recoup-song-metadata

Included with Lifetime

$97 forever

Turn a song's audio into structured catalog metadata using Recoup's audio language model (Music Flamingo). Use when asked to "tag this song", "generate catalog metadata", "get BPM/key/genre/mood", "create searchable metadata", "fill release metadata from audio", or to enrich a track or small catalog for DSPs, catalog systems, and release docs. Needs a public audio URL.

Image & Video

What this skill does


# Song Metadata Tagger (Music Flamingo)

Convert raw audio into clean, structured metadata you can drop into a catalog
system, DSP delivery, search index, or release doc.

The endpoint contract (auth, base URL, request/response, presets, call patterns,
gotchas) is in `references/flamingo-api.md`. Read it before calling.

## When to use

- "Tag this song" / "generate metadata"
- "What's the BPM, key, genre, mood?"
- "Make searchable metadata for these tracks"
- "Fill release metadata from the audio"

For lyrics specifically, use `recoup-song-lyrics`. For a playlist
pitch, use `recoup-song-playlist-pitch`.

## Preset chain

- **Required:** `catalog_metadata` (genre, mood, BPM, key, instruments, vocals,
  energy, danceability, similar artists, one-line description)
- **Usually add:** `mood_tags`, `music_theory`, `content_advisory`
- **Optional:** `lyric_transcription` when the user wants lyrics in the metadata

Run only what the user needs — each preset is a separate model call.

## Steps

1. Resolve a **public `audio_url`** (the endpoint cannot take a local file).
2. Call `catalog_metadata` first; add the optional presets only if asked.
3. Normalize into one `metadata.json` object (see shape below).
4. Summarize the key fields for the user; persist the JSON if in a workspace.

## Output

`metadata.json` — a single normalized object:

```json
{
  "genre": "",
  "subgenres": [],
  "primary_mood": "",
  "mood_tags": [],
  "bpm": 0,
  "key": "",
  "time_signature": "",
  "energy": "",
  "danceability": "",
  "instruments": [],
  "vocals": "",
  "similar_artists": [],
  "content_rating": "",
  "one_line_description": ""
}
```

If inside an artist workspace, save to `songs/{song-slug}/analysis/metadata.json`,
and `lyrics.md` when transcription was requested. Surface suggested updates to a
release doc's identifiers/metadata, narrative, and DSP sections rather than
editing those files silently.

## Guardrails

- **Public URL required**; no local file upload.
- **No `account_id` in the request body.**
- Treat model output as a strong draft — confirm BPM/key against a detector if
  the value drives a creative or contractual decision.

## Reference

- `references/flamingo-api.md` — auth, base URL, request/response, preset table,
  call patterns, gotchas.

Files: 2

Size: 10.9 KB

Complexity: 26/100

Category: Image & Video

Source: https://github.com/recoupable/skills/tree/main/plugins/recoup-song-analysis/skills/recoup-song-metadata

Related in Image & Video

watch

Included

Watch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.

Image & Videoscriptsfeatured

physical-ai-defect-image-generation

Included

Use when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.

Image & Videoscripts

accelint-react-best-practices

Included

React performance optimization and best practices. ALWAYS use this skill when working with any React code - writing components, hooks, JSX; refactoring; optimizing re-renders, memoization, state management; reviewing for performance; fixing hydration mismatches; debugging infinite re-renders, stale closures, input focus loss, animations restarting; preventing remounting; implementing transitions, lazy initialization, effect dependencies. Even simple React tasks benefit from these patterns. Covers React 19+ (useEffectEvent, Activity, ref props). Triggers - useEffect, useState, useMemo, useCallback, memo, inline components, nested components, components inside components, re-render, performance, hydration, SSR, Next.js, useDeferredValue, combined hooks.

Image & Videoscripts

elevenlabs-agents

Included

Build conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication

Image & Videoscripts

humanizer

Included

Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.

Image & Videoscripts

generating-mermaid-diagrams

Included

Salesforce architecture diagrams using Mermaid with ASCII fallback. Use this skill when generating text-based diagrams for Salesforce architecture, OAuth flows, ERDs, integration sequences, or Agentforce structure. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use generating-visual-diagrams), or asks about non-Salesforce systems.

Image & Videoscripts