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supabase-rls-check

supabase-rls-check

by Tthanh2k6
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

diff_results

Compares two local CSV or JSON result files to return new and resolved findings, helping you track changes between security scans.

Instructions

Compare two local CSV or JSON result files (read-only, local files only, no network) and return new and resolved findings.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "old_path": "<old_path>",
      "new_path": "<new_path>"
    },
    "name": "diff_results"
  }
}

Input Schema

NameRequiredDescriptionDefault
new_pathYes
old_pathYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.1

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden, and it does disclose the important safety profile: read-only, local-only, no network. It stops short of other behavior an agent would want for a diff tool, such as how mismatched schemas or invalid/missing files are handled and whether comparison is key-based or positional.

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?

A single front-loaded sentence that packs the verb, input types, constraints, and return semantics with zero filler. Nothing is repeated from the schema or annotations, and every clause earns its place.

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?

The tool is simple (two required params, no nesting), and an output schema exists so return values need not be spelled out. The description covers inputs, environment constraints, and result meaning; only failure-mode and comparison-key behavior is left uncovered, which is a minor gap at this complexity.

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?

Schema description coverage is 0% and neither old_path nor new_path is documented in the schema, so the description has to compensate. The phrase 'new and resolved findings' implicitly establishes the old-to-new direction, but it never explicitly maps old_path as the baseline and new_path as the comparison target, nor specifies file format expectations per path.

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

Purpose4/5

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

States a specific verb ('Compare') and resource ('two local CSV or JSON result files') and names the output semantics ('new and resolved findings'). The siblings (analyze_sql_export, explain_rule, scan_public_env) are unrelated in behavior, so no explicit differentiation is required, though the description does not carve out any boundary against them.

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

Usage Guidelines3/5

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

It gives a precondition and an exclusion ('local files only, no network'), which tells the agent this is for comparing already-downloaded result artifacts. However, it never states when to prefer this over another tool or what an agent should do for remote/SQL sources, leaving usage to inference.

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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