Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Hainrixz/claude-db --skill db-storage-bloatgit clone --depth 1 https://github.com/Hainrixz/claude-dbWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hainrixz/claude-db/db-storage-bloat)<a href="https://agentmods.dev/skills/hainrixz/claude-db/db-storage-bloat"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-db/db-storage-bloat/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hainrixz/claude-db/db-storage-bloat"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-db/db-storage-bloat.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.01232 |
| Opus 5 | $0.00028 | $0.00616 |
| Sonnet 5 | $0.00011 | $0.00246 |
| Haiku 4.5 | $0.00006 | $0.00123 |
Grade A, and why
db-storage-bloat scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- VACUUM / autovacuum health — autovacuum disabled or mis-tuned on a high-churn table, dead tuples accumulating, bloated tables/indexes inflating size and slowing scans.
- TXID wraparound —
age(datfrozenxid)(or per-tablerelfrozenxid) approachingautovacuum_freeze_max_age/ the 2-billion ceiling. Imminent wraparound isseverity:5,fail(perf) — but only with live age evidence; statically it is at most aneeds_apinudge. - Tombstones (wide-column) — Cassandra/Scylla heavy deletes / TTL churn producing tombstones that
degrade reads (
tombstone_warn_thresholdterritory).
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 81 lines · 56 tokens per session scan A 3944c89da0d9
db-storage-bloat is a skill published in the GitHub repository Hainrixz/claude-db (19 stars, last pushed 2mo ago), licensed MIT. It adds 56 tokens to every session and 1,232 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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