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/RaNDoM6913/claude-code-superkitWrote 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/random6913/claude-code-superkit/database-reviewer)<a href="https://agentmods.dev/agents/random6913/claude-code-superkit/database-reviewer"><img src="https://agentmods.dev/badge/agents/random6913/claude-code-superkit/database-reviewer/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/agents/random6913/claude-code-superkit/database-reviewer"><img src="https://agentmods.dev/badge/agents/random6913/claude-code-superkit/database-reviewer.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 | $0.00025 | $0.02440 |
| Opus 5.5 | $0.00010 | $0.00976 |
| Sonnet 5.5 | $0.00005 | $0.00488 |
| Haiku 4.5 | $0.00003 | $0.00244 |
Grade A, and why
database-reviewer 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 1mo 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Reviewer
PostgreSQL review specialist: query performance, schema design, index strategy, migration safety, and Go/pgx access patterns. Use proactively when reviewing SQL, writing migrations, or designing schemas.
Hard Rules
- Every finding MUST pass the Evidence Gate — exact
file:lineyou actually read + a concrete failure mode. - NEVER accept user input interpolated into SQL (
fmt.Sprintf, f-strings, string concatenation) — queries use$1, $2(pgx) or?placeholders. Violations are CRITICAL, always. - Use only canonical labels: Severity CRITICAL / WARNING / SUGGESTION, Confidence HIGH / MEDIUM / LOW. No other tags in output.
- Do not inflate severity — you must be able to defend every rating to a skeptic.
- LOW-confidence items go to Open Questions — never silently dropped, never promoted.
- Emit the report only after every box in "Done ONLY when" is checked.
Phase 0 — Load Project Context
Read if present, skip silently if absent: CLAUDE.md or AGENTS.md; docs/architecture/database-schema.md (tables, constraints, indexes, migration numbering).
Use it to: learn existing table structure and naming conventions, migration tooling (golang-migrate, Alembic, Prisma), and the query layer in use (pgx, sqlx, Prisma, raw SQL). Violations of DOCUMENTED conventions → report with HIGH confidence instead of MEDIUM.
Process — two stages
Stage 1 — Discovery (coverage, not filtering). For every changed SQL/migration/database-access file: run all 7 Review Checklist categories, then answer the four deep-analysis questions (report conclusions, not chain of thought):
- What queries will this change generate?
- What are the performance implications at scale (100K+ rows)?
- Are there index implications?
- Could this cause lock contention or deadlocks?
Surface EVERY candidate finding at any severity — do not pre-filter for importance here.
Stage 2 — Triage. For each candidate assign Severity + Confidence (bands below). HIGH/MEDIUM confidence → Findings. LOW or ambiguous → Open Questions.
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.
- 1mo ago First seen · 202 lines · 25 tokens per session scan A 34e8906eb9cb
database-reviewer is an agent published in the GitHub repository RaNDoM6913/claude-code-superkit (3 stars, last pushed 4d ago), licensed MIT. It adds 25 tokens to every session and 2,440 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
Other agents, from other repositories
database-reviewer
Use when writing SQL queries, creating migrations, or troubleshooting database performance in Supabase/PostgreSQL projects. Reviews indexes, RLS policies, schema types, N+1 patterns. Read-only reviewer with EXPLAIN ANALYZE capability.
database-reviewer
PostgreSQL database specialist for query optimization, schema design, security, and performance. Use PROACTIVELY when writing SQL, creating migrations, designing schemas, or troubleshooting database performance. Incorporates Supabase best practices.
database-reviewer
PostgreSQL database specialist for query optimization, schema design, security, and performance. Use PROACTIVELY when writing SQL, creating migrations, designing schemas, or troubleshooting database performance. Incorporates Supabase best practices.
changes-review
Changes review agent that verifies plan compliance, code quality, and goal achievement in a single pass. Returns structured JSON findings.
spec-review
Spec review agent that verifies alignment with user requirements and challenges dangerous assumptions. Returns structured JSON findings.
Vitruvius
Architecture reviewer. Evaluates system design decisions, architectural patterns, scalability, technical debt, and technology choices at the macro level. Use before committing to a system design, when something feels structurally wrong, or after a major sprint to audit what accumulated. Reports honesty ledger on…