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yagaMI-Reverse

schema-guard-mcp

Audit SQL schema

audit_sql

Audit Postgres/Supabase SQL for security vulnerabilities: missing RLS, permissive policies, broad grants, search_path gaps, and sensitive column exposure. Receive a summary with ranked findings.

Instructions

Statically audit Postgres/Supabase SQL for security issues: tables missing RLS, permissive policies, broad grants to anon/public, SECURITY DEFINER search_path gaps, and sensitive columns in client-readable tables. Returns a summary + ranked findings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesThe SQL schema / migration text to audit.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that the audit is static (implying no side effects) and returns a summary plus ranked findings. It does not explicitly state non-destructiveness or permissions, but 'statically' plus the nature of the tool provides adequate transparency for a read-only analysis.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded. The first sentence states the action and target, lists the key checks, and the second sentence describes the output. No redundant information or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking annotations and an output schema, the description covers the core inputs, the scope of analysis, and the return type (summary + ranked findings). It does not detail the ranking methodology or output structure, but for a single-parameter static analysis tool, it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides 100% coverage of the single `sql` parameter with a clear description ('The SQL schema / migration text to audit.'). The tool description adds no additional parameter-level meaning, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('statically audit') and resource ('Postgres/Supabase SQL'), and enumerates concrete security issues it detects (missing RLS, permissive policies, broad grants, SECURITY DEFINER gaps, sensitive columns). This clearly distinguishes it from sibling tools like rls_coverage, which likely focuses narrowly on RLS coverage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use the tool: when you need a static security audit of SQL schema. It does not explicitly mention alternatives or exclusions, but the scope is clear enough that an agent could infer this is the broad audit tool, while siblings like rls_coverage or list_rules serve narrower purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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