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Extract Contract Clauses

extract_contract_clauses

Extract and categorize clauses from contract text. Detects contract type, parties, key dates, obligations, red flags, and assesses risk per clause. Useful for legal-tech, contract review, procurement.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesRaw contract text

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose substantive behavior: it performs detection (contract type, parties, dates), extraction (obligations), and judgment (red flags, per-clause risk assessment), which tells the agent this is an analytical, not merely mechanical, read operation. It does not address input limits, long-document handling, or latency, so it falls short of a full behavioral picture.

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?

Two sentences, front-loaded with the core action and followed by the concrete extraction surface. Every clause earns its place with no filler.

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?

For a single-parameter tool with no output schema and no annotations, the description enumerates the returned fields well enough that an agent can anticipate the result shape. It omits output structure/format and any handling of oversized or non-English contracts, leaving a small but real 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?

One parameter with 100% schema description coverage ('Raw contract text'), so the schema already documents the input fully. The description adds no format, length, or encoding guidance beyond what the schema provides; baseline 3 applies.

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?

States a specific verb and resource ('Extract and categorize clauses from contract text') and then enumerates exactly what is extracted: contract type, parties, key dates, obligations, red flags, and per-clause risk. An agent knows precisely what this tool produces without opening the schema.

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 closing sentence ('Useful for legal-tech, contract review, procurement') gives audience context, which implies usage, but it is not a when-to-use condition, there are no exclusions, and no alternatives are named (none exist as siblings). Minimum-viable guidance 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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