mcpField
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db-storage-bloat

db-storage-bloat

github.com/hainrixzData & databases2170 installsUpdated 3d ago
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About db-storage-bloat

A database-audit skill for assessing storage maintenance and runtime health, including PostgreSQL vacuum activity, transaction ID wraparound risk, and wide-column tombstones. It helps database operators investigate performance and storage concerns using static checks and live database statistics.

Key features

  1. 01Checks VACUUM and autovacuum health
  2. 02Assesses transaction ID wraparound
  3. 03Identifies tombstone-related read degradation
  4. 04Uses catalog and statistics queries
  5. 05Reviews update-heavy table settings

Use cases

  1. 01Investigating PostgreSQL table bloat
  2. 02Checking transaction ID headroom
  3. 03Reviewing autovacuum configuration
  4. 04Assessing tombstone-heavy workloads

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/hainrixz/claude-db --skill db-storage-bloat

After installing, type/db-storage-bloatin Claude Code to confirm it loaded.

Details

From the project README

db-storage-bloat (M18)

Storage operability keeps a database fast and alive over time; it is a Performance & Scale (axis performance) concern, feeding relational Almacenamiento w12 (shared with M22/M20/M21) and the Tombstones category in the wide-column profile. The catastrophic case — TXID wraparound — can force a Postgres shutdown, so it is a severity:5 cap when imminent.

What it checks

  1. VACUUM / autovacuum health — autovacuum disabled or mis-tuned on a high-churn table, dead tuples accumulating, bloated tables/indexes inflating size and slowing scans.
  2. TXID wraparound — age(datfrozenxid) (or per-table relfrozenxid) approaching autovacuum_freeze_max_age / the 2-billion ceiling. Imminent wraparound is severity:5, fail (perf) — but only with live age evidence; statically it is at most a needs_api nudge.
  3. Tombstones (wide-column) — Cassandra/Scylla heavy deletes / TTL churn producing tombstones that degrade reads (tombstone_warn_threshold territory).

Score / axis

Feeds performance only (relational Almacenamiento w12; Tombstones in the wide-column profile).

Tier-0 (static)

Almost all of M18 is runtime truth. Statically, detect autovacuum-disabling DDL/config (autovacuum_enabled = false, aggressive fillfactor), high-delete/TTL access patterns, and wide-column delete-heavy modeling. Dead-tuple counts, real bloat, frozen-xid age, and tombstone counts all require a live DB → status: needs_api at Tier-0 (never a silent pass).

Tier-1/2 (verification query, Postgres)

-- TXID wraparound headroom (Tier-1):
SELECT datname, age(datfrozenxid) AS xid_age,
       current_setting('autovacuum_freeze_max_age')::int AS freeze_max
FROM pg_database ORDER BY age(datfrozenxid) DESC;
-- dead tuples + last autovacuum (Tier-2):
SELECT relname, n_dead_tup, n_live_tup, last_autovacuum
FROM pg_stat_user_tables ORDER BY n_dead_tup DESC LIMIT 20;

Method query_stat. xid_age near freeze_max (or the 2e9 ceiling) confirms wraparound as established and capping. High n_dead_tup with stale/NULL last_autovacuum confirms bloat as established; without sustained stats, bloat stays directional.

Findings

Emit findings per schema/finding.schema.json. Examples:

  • M18.db.txid_wraparound_imminent — xid_age approaching the ceiling (severity:5, fail, axis performance, confidence established Tier-1 only / needs_api Tier-0, fixable: advisory — aggressive VACUUM (FREEZE)).
  • M18.events.autovacuum_disabled — autovacuum turned off on a churny table (severity:3, warn, established from DDL, fixable: proposed).
  • M18.events.dead_tuple_bloat — high dead-tuple ratio (severity:3, warn, established Tier-2 / needs_api, fixable: advisory).

Each finding: evidence.observed quotes the config/DDL line or the catalog/stats row verbatim; verification.reproduce is the query above referencing $DATABASE_URL; expected_impact is banded + confidence-tagged (no naked %).

Honesty

  • Wraparound sev-5 requires live age() evidence — never declare it imminent from files; absent a connection, emit needs_api, which never caps.
  • Some "bloat" is normal steady-state headroom; flag it only against a churn pattern or measured dead ratio, and mark file-only verdicts directional.
  • Never quote a dead-tuple percentage or a days-to-wraparound number you cannot observe; magnitude is banded only. Routine maintenance fixes (VACUUM, autovacuum tuning) are proposed/advisory.

Remedy — keep updates HOT

On an update-heavy table, lowering FILLFACTOR (e.g. the default 100/90 → 70) leaves free space in each page so an UPDATE can place the new row version on the same page as a HOT (Heap-Only Tuple) update — which skips writing new index entries, curbing index write-amplification and slowing bloat growth. HOT only fires when no indexed column changed and the page has room, so a lower FILLFACTOR plus not over-indexing the churned columns is the lever. This is the positive counterpart to the autovacuum/bloat findings above; emit it as fixable: proposed (a FILLFACTOR change rewrites only on subsequent updates).

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