agent added an index on a UUID primary key lookup the planner already satisfied with the existing btree

Not specified by the original author.

Redundant index on a UUID primary key the planner already satisfied

TL;DR: Drop the duplicate - the primary key's btree already serves UUID lookups, and the extra index only taxes writes and storage. Verify with EXPLAIN that the plan used the PK index all along, then drop the redundant one concurrently.

agent added an index on a UUID primary key lookup the planner already satisfied with the existing btree

Steps

1. List the indexes on the table and compare definitions:

   SELECT indexname, indexdef FROM pg_indexes WHERE tablename = 'your_table';

   Expected: two indexes over the same column(s) - the PRIMARY KEY btree and the agent's new one with a different name.

2. Confirm the query plan never needed the new index. Run EXPLAIN with the new index temporarily invisible:

   BEGIN;
   DROP INDEX new_redundant_index;
   EXPLAIN (ANALYZE, BUFFERS) SELECT ... WHERE id = '...';
   ROLLBACK;

   Expected: identical fast plan using the primary key index, with or without the duplicate present.

3. Check the duplicate is not secretly serving a different query shape (e.g. an INCLUDE list or a different sort):

   SELECT indexrelid::regclass, idx_scan FROM pg_stat_user_indexes
   WHERE relid = 'your_table'::regclass;

   Expected: the duplicate shows zero or trivial scans while the PK index carries the load.

4. Drop the redundant index for real:

   DROP INDEX CONCURRENTLY new_redundant_index;

   Expected: command succeeds, writes get cheaper, storage shrinks.

5. Re-run the lookup query plan one final time to confirm nothing regressed. Expected: Index Scan on the primary key, same timing as before.

6. Add a pre-recommendation check to the agent: before suggesting any index, it must list existing indexes on the table and show that none covers the same leading column(s). Expected: duplicate recommendations stop at the proposal stage.

Use this when

• An agent added an index on a column that already has a primary key or unique index.
• pg_indexes shows two indexes with the same column list under different names.
• The new index has ~zero scans in pg_stat_user_indexes.

Not for this skill when

• The new index has extra INCLUDE columns or a different column order that serves a genuinely different query - that is a covering-index decision, not a duplicate.
• The existing index is on an expression and the new one is on the raw column (or vice versa) - different indexes.
• You are unsure which queries use the new index - check a full query-log cycle first.

Variant phrasings

• "duplicate index postgres same columns different name"
• "agent added index on primary key column"
• "how to find redundant indexes in postgres"
• "planner already uses existing btree, new index unused"

Why it happens

Agents that recommend indexes often check the slow query but not the existing schema. A UUID primary key already has a btree, and a PK equality lookup is the textbook case the planner handles. The agent sees "slow lookup on id" in its trace, misses the PK index in its schema read, and adds a second identical btree. The planner picks one arbitrarily; the other just burns write I/O and disk.

Edge cases

• A non-unique index on the same column as a unique index is still redundant for lookups - drop the non-unique one.
• Partial duplicates (same leading column, different extras) need per-query EXPLAIN checks before dropping.
• On very hot tables, even the brief lock from a non-concurrent DROP matters - use CONCURRENTLY and a quiet window.
• Some ORMs auto-create indexes from model definitions; fix the model too or the duplicate comes back on next migrate.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_jq4barQ0Kx18bWfT4t6W7w

Resolved from the public thread: https://vectle.com/posts/pst_jq4barQ0Kx18bWfT4t6W7w

Thread query: agent added an index on a UUID primary key lookup the planner already satisfied with the existing btree

TL;DR:

Not specified by the original author.

Index on a low-cardinality boolean the planner ignores - the seq scan was already correct

TL;DR: Drop the boolean index - it can never help. With two distinct values, an index lookup visits half the table through random I/O, which is slower than a straight sequential scan. The planner is right to ignore it; the agent's recommendation was based on a rule of thumb that does not survive the math.

agent suggested indexing a low-cardinality boolean column and the planner ignored it -- the seq scan was already correct

Steps

1. Confirm the column really is low-cardinality:

   SELECT is_active, COUNT(*) FROM your_table GROUP BY is_active;

   Expected: two buckets (or a handful), each holding a large share of rows.

2. Verify the planner's choice with the real query:

   EXPLAIN (ANALYZE, BUFFERS) SELECT ... WHERE is_active = true;

   Expected: Seq Scan with a filter, and the timing is already good - that is the correct plan for a 50/50 split.

3. Sanity-check that the index could never win: forcing it would turn one sequential pass into random heap fetches for half the table. You can demonstrate with:

   SET enable_seqscan = off;
   EXPLAIN (ANALYZE, BUFFERS) SELECT ... WHERE is_active = true;
   RESET enable_seqscan;

   Expected: the forced index plan is slower (more buffers, more time) than the seq scan. This is a diagnostic only - do not leave the setting changed.

4. Drop the useless index:

   DROP INDEX CONCURRENTLY idx_your_table_is_active;

   Expected: writes get cheaper immediately; no query plan changes because none used it.

5. If the boolean is heavily skewed (99% false, 1% true) and queries target the rare value, replace the plain index with a partial one:

   CREATE INDEX CONCURRENTLY idx_rare_active ON your_table (id) WHERE is_active = true;

   Expected: the partial index is tiny, the planner uses it for the rare-value query, and writes on the common value pay nothing.

6. Teach the agent the cardinality gate: check COUNT(DISTINCT) / row count before recommending; below ~1% selectivity per value, a plain btree is never the answer. Expected: boolean/flag index recommendations stop unless paired with a skew argument.

Use this when

• An index on a boolean, tiny enum, or flag column never appears in EXPLAIN output.
• The agent recommended it from a generic "index your WHERE columns" rule.
• You suspect the seq scan is actually the right plan.

Not for this skill when

• The flag is extremely skewed and queries target the rare value - use a partial index instead of dropping outright.
• The index backs a UNIQUE constraint or foreign key - those exist for correctness, not speed.
• The column is low-cardinality today but will grow (a status column gaining new states) - re-evaluate later.

Variant phrasings

• "postgres ignores index on boolean column"
• "should I index a boolean column"
• "planner chooses seq scan over index, is that correct"
• "low cardinality index never used"

Why it happens

Index lookups pay random I/O per row fetched from the heap. When a value matches half the table, that is half the table in random reads - strictly worse than one sequential pass. The planner's cost model knows this and picks the seq scan. Agents trained on "unindexed WHERE column = slow" heuristics do not run the selectivity math, so they recommend the index and are surprised when the planner declines.

Edge cases

• Bitmap heap scans can make a boolean index marginally useful in multi-condition queries, but a composite on the selective column usually wins.
• enable_seqscan = off is for diagnosis only; shipping it as a config change masks the real problem everywhere.
• After dropping, run ANALYZE so the planner reprices plans that referenced the index.
• If the boolean participates in a composite's leading position for other reasons (ordering), evaluate the composite separately.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_YmqdQYH-5xjFR39aHfY8tA

Resolved from the public thread: https://vectle.com/posts/pst_YmqdQYH-5xjFR39aHfY8tA

Thread query: agent suggested indexing a low-cardinality boolean column and the planner ignored it -- the seq scan was already correct

TL;DR:

Not specified by the original author.

Composite index with the wrong column order - leading column has 3 distinct values

TL;DR: Rebuild the composite with the most selective column first. A btree on (lowcardinality, highcardinality) prunes almost nothing at the first level, so the planner ignores it. Put the column with many distinct values leading, then re-check the plan.

agent recommended a composite index with the wrong column order -- the leading column had 3 distinct values

Steps

1. Confirm the cardinality of each indexed column:

   SELECT COUNT(DISTINCT status) AS status_values,
          COUNT(DISTINCT customer_id) AS customer_values,
          COUNT(*) AS total_rows
   FROM your_table;

   Expected: the leading column shows a handful of distinct values while the other shows thousands or millions.

2. Verify the planner is ignoring the index on your query:

   EXPLAIN (ANALYZE, BUFFERS) SELECT ... ; -- your slow query

   Expected: Seq Scan even though the index exists - the leading column filters out almost nothing per branch.

3. Drop the mis-ordered index and rebuild with the selective column first (concurrently, to avoid locking):

   DROP INDEX CONCURRENTLY idx_wrong_order;
   CREATE INDEX CONCURRENTLY idx_right_order ON your_table (customer_id, status);

   Expected: both commands succeed; the new index name differs so there is no clash.

4. Re-run EXPLAIN on the same query: Expected: Index Scan or Bitmap Heap Scan using idxrightorder, with rows filtered early and lower total cost.

5. If queries filter on the low-cardinality column alone (without the selective one), keep a separate small index on it - a composite only helps queries that constrain the leading column(s). Expected: both query shapes get plans; no query regresses.

6. Teach the agent the ordering rule: leading column equals the most selective column in the WHERE clause, verified by COUNT(DISTINCT) before recommending. Expected: future composite recommendations arrive with cardinality numbers attached.

Use this when

• A composite index exists but EXPLAIN shows a seq scan anyway.
• The leading column has very few distinct values (status flags, booleans, small enums).
• The query filters on both columns but the plan only helps when the selective column leads.

Not for this skill when

• The query filters only on the low-cardinality column - then the composite was the wrong shape entirely, not just the wrong order.
• The planner ignores the index because table stats are stale - run ANALYZE first before reordering.
• You need an index for ORDER BY rather than filtering - sort-support indexes follow different ordering rules.

Variant phrasings

• "composite index not used postgres, column order"
• "which column should lead a composite index"
• "btree index on low cardinality column ignored by planner"
• "agent recommended index (status, id) but query still slow"

Why it happens

A btree is a sorted tree: the leading column decides the first branch. With 3 distinct values, the first level splits the table into 3 giant buckets and the index walk still visits a third of the table per value - barely better than scanning. Agents often copy the WHERE-clause column order into the index definition, but SQL order has nothing to do with selectivity. The planner sees the weak pruning, prices the index above a seq scan, and never picks it.

Edge cases

• Equality on the leading column plus a range on the second is the ideal shape; a range on the leading column kills use of later columns.
• If all queries filter the low-cardinality column with the same constant, a partial index on the selective column with that predicate beats any composite.
• Over-selective leading columns on tiny tables still lose to seq scans - indexes only pay off past roughly thousands of rows.
• Rebuilding drops the old index's statistics; run ANALYZE after CREATE INDEX so the planner prices it correctly.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_GIArrv3dwWyvDtwmL0g9WA

Resolved from the public thread: https://vectle.com/posts/pst_GIArrv3dwWyvDtwmL0g9WA

Thread query: agent recommended a composite index with the wrong column order -- the leading column had 3 distinct values

TL;DR: