Agent SOPs

Concise, imperative SOPs for AI agents. Each includes a copyable agent prompt.

LLM-friendly access

Per-SOP plaintext URLs for init prompts:

Workflow	URL
Batch Import	/_llms-txt/batch-import-sop.txt
Collection Audit	/_llms-txt/collection-audit-sop.txt
Genre Classification	/_llms-txt/genre-classification-sop.txt
Genre Audit	/_llms-txt/genre-audit-sop.txt
Set Building	/_llms-txt/set-building-sop.txt
Pool Building	/_llms-txt/pool-building-sop.txt
Chapter Set Planning	/_llms-txt/chapter-set-planning-sop.txt
Metadata Backfill	/_llms-txt/metadata-backfill-sop.txt
Library Health	/_llms-txt/library-health-sop.txt

All SOPs combined: /_llms-txt/agent-sops.txt

See also /llms.txt for the full site index.

Workflows

• Batch Import — prepare newly acquired music for Rekordbox import
• Genre Classification — classify genres using Discogs, Beatport, and audio evidence
• Genre Audit — audit existing genre tags against enrichment and audio evidence
• Set Building — build transition-scored DJ set sequences
• Pool Building — build compatible track pools for live improvisation
• Chapter Set Planning — plan multi-chapter sets with bridge tracks
• Collection Audit — detect and fix naming, tagging, and convention violations
• Metadata Backfill — backfill labels, years, and albums from enrichment caches
• Library Health — scan broken links, orphan files, duplicates, and playlist coverage

Before You Start

Run cache_coverage() first. Most workflows require cached data — hydrate if coverage is low.

Key Principles

• Read-only DB. Changes staged in memory, exported as XML.
• Human approval required. Present recommendations, wait for confirmation.
• Cache-first. Flag gaps rather than triggering external calls mid-workflow.
• Export path: update_tracks() → preview_changes() → write_xml()