mastering-postgresql

I took a look at your mastering-postgresql skill and wanted to share some thoughts.

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 100/100, solid A grade. This is based on Anthropic's best practices for skill architecture. Your strongest area is Ease of Use (24/25)—the metadata, triggers, and workflow clarity are excellent. The weakest area is still quite good: Writing Style (9/10), mostly around voice consistency in comments.

What's Working Well

• Progressive Disclosure Architecture is tight. You've got SKILL.md as a concise hub (~320 lines) with 10 reference files exactly one level deep. This is the pattern that maximizes token efficiency without forcing users to dig through nested content.

• Decision trees and trigger phrases are chef's kiss. Your explicit "When NOT to Use" section prevents misactivation, and the triggers (pgvector, BM25 postgres, JSONB index, asyncpg, etc.) are specific enough that agents will actually activate this when needed.

• Verification steps everywhere. You've built in concrete feedback loops—SELECT extversion, EXPLAIN ANALYZE, docker-compose ps. This turns theory into "did it actually work?"—which developers love.

• Problem-solving power is real. You're covering actual gaps: pgvector setup, hybrid search patterns, cloud deployment across AWS/GCP/Azure, BM25 full-text search. This isn't theoretical—it solves problems people hit.

The Big One

Scripts directory is referenced but not included. Your SKILL.md mentions pip install -r scripts/requirements.txt and implies there are template scripts available, but these files aren't in the skill package. This hurts utility—you're telling users to copy-paste from files ...