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CongressMCP-full

by amurshak

Congressional Laws - Enacted public and private laws

laws

Retrieve enacted public and private laws for a U.S. Congress, with options to filter by law type and access full details for a specific law.

Instructions

Congressional Laws - enacted public and private laws (the /law endpoint).

OPERATIONS:
• get_laws: list enacted laws for a congress. Optional law_type ('pub' or
  'priv') narrows to public or private laws.
• get_law_details: full detail for one law (needs congress, law_type, law_number).

Args:
    operation: 'get_laws' or 'get_law_details'
    congress: Congress number (e.g., 119) — required
    law_type: 'pub' (public) or 'priv' (private); optional for get_laws,
              required for get_law_details
    law_number: The law's sequential number (required for get_law_details)
    limit: Max results for get_laws (default 20)
    offset: Pagination offset for get_laws

Examples:
    {"operation": "get_laws", "congress": 119}
    {"operation": "get_laws", "congress": 119, "law_type": "pub", "limit": 10}
    {"operation": "get_law_details", "congress": 119, "law_type": "pub", "law_number": 1}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
congressNo
law_typeNo
operationYes
law_numberNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, and the description does not mention whether the tool is read-only, has side effects, rate limits, or error handling. While it implies retrieval, it does not explicitly state behavioral constraints.

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 concise, using a title, short summary, and then structured lists for operations, arguments, and examples. No redundant information is present, and all parts are relevant.

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?

The description covers the available operations, all parameters with their roles, and provides examples for both operations. It does not explain output structure, but given the presence of an output schema, this is not critical. However, it lacks explicit notes on edge cases or error scenarios, so it is not fully complete.

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 adds meaningful context to the parameters: it specifies which parameters are required for each operation (e.g., law_number required for get_law_details), explains the default for limit, and clarifies the purpose of offset. This goes beyond the schema's bare types and defaults.

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 that the tool deals with enacted public and private laws, distinguishing it from sibling tools that handle bills, amendments, etc. The operations 'get_laws' and 'get_law_details' are clearly listed, making the purpose unmistakable.

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 guidance on when to use this tool over alternatives, such as when to retrieve laws versus bills or amendments. It gives examples but no contextual usage scenarios or decision criteria.

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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