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AIMFP

AIMFP

by aryanduntley
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Python
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get_all_intent_keywords_with_counts

Read-onlyIdempotent

Retrieve all unique intent keywords along with their usage counts to analyze intent patterns and frequency.

Instructions

Get all unique intent keywords with usage counts for analytics

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_all_intent_keywords_with_counts"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.37.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, so the agent knows it's safe and idempotent. The description adds that it returns usage counts, which is helpful context beyond annotations. However, it does not disclose potential performance implications or output size, which could be relevant for large datasets.

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 a single, front-loaded sentence that conveys the core function without extraneous words. It efficiently communicates the purpose and key deliverable (unique keywords with counts).

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

Completeness3/5

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

While the description adequately states the purpose for a simple read tool, it lacks details about the output format (e.g., an array of objects with keyword and count fields). Since there is no output schema, the description bears the burden of explaining the return structure, which it does not do. This could leave the agent uncertain about the data shape.

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 no parameters (0), and schema coverage is 100%. The description adds no parameter details because none exist, but it does add meaning by specifying the counts aspect. Baseline for 0 params with complete schema is 4, and the description meets that.

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 clearly states the tool retrieves 'all unique intent keywords with usage counts for analytics,' specifying both the resource (intent keywords) and the additional value (counts). It distinguishes itself from siblings like 'get_all_directive_keywords' which likely returns keywords without counts, and implies a distinct use case for analytics.

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 description implies usage for analytics when counts are needed, but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. Given the sibling set, it could give more guidance about when not to use it (e.g., if only keywords are needed, use get_all_directive_keywords).

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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