modbender Creator Screening Skill
Automated creator/influencer screening powered by Memories.ai V2 Video Understanding API.
Parameters
| Parameter | Default | Description |
|---|---|---|
videos_per_creator |
5 | Number of top videos to analyze per creator |
video_seconds |
30 | First N seconds of each video to analyze |
platforms |
Supported: instagram, tiktok, youtube | |
analysis_mode |
mai |
mai (visual+audio AI analysis) or transcript (audio-only fallback) |
framework |
default | Screening framework to apply. See references/frameworks/ |
output_format |
discord | discord, pdf (Google Doc→PDF), or json |
batch_size |
10 | Max creators per batch run |
Quick Start
Screen these creators: @anshmehra.in, @nishkarshsharmaa
Parameters: videos_per_creator=3, framework=cac-crusher
Workflow
Step 1: Parse Input
Accept creator URLs in any format:
- Profile:
https://www.instagram.com/username/ - Individual reel:
https://www.instagram.com/reel/SHORTCODE/ - YouTube:
https://www.youtube.com/@channelor/shorts/ID
Step 2: Get Profile & Video Metadata
Memories.ai V2: POST /instagram/video/metadata
python3 scripts/scrape_profiles.py --urls "reel_url1,reel_url2" --channel rapid
Returns per video ($0.01/video):
- Owner profile: username, full_name, followers, verified, profile_pic
- Video stats: views, play_count, duration, caption, comments, dimensions, audio info
Step 3: Video Understanding (MAI)
Memories.ai V2 MAI: POST /instagram/video/mai/transcript
This is the core analysis step. MAI provides:
- Visual scene descriptions: lighting quality, framing, environment, clothing, production value
- Audio transcription: speech-to-text with timestamps
- Content understanding: topic classification, delivery style, structure
python3 scripts/analyze_videos.py --mode mai --videos_per_creator 5 --urls "url1,url2"
Each video returns visual + audio AI analysis. Use this to evaluate:
- Section 2.1: Look & Feel (lighting, environment, framing) — from visual scenes
- Section 2.2: Audio Quality (clarity, echo, consistency) — from audio analysis
- Section 3.x: Delivery & Content (structure, fluency, maturity) — from transcript text
- Section 4: Positioning (tone, energy, brand safety) — from combined analysis
Fallback: If MAI is unavailable, use --mode transcript for audio-only analysis:
python3 scripts/analyze_videos.py --mode transcript --videos_per_creator 5 --urls "url1,url2"
Step 4: Apply Framework
Score against the selected screening framework:
python3 scripts/score_creator.py --framework cac-crusher --profile profile.json --transcripts transcripts.json
Frameworks live in references/frameworks/:
cac-crusher.md— CAC Crusher Creator Screening Framework (Talking Head + Skit categories)default.md— Generic quality screening (5 dimensions, weighted scoring)template.md— Template for creating custom frameworks
Step 5: Generate Report
Output per-creator screening cards with:
- Profile stats (followers, verified, engagement)
- Per-section scores (PASS/FAIL/FLAG)
- Transcript excerpts as evidence
- Visual quality notes from MAI
- Final verdict (APPROVED / REJECTED / CONDITIONAL)
Memories.ai V2 API Reference
All endpoints use: Authorization: <API_KEY> header (no Bearer prefix).
Base URL: https://mavi-backend.memories.ai/serve/api/v2
| Endpoint | Method | Use | Cost |
|---|---|---|---|
/{platform}/video/metadata |
POST | Profile + video stats | $0.01/video |
/{platform}/video/mai/transcript |
POST | Visual + audio AI analysis | ~$0.11/video |
/{platform}/video/transcript |
POST | Audio transcription only | ~$0.01/video |
Platforms: instagram, tiktok, youtube, twitter
Request body: {"video_url": "...", "channel": "rapid"}
MAI response: {"data": {"task_id": "..."}} (async, results via webhook)
URL format: Instagram must use /reel/SHORTCODE/ (not /p/ or /reels/)
Error Handling
- Add 0.5s delay between API calls
- Retry failed requests once, then skip
- If MAI webhook not received, fall back to transcript mode
- Always normalize Instagram URLs:
/p/→/reel/,/reels/→/reel/