sessions.
Character Spec Schema
name: SARAH
role: protagonist
screen_time_estimate: 45.0 # seconds
physical:
age_range: "early 30s"
gender: "female"
build: "athletic"
hair: "short dark"
distinguishing: "determined expression"
personality:
- determined
- resourceful
- guarded
voice_type: "confident, measured"
dialogue_count: 12
scenes: [1, 3, 5, 7]
bridge_attributes:
- Resilience
- Precision
Identity Pack Schema
character_name: SARAH
images:
front: characters/SARAH/identity_pack/front.png
three_quarter: characters/SARAH/identity_pack/three_quarter.png
full_body: characters/SARAH/identity_pack/full_body.png
prompt_descriptors:
- "early 30s woman"
- "athletic build"
- "short dark hair"
- "determined expression"
- "wearing practical clothing"
lighting_notes: "Neutral studio lighting for Veo reference"
voice_model: "florence-pugh-rvc"
created_at: "2026-02-04T12:34:56Z"
Integration with create-movie
This skill runs as Phase 2.5 in the create-movie pipeline:
Phase 2: Script (create-story)
↓
Phase 2.5: CASTING (create-cast) ← THIS SKILL
↓
Phase 3: Storyboard (create-storyboard)
The identity packs flow into Phase 4 (Generate) where Veo uses them for character consistency.
Automatic Invocation
# In create-movie orchestrator (after script phase)
from create_cast import run_casting_session
casting_result = run_casting_session(
script_path=script_file,
output_dir=characters_dir,
model=model,
auto_approve=auto_approve,
)
Skill Dependencies
| Skill | Purpose | Required |
|---|---|---|
| discover-talent | Reference actor search | Optional |
| create-image | Identity image generation | Required |
| learn-artist | Voice/instrument model lookup | Optional |
| tts-train | Voice model listing | Optional |
| memory | Store learned preferences | Optional |
Configuration
Environment variables:
TMDB_API_KEY=xxx # For discover-talent
OPENAI_API_KEY=xxx # For create-image (if using DALL-E)
FLUX_API_KEY=xxx # For create-image (if using FLUX)
Example Workflow
Agent: "./run.sh start script.json"
Output:
{
"status": "needs_input",
"phase": "ANALYSIS",
"questions": [
{
"id": "confirm_characters",
"question": "I found 3 characters: SARAH (45s), VILLAIN (30s), GUARD (10s). Confirm?",
"options": ["approve", "add_character", "remove_character"]
},
{
"id": "sarah_age",
"question": "SARAH's age isn't specified. What age range?",
"options": ["20s", "early 30s", "late 30s", "40s"]
}
],
"resume_command": "./run.sh continue --session casting-20260204-abc123 --answers '{...}'"
}
Agent: "./run.sh continue --session casting-20260204-abc123 --answers '{\"confirm_characters\": \"approve\", \"sarah_age\": \"early 30s\"}'"
Output:
{
"status": "needs_input",
"phase": "DISCOVERY",
"questions": [
{
"id": "sarah_reference",
"question": "For SARAH, I found these reference actors: [Florence Pugh, Mackenzie Davis]. Select one or skip?",
"options": ["Florence Pugh", "Mackenzie Davis", "skip_reference"]
}
]
}
Sanity Checks
./run.sh sanity
# or
./sanity/sanity.sh
Verifies:
- Python syntax for all modules
- Imports work correctly
- CLI help displays
- Schema validation
- discover-talent integration (if available)
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