ENGINEERING
Missing-Index Advisor to Linear Tickets
Nightly, finds sequential scans on large tables from pg_stat_user_tables, proposes candidate indexes for the underlying slow queries.
How it runs
The automated pipeline, trigger to output.
- TriggerNightly schedule
- ActionRead seq-scan-heavy tablesPostgres
- ActionCorrelate with slow queriesPostgres
- LogicPropose candidate indexes and impact
- OutputCreate Linear ticket per recommendationLinear
What it does
It proactively suggests indexes for tables getting hammered by sequential scans. Nightly it reads `pg_stat_user_tables` for high seq_scan / seq_tup_read ratios on tables above a row-count floor, correlates them with the slowest queries hitting those tables from `pg_stat_statements`, and proposes candidate composite indexes based on the filter and join columns. Each recommendation becomes a Linear ticket with the table, candidate index DDL, and estimated rows-scanned savings.
When to use it
Use this when your schema has outgrown its original indexing and nobody owns periodic index review. It converts planner statistics into concrete, reviewable backlog items.
How it works
- 1A nightly schedule fires.
- 2Read `pg_stat_user_tables` for seq-scan-heavy large tables.
- 3Join to `pg_stat_statements` to find the slow queries on those tables.
- 4A logic step proposes candidate indexes and estimates impact.
- 5Create a Linear ticket per recommendation with the DDL and rationale.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect LinearIssues, projects, cycles, triage.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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