analyze_contractPaste contract text and get an AI risk analysis: red flags, one-sided clauses, missing protections, and questions to ask. Free (2/day). Not legal advice.
| Name | Required | Description | Default |
|---|---|---|---|
| focus | No | Optional focus, e.g. "IP ownership", "termination terms" | |
| contract_text | Yes | The contract text to analyze (200 to 50,000 characters) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description provides some behavioral context: it's an AI analysis, free with a daily limit, and not legal advice. However, it does not disclose data handling, storage, or privacy practices, which would enhance transparency for a tool processing user-supplied text.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences covering purpose, output types, limitations, and disclaimer. Every word adds value with no redundancy or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the average complexity (two parameters, no output schema), the description adequately covers input requirements, output types, limitations, and differentiation from sibling tools. It provides enough information for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds value by explaining the analysis output (red flags, clauses, protections, questions) and the optional focus keyword, providing context beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: analyze contract text for risks, red flags, one-sided clauses, missing protections, and questions. The verb 'analyze' and resource 'contract' are specific, and it distinguishes from sibling tools like check_non_compete_enforceability, which focus on specific legal questions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for general risk analysis and mentions free tier limitations and a disclaimer, but does not explicitly specify when not to use this tool or suggest alternatives among siblings. Some context is provided, but not comprehensive guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: analyzing existing contracts, checking non-compete enforceability, managing draft lifecycle (questions, start, status, checkout), listing types, and getting jurisdiction requirements. No two tools have overlapping functionality.
All tools follow a consistent verb_noun pattern in snake_case (e.g., analyze_contract, get_checkout_link, list_contract_types), making them predictable and easy to understand.
With 8 tools covering contract analysis, drafting, and legal requirements, the count is well-scoped for the server's purpose. Each tool serves a necessary function without bloat or deficiency.
The tool set covers listing, intake, drafting, status checking, payment, analysis, and legal requirements. However, after payment there is no tool to retrieve the full contract text programmatically; users must visit a URL, which is a minor gap.