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Chantichalla

Safe DB Gateway

by Chantichalla

list_accessible_tables

Shows which database tables an AI agent is allowed to query, with descriptions, to prevent hallucinated queries against internal or restricted tables.

Instructions

Lists the tables the agent is permitted to query, along with descriptions. Prevents the LLM from hallucinating queries against internal/restricted tables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists permitted tables and descriptions and frames its purpose as preventing hallucination, which is a useful behavioral trait. It doesn't mention authentication, rate limits, or side effects, but for a simple read-only discovery tool with an output schema, this is acceptable but not rich.

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?

Two sentences with no wasted words. The primary action is front-loaded, and the second sentence adds a clear rationale for using the tool. It is compact and efficient.

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?

Given the tool's simplicity (no parameters) and the presence of an output schema, the description is largely complete. It clearly states what it lists and why it matters. It could be slightly more explicit about when to call it relative to siblings, but it's adequate for an agent to understand its role.

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

Parameters4/5

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

The tool has zero parameters, so the baseline is 4. The description correctly says nothing about parameters, which is appropriate. The schema coverage is 100% (empty properties), and there is nothing to compensate for.

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 states a specific verb ('Lists') and resource ('tables the agent is permitted to query') with an explicit purpose. It clearly distinguishes itself from siblings like safe_query (querying) and describe_table (describing a specific table) by focusing on the enumeration of allowed tables.

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 conveys when to use it by explaining it prevents hallucinating queries against internal/restricted tables, implying it should be used before querying to know which tables are allowed. However, it doesn't explicitly name alternatives or state 'use this before safe_query', leaving some routing to inference.

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