find-hypertable-candidates
Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detectio
Profile →npx skills add timescale/pg-aiguide --skill find-hypertable-candidates --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# PostgreSQL Hypertable Candidate Analysis Identify tables that would benefit from TimescaleDB hypertable conversion. After identification, use the companion "migrate-postgres-tables-to-hypertables" skill for configuration and migration. ## TimescaleDB Benefits **Performance gains:** 90%+ compression, fast time-based queries, improved insert performance, efficient aggregations, continuous aggregates for materialization (dashboards, reports, analytics), automatic data management (retention, compression). **Best for insert-heavy patterns:** - Time-series data (sensors, metrics, monitoring) - Event logs (user events, audit trails, application logs) - Transaction records (orders, payments, financial) - Sequential data (auto-incrementing IDs with timestamps) - Append-only datasets (immutable records, historical) **Requirements:** Large volumes (1M+ rows), time-based queries, infrequent updates ## Step 1: Database Schema Analysis ### Option A: From Database Connection #### Table statistics and size ```sql -- Get all tables with row counts and insert/update patterns WITH table_stats AS ( SELECT schemaname, tablename, n_tup_ins as total_inserts, n_tup_upd as total_updates, n_tup_del as tot
- TimescaleDB Benefits
- Step 1: Database Schema Analysis
- Option A: From Database Connection
- Option B: From Code Analysis
- Step 2: Candidacy Scoring (8+ points = good candidate)
- Time-Series Characteristics (5+ points needed)
- Scale & Performance (3+ points recommended)
- Data Patterns (bonus)
- Common Patterns
- ✅ GOOD Candidates
- ❌ POOR Candidates
- Analysis Output Requirements
What does the find-hypertable-candidates skill do?
Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detectio
How do I install it?
Run `npx skills add timescale/pg-aiguide --skill find-hypertable-candidates --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From timescale/pg-aiguide, a repository with 1,806 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.