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AIMFP

AIMFP

by aryanduntley
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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query_settings

Read-onlyIdempotent

Execute complex SQL WHERE clauses to filter records in user preferences database tables.

Instructions

Execute complex SQL WHERE clause (advanced, rare use)

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": {
      "table": "<table>"
    },
    "name": "query_settings"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYesTable name in user_preferences.db
where_clauseNoSQL WHERE clause for filtering

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.37.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is clear. The description adds minimal extra behavioral context beyond 'complex' and 'rare use'. It does not contradict annotations.

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

Conciseness4/5

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

The description is extremely short (one sentence with parenthetical) and front-loads the core action. While concise, it could be slightly more informative without being verbose. No extraneous content.

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

Completeness2/5

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

The description lacks information about return values or error behavior. Given there is no output schema, the agent is left to infer what the tool returns. For a simple query tool, this is a notable gap.

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 100%, with clear descriptions for both parameters ('Table name in user_preferences.db' and 'SQL WHERE clause for filtering'). The description adds no additional meaning beyond the schema, resulting in a baseline score.

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?

The description clearly states it executes a complex SQL WHERE clause, which is a specific action on a resource. It implies direct SQL execution, distinguishing it from more structured query tools, though not explicitly naming siblings.

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

Usage Guidelines2/5

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

The phrase '(advanced, rare use)' hints at non-routine usage but provides no explicit guidance on when to use this tool versus alternatives like get_from_settings or query_core. There is no mention of prerequisites or conditions.

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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