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AI for Postgres Difficulty: Intermediate ClaudeChatGPTCursor

Postgres Slow Query EXPLAIN Triage Prompt

Turn a confusing EXPLAIN (ANALYZE, BUFFERS) plan into a ranked, plain-English diagnosis with concrete index/rewrite fixes and a verification step — so you fix the real bottleneck, not a guess.

Target user
Backend and platform engineers chasing a single slow Postgres query
Difficulty
Intermediate
Tools
Claude, ChatGPT, Cursor

The prompt

You are a senior PostgreSQL DBA who reads execution plans for a living. You diagnose from
evidence in the plan, never from folklore, and you always confirm a fix with a fresh plan.

I will paste:
- The SQL query: [SQL QUERY]
- The full plan from `EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) <query>`: [EXPLAIN OUTPUT]
- Postgres version and relevant settings if known (work_mem, random_page_cost): [VERSION / SETTINGS]
- Table sizes and existing indexes if known: [SCHEMA / INDEXES]

Work through this in order:

1. **Find the dominant node** — identify where actual time and buffer reads concentrate.
   Flag any node where `actual rows` diverges sharply from `estimated rows` (a planner
   mis-estimate), large `Rows Removed by Filter`, external Sort/Hash spills to disk, or
   high `shared read` (cold cache) vs `shared hit`.

2. **Name the root cause** — e.g. missing index forcing a Seq Scan, a non-sargable
   predicate (function on an indexed column), stale statistics, bad join order from a
   bad estimate, or under-sized work_mem causing a spill. Tie each conclusion to a
   specific line in the plan.

3. **Propose fixes, ranked by impact and risk** — for each: the exact DDL or rewrite,
   why it helps, and the downside (write overhead, lock cost, plan regression risk).
   Prefer the smallest change that addresses the dominant node.

4. **Give a verification step** — the exact `EXPLAIN (ANALYZE, BUFFERS)` to re-run, what
   numbers should change (e.g. Seq Scan → Index Scan, buffers down, no spill), and an
   `ANALYZE <table>` to run first if statistics look stale.

Output format: (a) one-line verdict, (b) a ranked table of fixes [change | impact |
risk | how to verify], (c) the exact commands to run, in order.

Guardrails: validate every index/rewrite on a replica or a snapshot of prod first.
Build new indexes with `CREATE INDEX CONCURRENTLY`. Never DROP an index on prod until you
have confirmed nothing relies on it (check pg_stat_user_indexes idx_scan) and you can
recreate it. Wrap any DDL you do apply in a transaction where the storage engine allows it.

Run this prompt with AI

Test it, get an AI-improved version, or compare models — live in the Prompt Workspace. No copy-paste.

Why this prompt works

EXPLAIN plans are dense, and the natural failure mode is to skim for the word “Seq Scan” and bolt on an index. This prompt forces a disciplined read: locate the node that actually dominates wall-clock time and buffer traffic, then explain the cost from the evidence in front of you. By anchoring the estimate-vs-actual gap and Rows Removed by Filter, it surfaces the planner mis-estimates and non-sargable predicates that an index alone won’t fix.

The ranked-fix table keeps you honest about trade-offs. A new index speeds reads but taxes every write and can itself be the wrong shape; a query rewrite may be safer than new storage. Asking for impact and risk side by side means the model proposes the smallest effective change rather than a pile of speculative indexes.

Finally, the verification step closes the loop. A tuning change is only real once a fresh EXPLAIN (ANALYZE, BUFFERS) shows the dominant node shrink and the spill or cold reads disappear — and the guardrails (replica testing, CONCURRENTLY, baselines) keep the human in control of anything that touches production.

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