inspect_type

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 states the action 'resolve' but doesn't clarify if this is a read-only operation, what permissions might be needed, or any side effects like caching or rate limits. It hints at output structure but lacks details on format or error handling, making it insufficient for a mutation tool with zero annotation coverage.

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 a single, efficient sentence that front-loads the core purpose without unnecessary words. It avoids redundancy and wastes no space, making it easy for an agent to parse quickly. Every word earns its place in conveying the tool's 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?

Given the tool has an output schema, the description doesn't need to explain return values, which helps completeness. However, with 2 parameters at 0% schema coverage and no annotations, the description lacks details on inputs and behavioral traits. It's minimally adequate but has clear gaps in guiding usage and understanding parameters.

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 description coverage is 0%, so the description must compensate for undocumented parameters. It doesn't explain what 'target' represents (e.g., a string of Python code or a model name) or what 'expand_nested' does (e.g., whether it recursively inspects nested types). No parameter details are provided, failing to add 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 verb 'resolve' and the resource 'Python type annotation or model', specifying what the tool does. It distinguishes from siblings like 'explain_model' or 'generate_json_schema' by focusing on structured description rather than explanation or schema generation. However, it doesn't explicitly differentiate from 'list_models' or 'validate_data', keeping it from a perfect score.

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 is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, such as when to choose 'inspect_type' over 'explain_model' or 'generate_json_schema' for similar tasks. The description lacks any usage context, leaving the agent to infer based on tool names alone.

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