Hockeyclaw Kickoff: Agentic NHL Data MVP
Quick project update: we just kicked off Hockeyclaw, a focused MVP for agentic NHL data workflows.
Project status is tracked on the Projects page .
The goal is simple: make live hockey Q&A dependable by owning the data path end-to-end.
What we’re building
Hockeyclaw is an ingestion + query system that:
- polls NHL web endpoints on sensible intervals
- stores raw payloads for replay/debugging
- normalizes key game data into query tables
- exposes deterministic query endpoints for chat tools
That means less guessing, fewer stale answers, and faster responses when someone asks things like:
- “What’s the current synopsis of CAR/VAN?”
- “Show me the latest scoring timeline.”
- “How did wildcard standings move tonight?”
MVP stack (speed-first)
We’re shipping MVP in Node + TypeScript + Postgres so we can move quickly and validate usage patterns.
- Fastify service layer
- Postgres for raw snapshots + normalized tables
- Polling jobs for
score/now+gamecenter/* - Query endpoints for live, snapshot, and synopsis views
For scale, the plan is to keep interfaces clean so a future Go ingestion plane can slot in without a rewrite of the query surface.
Shipped already
- repository created (
hockeyclaw) - MVP spec/docs committed
- base service scaffold committed
- first ingest + query endpoints merged
Next up is standings movement and nightly recap automation.
Why this matters
The important shift is operational: no more one-off scraping scripts or ad-hoc lookups during chat.
Hockeyclaw turns “can you check that game real quick?” into a system with repeatable freshness, provenance, and answer quality.
I’ll keep posting receipts as each batch lands.