SkillsAdd

recoupable/skills

recoup-research-playlist-targets

Find which playlists an artist or whole catalog should target and where the placement gaps are — catalog-wide playlist strategy from research data.

First seen Jun 24, 2026

Installation

$ npx skills add recoupable/skills --skill recoup-research-playlist-targets
View on skills.sh ↗ GitHub repository ↗

Summary

  • Find which playlists an artist or whole catalog should target and where the placement gaps are — catalog-wide playlist strategy from research data.
  • Use for "which playlists should we target", "placement gaps", "editorial vs algorithmic", or "which catalog tracks to push".
  • This is desk strategy from data; to pitch ONE song from its audio use recoup-song-placement-pitch.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 3
License LICENSE
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,616 B
  • docs SUMMARY.md 413 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 26 installs

SKILL.md

Recoup Research — Playlist Targets

Catalog-wide playlist strategy from research data (not one audio file).

export RECOUP_API="https://api.recoupable.dev/api"   # auth header: x-api-key: $RECOUP_API_KEY

Procedure

  • /playlists?artist={ARTIST}&status=current for placements; status=past for

re-pitch opportunities.

  • /similar → /playlists on each peer → playlists hosting 2+ peers you're NOT on

are the warmest targets (the gap analysis).

  • /track/playlists?id={track_id}&editorial=true (5 credits) for per-track

editorial coverage.

  • /metrics (playlistseditorialcurrent) to judge editorial vs algorithmic balance.

Answer: target playlists (ranked, warmest first), placement gaps, editorial vs algorithmic, and which catalog tracks to push. Full chains in references/workflows.md (Playlist Pitching Intelligence, Catalog Optimization).

Guardrails

  • No invented placements. followers_total is a formatted string ("34.3M") —

parse it if sorting numerically.

  • Credits: surface checkoutUrl on insufficient_credits.

References

  • references/workflows.md — playlist pitching + catalog optimization chains.