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taxcite

taxcite

by rakib-nyc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

find_definition

Look up where a U.S. federal tax term is defined and identify the scope of that definition.

Instructions

Find where a term is defined, and what scope the definition has.

Args: term: The term to look up, e.g. "gross income". limit: Maximum number of definitions to return.

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": {
      "term": "<term>"
    },
    "name": "find_definition"
  }
}

Input Schema

NameRequiredDescriptionDefault
termYes
limitNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It only states the action and result (find definitions and scope) but does not disclose whether the operation is read-only, what happens if no definition is found, any authentication requirements, or the format of the output. This is a significant gap for a tool with no annotation support.

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 extremely concise, with the purpose stated in one sentence and the Args section providing minimal but sufficient parameter details. There is no fluff or redundant information; every word earns its place.

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?

The tool is simple with only two parameters, and an output schema exists, so the description covers the core purpose and parameter meanings. However, it lacks usage guidance and behavioral details (e.g., read-only nature, error behavior), making it slightly incomplete for a tool with no annotations to fall back on.

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 description explains both parameters: 'term' with an example ('gross income') and 'limit' with a clear meaning ('Maximum number of definitions to return'). The schema only provides titles and a default, so the description adds meaningful semantic value that helps an agent understand how to fill in the arguments correctly.

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 action ('Find') and the resource ('where a term is defined, and what scope the definition has'), making it specific and distinct from sibling tools like search_tax_law, which imply broader searching. An agent can immediately understand what this tool does without ambiguity.

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 description does not provide any guidance on when to use this tool versus alternatives such as search_tax_law or resolve_citation. It lacks explicit context about when this tool is appropriate and when it is not, leaving usage to inference only.

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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