call_endpoint

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it's a data retrieval tool ('retrieve the actual data'), requires valid inputs from other tools, handles parameters in a specific way ('Both path parameters and query parameters are passed together'), and returns structured responses ('APIResponse object'). However, it doesn't mention error handling details or rate limits, leaving some gaps.

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 well-structured and appropriately sized. It starts with the core purpose, provides workflow context, explains parameter requirements clearly, and includes a returns section. Every sentence adds value without redundancy, and the information is front-loaded with the most important details first.

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 complexity (3 parameters with 0% schema coverage, no annotations, but with output schema), the description is complete enough. It explains the tool's role in the workflow, parameter requirements and semantics, and references the output format ('APIResponse object'). The presence of an output schema means the description doesn't need to detail return values, and it adequately covers the essential context for proper use.

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 schema description coverage is 0%, so the description must fully compensate. It provides comprehensive parameter semantics: explains that 'path' and 'method' must be valid combinations from list_api_endpoints, describes the 'params' dictionary must contain all required parameters from get_endpoint_schema, and clarifies how parameters are passed ('Both path parameters and query parameters are passed together'). This adds significant meaning beyond the bare 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 states the tool's purpose: 'Calls a specific endpoint of the Brazilian Chamber of Deputies API' and 'used to retrieve the actual data.' It specifies the verb ('calls'), resource ('endpoint'), and scope ('Brazilian Chamber of Deputies API'), distinguishing it from sibling tools that perform more specific queries like get_bills_by_deputy or get_deputy_expenses.

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 provides explicit guidance on when and how to use this tool: 'This is the final tool in the workflow' and 'The path and method must be a valid combination obtained from the list_api_endpoints tool.' It also references alternatives by naming prerequisite tools (list_api_endpoints, get_endpoint_schema), clarifying its role in the workflow.

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