Analyze Requirements
lexq_requirementsAnalyze which input facts a version requires. Returns required keys, types, and an example request body.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| groupId | Yes | Policy group ID | |
| versionId | Yes | Version ID |
lexq_requirementsAnalyze which input facts a version requires. Returns required keys, types, and an example request body.
| Name | Required | Description | Default |
|---|---|---|---|
| groupId | Yes | Policy group ID | |
| versionId | Yes | Version ID |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Input schema / additionalPropertiesRemoved value: -falseInput schema / properties / groupId / patternAdded value: +"^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$"Input schema / properties / versionId / patternAdded value: +"^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation readOnlyHint=true already signals a safe read operation. The description adds that it returns required keys, types, and an example request body, which is useful but not extensive. No contradictions with annotations, but no additional depth on permissions or response details.
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, front-loaded with the core purpose and immediately clarifying return value. No fluff or redundant phrasing.
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 read-only tool with two well-documented parameters, the description covers purpose and output. It lacks usage context (when to call it), but that is a minor gap given the straightforward nature and available annotations.
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 both groupId and versionId having descriptive names. The description does not add extra meaning beyond the schema, so baseline 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 analyzes which input facts a version requires, with a specific verb and resource. It also mentions return content (keys, types, example body). It does not explicitly differentiate from siblings, but the function is distinct enough among the many lexq_* 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 guidance on when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or sibling tools. The description only states what it does, leaving the agent to infer applicability.
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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