contracts

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.

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

No annotations provided, so description carries full burden. It discloses the output categories (enforceable, limited, void) and included data (salary thresholds, statute). Does not mention potential limitations or side effects, but for a read-only lookup this is acceptable.

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?

Two well-structured sentences, front-loaded with key information. Every sentence adds value without redundancy.

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?

For a simple single-parameter tool with no output schema, the description sufficiently covers purpose, input, and output. Mentions specific data points (salary thresholds, statute) but could be more precise about what 'key statute' entails. Overall adequate for the tool's simplicity.

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 one parameter. Description adds value by providing an example input ('California' or 'california') and clarifying slug format, which goes beyond the schema description.

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?

Description explicitly states the tool checks enforceability of non-compete agreements by US state, including whether enforceable, limited, or void, along with salary thresholds and key statute. Covers all 50 states + DC, clearly distinguishing it from broader contract analysis tools.

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?

No explicit guidance on when to use this tool vs. alternatives. While the description implies it's for state-specific non-compete law, it does not provide when-not scenarios or mention related tools like analyze_contract or get_jurisdiction_requirements.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description must cover behavior. It explains the returned URL's purpose but omits potential side effects, prerequisites (e.g., draft status), or error conditions (e.g., invalid preview_id).

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?

Two efficient sentences that front-load the core purpose and usage, with no extraneous words.

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 one required parameter, no output schema, and no annotations, the description covers the basic purpose and usage but could elaborate on error handling, expiration of the link, or state requirements for the draft.

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?

The only parameter, preview_id, has a clear description linking it to start_contract_draft's return value. With 100% schema coverage, the description adds helpful context beyond the schema.

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 specifies the tool returns a URL for a human to preview and pay to unlock a full contract, distinct from siblings like start_contract_draft (creates draft) and get_draft_status (checks status).

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 advises use after start_contract_draft and to share the link with the user, but does not explicitly state when not to use it or mention alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Without annotations, the description fully discloses behavior: pending status during generation, and on completion returns a free preview, locked section titles, and an unlock URL. This covers all states and outputs.

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?

Two sentences deliver all necessary information: purpose, dependency on sibling, and output details. No extraneous words or repetition.

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?

For a simple polling tool with one parameter and no output schema, the description completely explains both states and return values. No gaps.

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?

The single parameter preview_id is fully described in the schema. The description adds value by linking it to start_contract_draft, explaining its origin.

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 checks contract draft status and distinguishes it from sibling tools like start_contract_draft and analyze_contract. It uses specific verbs 'check' and 'returns' to describe its action.

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?

It explicitly says the tool is for drafts started with start_contract_draft, providing context for when to use. It does not list explicit alternatives, but the reference to the sibling tool is sufficient for guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the burden. It discloses that the tool returns fields, types, options, and validation rules, which gives insight into the output structure. However, it does not explicitly state that the tool is read-only or describe any side effects, though for a question retrieval tool these are likely minimal.

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 two sentences with no extraneous information. It is front-loaded with the core purpose and adds essential context about usage and return content efficiently.

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 tool's simplicity (two parameters, no nested objects, no output schema), the description is complete. It explains the tool's purpose, its place in a workflow, and the nature of the returned data, which is sufficient for an agent to use it correctly.

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 each parameter described in the input schema. The tool description does not add additional parameter-level meaning beyond the high-level context, so the baseline score of 3 is appropriate.

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 retrieves intake questions for a specific contract type, explicitly links it to the drafting workflow by mentioning use before start_contract_draft, and distinguishes it from siblings like list_contract_types and start_contract_draft.

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 explicitly states when to use the tool ('before calling start_contract_draft') and implies its role in collecting prerequisite information. It does not provide exclusions or alternative tools, but the context makes usage clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries full burden. It discloses the type of information returned (requirements, pitfalls, etc.), which implies a read-only lookup. However, it does not explicitly confirm no side effects, auth needs, or rate limits, leaving some ambiguity.

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?

Two concise sentences: the first defines the output, the second specifies how to call it with slug examples. No unnecessary words, front-loaded with key 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?

For a simple lookup tool with two string parameters and no output schema, the description covers the return content and usage adequately. It does not mention limitations or pagination, but the tool's complexity is low, so it is largely complete.

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%, so the schema already describes both parameters. The description adds context by showing example values for contract_slug and jurisdiction_slug, but does not add new constraints or format details. Baseline of 3 is appropriate.

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 returns statute-cited legal requirements, key differences, common pitfalls, terminology, and FAQs for a contract type in a specific jurisdiction. It provides concrete examples of slugs, distinguishing it from sibling tools like analyze_contract or check_non_compete_enforceability.

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 explicitly instructs to use contract slug and jurisdiction slug with examples. It implies when to use (for legal requirements), but does not explicitly state when not to use or list alternatives. Clear context but no exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns descriptions, use cases, and prices. For a read-only list with no parameters, this is sufficient transparency, though it omits potential pagination or rate limits.

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?

Two sentences, both front-loaded with action and value. Every word earns its place; no redundancy or filler.

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 no parameters and no output schema, the description adequately explains what the tool returns and its purpose. It could mention ordering or pagination, but for a likely small set, it's sufficient.

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?

The input schema has no parameters (0 params), so schema_description_coverage is effectively 100%. Baseline for 0 params is 4; the description doesn't need to add parameter details.

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 lists all contract types with descriptions, use cases, and prices, and positions it as the starting point for finding slugs/IDs. This distinguishes it from siblings like analyze_contract or start_contract_draft.

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 explicitly advises 'Start here to find the right contract type slug/id for other tools,' indicating it's a prerequisite step. While no when-not guidance is given, the context implies it's the primary discovery tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations provided, so description fully carries the burden. Discloses async behavior (3-5 min, returns preview_id, poll for status), free preview vs paid full contract, and data requirements. No contradictions.

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?

Four sentences, each adding essential information: purpose, timing, return value, prerequisites. No wasted words; front-loaded with the core function.

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?

No output schema, but description explains the return (preview_id) and next steps (polling, checkout). Covers prerequisites, process, and lifecycle completely for a complex async 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%. Description adds value by linking deal_summary to get_intake_questions and specifying minimum required fields (parties, required fields). Does not repeat schema details, which is appropriate given full coverage.

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?

Clearly states the tool starts generating a contract draft using a multi-agent AI engine (drafter, critic, compliance checker). Distinguishes from siblings like get_draft_status and get_intake_questions by specifying the asynchronous process and prerequisites.

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?

Explicitly instructs to first get intake questions via get_intake_questions and specifies required deal_summary fields. Tells when to poll get_draft_status and that full contract requires checkout, providing clear when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.