1. Find a release that ships with SDH subtitles

Use this skill whenever we need cinematic emotional exemplars (respect, humor, regret, anger, rage, etc.) for PersonaPlex.

It enforces a subtitle-first workflow:

1. Search NZBGeek for scene releases that already include .srt/.sup files with stage directions.
2. Map rage/​anger windows from the subtitle text or tags (no decoding needed yet).
3. Clip + Transcribe targeted scenes, marry them with the subtitle cues, and emit Persona-ready JSON.

Commands

run.sh search "<title>"

• Calls NZBGeek’s API (requires NZBD_GEEK_API_KEY) and prints size/​date/​link.
• Use this to locate releases that explicitly mention subs, CC, or SDH.

run.sh scenes find --subtitle <file.srt> (--query "text" | --tag laugh)

• Quick TUI view of subtitle windows that match free text or cue tags (rage, shout, laugh, etc.).
• Pass --video movie.mkv to see ready-to-copy ffmpeg -ss ... -to ... snippets.
• Designed for “project agent wants a specific sequence” moments.

run.sh scenes quality --subtitle <file.srt> [--strict]

• Validates subtitle quality for PersonaPlex ingestion before processing.
• Checks: encoding, entry count, emotion cue presence, timing consistency.
• Use --strict to fail on warnings (for CI pipelines).

run.sh scenes analyze --subtitle <file.srt> [--verbose] [--output-json report.json]

• Scans a subtitle file and reports ALL emotion cues found, grouped by type.
• Shows count, tags found, and first occurrence for each emotion.
• Use this to assess a subtitle before extracting specific emotions.

run.sh scenes extract --subtitle <file.srt> --tag rage --video movie.mkv --clip-dir ./​clips

• Writes a PersonaPlex-ready manifest that lists each candidate scene, cue tags, inferred emotion, and clip timing.
• Optional --clip-dir automatically runs ffmpeg to produce numbered .mkv clips plus .srt subtitle snippets per match.
• Use this when we need every rage/​anger sequence from a film—no guessing or manual scrubbing.

run.sh transcribe movie_clip.mkv --emotion rage --scene "..."

• Extracts mono WAV via ffmpeg, runs Whisper (default medium), and joins the output with the matching .srt.
• Produces *_persona.json containing:
  • Stable video_id, movie title, scene notes, ISO timestamp.
  • Segment-by-segment tags (laugh, rage, whisper_candidate, etc.).
  • Rhythm metrics (WPM, pause count, duration).
• Pipe straight into horus_lore_ingest.py emotion --input <dir> --emotion rage.

Do we still need the movie if we have subtitles?
Yes for PersonaPlex: subtitles help us find the right windows, but Whisper + rhythm features require the actual audio to model tone, pacing, and breath. Use scenes extract --subtitle-only when scouting, then transcribe once the clip is cut.

Environment

Audio intensity tagging automatically installs numpy + soundfile via uv. If either import ever fails, the CLI logs a warning and continues without those tags so ingestion still works.

Workflow Example

# 1. Find a release that ships with SDH subtitles
cd /​home/​graham/​workspace/​experiments/​pi-mono/​.pi/​skills/​ingest-movie
./​run.sh search "There Will Be Blood"

# 2. Extract rage windows from the downloaded subtitles
./​run.sh scenes extract \
  --subtitle "/​home/​graham/​Downloads/​media/​movies/​There Will Be Blood (2007)/​blood.en.srt" \
  --tag rage \
  --video "/​home/​graham/​Downloads/​media/​movies/​There Will Be Blood (2007)/​There.Will.Be.Blood.2007.PROPER.1080p.BluRay.x264-ELBOWDOWN.mkv" \
  --clip-dir "./​clips/​there_will_be_blood_rage" \
  --output-json "./​clips/​there_will_be_blood_rage/​scenes.json"

# 3. Transcribe one of the clips with subtitles + metadata baked in
./​run.sh transcribe ./​clips/​there_will_be_blood_rage/​clip_01.mkv \
  --subtitle ./​clips/​there_will_be_blood_rage/​clip_01.srt \
  --emotion rage \
  --movie-title "There Will Be Blood" \
  --scene "Most explosive confrontation" \
  --characters "Daniel Plainview,Eli Sunday"

Batch Processing (Automated Pipeline)

For automated Horus persona training, use the batch commands to process multiple movies at once.

run.sh batch discover [--subtitles]

Scan media directories to create an inventory of available movies.

./​run.sh batch discover --subtitles
# Shows: Title | Size | Subtitle availability (✓ SDH, ✓, ✗)

run.sh batch plan [--emotion rage,sorrow] [--include-unavailable]

Create a processing manifest from built-in emotion-movie mappings (dogpile research).

./​run.sh batch plan --emotion camaraderie
# Creates batch_manifest.json with ready/​needs_subtitle/​not_in_library status

run.sh batch run --manifest batch_manifest.json [--dry-run]

Execute batch processing: extract → clip → transcribe → persona JSON.

./​run.sh batch run --manifest batch_manifest.json --dry-run  # Preview
./​run.sh batch run --manifest batch_manifest.json            # Execute

run.sh batch status

Show status of processed emotion exemplars.

./​run.sh batch status
# Shows: Emotion | Movies | Clips | Personas

Built-in Emotion Mappings

The batch system includes curated movie-emotion mappings from dogpile research:

Agent-Friendly Commands

These commands are designed for easy use by project agents (like Horus) with integration into dogpile for research and agent-inbox for cross-project communication.

run.sh agent recommend <emotion> [--actor MODEL] [--library PATH]

Research movies with emotional scenes for TTS training. Returns abstracts, balanced reviews, and scene recommendations for agent evaluation.

# Research rage movies with DDL intensity
./​run.sh agent recommend rage --actor "DDL" --library /​mnt/​storage12tb/​media/​movies

# Output includes:
# - Actor model and voice tone for the emotion
# - BDI patterns (Belief/​Desire/​Intention) to match
# - Dogpile research results with movie abstracts and reviews
# - Local library availability check
# - Instructions for agent to respond with APPROVED/​QUEUE/​SKIP decisions

run.sh agent quick --movie PATH --emotion EMO --scene "desc" --timestamp "HH:MM:SS-HH:MM:SS"

Single-step extraction that consolidates the 6-step manual workflow:

1. Download subtitles (if missing)
2. Extract video clip
3. Extract subtitle window
4. Run Whisper transcription
5. Create persona JSON
6. Update inventory

./​run.sh agent quick \
  --movie "/​mnt/​storage12tb/​media/​movies/​Troy (2004)" \
  --emotion rage \
  --scene "Achilles beach landing" \
  --timestamp "01:15:30-01:17:00" \
  --output /​path/​to/​persona/​exemplars/​rage/

run.sh agent discover <library_path> [--emotion EMO] [--query TEXT]

Discover emotion-matching scenes in local media library by scanning subtitles.

./​run.sh agent discover /​mnt/​storage12tb/​media/​movies --emotion rage
# Outputs matching scenes with timestamps, ready for extraction

run.sh agent inventory [--emotion EMO] [--json]

Show inventory of processed clips across all sessions.

./​run.sh agent inventory
# Shows: Total clips, movies processed, clips per emotion, threshold status

run.sh agent request --to PROJECT --emotion EMO --desc "description"

Send clip extraction request to another project via agent-inbox.

./​run.sh agent request --to ingest-movie --emotion rage --desc "Need betrayal fury scenes" --count 5

run.sh agent recommend-book [--movie TITLE] [--emotion EMO] [--library PATH]

Recommend books to read before processing a movie for emotion extraction.

# Find source material for a specific movie
./​run.sh agent recommend-book --movie "Dune"

# Find thematically related books for an emotion
./​run.sh agent recommend-book --emotion rage --library ~/​library/​books

# Combined: find books related to movie AND emotion
./​run.sh agent recommend-book --movie "There Will Be Blood" --emotion rage

Why read before watching?

• Understand character motivations and internal monologue
• Note what was changed in the adaptation
• Provide richer context for emotion extraction
• Ground persona training in textual detail

See /​consume_common/​WORKFLOW.md for the complete book-before-movie pipeline.

Radarr Integration (Automated Acquisition)

Automatically acquire movies from curated emotion mappings using Radarr.

Horus TTS Preset

All downloads enforce:

• 1080p maximum - No 4K (1080p sufficient for TTS voice extraction)
• 15GB maximum file size - Prevents storage bloat
• English audio required - For TTS training
• SDH subtitles preferred - For emotion tagging

Radarr Configuration

Configure in Radarr UI before using:

1. Settings > Profiles > Quality Profiles - Add "Horus TTS" profile:

   • Enable ONLY: Bluray-1080p, WEB 1080p, HDTV-1080p
   • Set Bluray-1080p Max Size: 15000 MB (15GB)
   • Disable all 4K qualities

2. Settings > Custom Formats - Add "SDH Subtitles":

   • Condition: Release Title contains "SDH" OR "CC" OR "Subs"
   • Score: +100

3. Settings > Profiles > "Horus TTS" - Set custom format scores:

   • SDH Subtitles = +100

run.sh acquire radarr [--preset horus_standard] [--emotion rage,sorrow]

Add missing movies to Radarr with enforced constraints.

# Use the recommended preset (1080p, 15GB max, English, SDH subs)
./​run.sh acquire radarr --preset horus_standard

# Preview what would be added
./​run.sh acquire radarr --preset horus_standard --dry-run

# Add only specific emotions
./​run.sh acquire radarr --preset horus_standard --emotion rage,anger

Dogpile Integration

Use /​dogpile with the movie_scenes preset for comprehensive movie research:

cd /​home/​graham/​workspace/​experiments/​pi-mono/​.pi/​skills/​dogpile
./​run.sh search "war movies betrayal scenes DDL intensity" --preset movie_scenes

The movie_scenes preset searches:

• IMDB, Rotten Tomatoes, Metacritic for reviews
• Letterboxd for community ratings
• Sublikescript, IMSDB for scripts
• OpenSubtitles for availability

Cross-Project Workflow (Horus Example)

Horus Agent                              ingest-movie Skill
     |                                          |
     |-- /​dogpile "rage movies" ------------------>
     |<-- Movie recommendations with reviews ------|
     |                                          |
     |-- "APPROVED: Troy - Achilles scene" ------->
     |                                          |
     |                  ./​run.sh agent quick    |
     |                  --movie Troy            |
     |                  --emotion rage          |
     |                  --timestamp 01:15-01:17 |
     |                                          |
     |<-- Persona JSON created, inventory updated -|
     |                                          |
     |-- Import to ArangoDB knowledge graph ------>

Sanity

./​sanity.sh   # Verifies Typer CLI + scenes helpers load