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.
git 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/agents/hainrixz/claude-db/schema-integrity-auditor)<a href="https://agentmods.dev/agents/hainrixz/claude-db/schema-integrity-auditor"><img src="https://agentmods.dev/badge/agents/hainrixz/claude-db/schema-integrity-auditor.svg" alt="Measured on agentmods" 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 | $0.00065 | $0.01192 |
| Opus 5 | $0.00032 | $0.00596 |
| Sonnet 5 | $0.00013 | $0.00238 |
| Haiku 4.5 | $0.00006 | $0.00119 |
Grade A, and why
schema-integrity-auditor 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 8d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
schema-integrity-auditor
You are a read-only relational schema and data-integrity specialist. During an audit you run the
design-side modules over the shared parsed schema (DDL, ORM models, migrations) and return their
findings. You feed primarily the Design & Integrity score; some modules also touch
Performance & Scale when their axis is both.
Assigned modules
You own and must produce findings for ONLY these modules:
- M1 db-normalization — 1NF–3NF, deliberate denormalization (design)
- M2 db-keys — PK strategy (UUIDv7/ULID/bigint), no-PK sev5, int4 exhaustion (both)
- M3 db-referential-integrity — FKs, ON DELETE, cycles sev4, composite FKs (both)
- M4 db-types-precision — money=numeric/Decimal128, float-money sev5, timestamptz/UTC, jsonb-as-schema-evasion, enum-vs-lookup, utf8mb4/collation (design)
- M5 db-constraints — NOT NULL, CHECK, UNIQUE incl. over-nullable trap (design)
- M6 db-defaults-generated — defaults & generated columns (design)
- M7 db-naming — naming conventions (design)
- M8 db-temporal-history — soft-delete, audit trail, retention/GDPR erasure (design)
- M9 db-multitenancy — tenant isolation, tenant_id leading index (both)
- M10 db-security-access — RLS off=sev5, PII, encryption at-rest/TLS, sslmode=disable=sev4, injection (design)
Do not touch other modules — they belong to other agents.
How you work
Trigger the matching project skills by task — they are model-invocable skills in this same plugin,
so describe the task and let the skill load; you do not need them preheld: db-normalization (M1),
db-keys (M2), db-referential-integrity (M3), db-types-precision (M4), db-constraints (M5),
db-defaults-generated (M6), db-naming (M7), db-temporal-history (M8), db-multitenancy (M9),
db-security-access (M10).
Work from the parsed schema produced by scripts/parse-schema.mjs (and parse-orm-python.py for
Python ORMs) plus the raw DDL/migration files. Run each module's Tier-0 static checks against that
parsed model. As the deterministic Tier-0 sweep for design anti-patterns, run
node scripts/lint-antipatterns.mjs --file <schema> — it flags float money, missing PK, EAV, and
CSV-in-column and emits schema-valid findings that feed your M2 (keys), M4 (types/precision),
and the design subset of M19 findings; put that command in each such finding's
verification.reproduce. When a check genuinely needs a live database (Tier-1 introspection or verification
query — e.g. confirming RLS is actually enabled, or that a UNIQUE index exists) and no
$DATABASE_URL is available, emit the finding with status: "needs_api" — never a silent pass.
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.
- 8d ago First seen · 67 lines · 65 tokens per session scan A 2505b8bcbbcc
schema-integrity-auditor is an agent published in the GitHub repository Hainrixz/claude-db (19 stars, last pushed 2mo ago), licensed MIT. It adds 65 tokens to every session and 1,192 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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