Skill Feedback: domain-discovery (good) #30
Description
Skill Feedback: domain-discovery
Package: @tanstack/intent
Skill version: 2.0
Rating: good
Task
Generate TanStack Intent skills for the ElectricSQL monorepo (@electric-sql/client and @electric-sql/y-electric).
What Worked
- The phased approach (scan → interview → deep read → detail interview) produced comprehensive coverage
- Failure mode extraction from source assertions and migration guides was particularly high-yield
- Gap-targeted question templates helped surface maintainer knowledge efficiently
- The interview flow correctly identified 9 skills across 5 domains
What Failed
- No errors from following skill instructions directly
Missing
- The lightweight path criteria ("fewer than 5 client-facing skill areas") was ambiguous for Electric (9 skills but a focused library). Ended up using the full flow which worked fine
- The instruction to read "every narrative guide" is impractical for libraries with extensive online-only docs
- No guidance for monorepos where skills span multiple packages but domain discovery is repo-wide
- No guidance for libraries where the main value is in composition with another library (Electric + TanStack DB)
Self-Corrections
- User removed react-integration skill (use TanStack DB instead) — skill could have asked about companion library overlap earlier
- User removed multi-shape-sync (experimental feature) — skill could have asked about experimental/unstable features to exclude
- User merged content-types-and-parsing into shape-streaming — skill could have checked for skills that are subsets of another
- User removed framework-integrations (TanStack DB handles it) — same companion library overlap issue
- User skipped AI-agent detail questions ("lib too new to be in training set") — skill should offer a fast-skip for new libraries
User Comments
Process was clear and quality was good. Would like more review of individual skills before moving to the next one in future sessions.