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AI App MCP

AI App MCP

by yh008
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

normalize_user_query

Normalize user text before retrieval, routing, or agent planning. Optionally lowercases the query for consistent matching.

Instructions

Normalize user text before retrieval, routing, or agent planning.

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": {
      "query": "<query>"
    },
    "name": "normalize_user_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes
lowercaseNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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. However, it fails to specify what 'normalize' entails (e.g., casing, trimming, stemming), whether it modifies the input or returns a new value, or any side effects. The 'lowercase' parameter is not mentioned, leaving significant ambiguity.

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 a single, concise sentence with no unnecessary words. It is front-loaded with the verb and resource, making it easy to scan. However, the extreme brevity borders on under-specification, though that is more a completeness issue than a conciseness one.

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?

Despite the tool being relatively simple, the description is too minimal. It lacks behavioral details, parameter explanations, and any firm usage heuristics. Given the absence of annotations and the presence of an output schema, the description still fails to provide a complete picture of when and how to use the tool.

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

Parameters1/5

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

Schema description coverage is 0%, and the description adds no information about the 'query' or 'lowercase' parameters. The parameter names offer some hints, but the description does not explain their meaning, types, or usage. This provides no added value beyond the raw schema.

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 the action ('Normalize') and the resource ('user text'), and provides context for when it is performed ('before retrieval, routing, or agent planning'). It is distinct from sibling tools like search_knowledge_base or get_document, though it does not explicitly differentiate itself.

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?

The phrase 'before retrieval, routing, or agent planning' implies the usage context, but there is no explicit guidance on when not to use the tool or which alternatives might be more appropriate. The guidance is implied rather than directive.

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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