verify

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

With no annotations, the description carries the full burden. It discloses a critical behavioral trait: the tool only reports provably absent references, so a clean result is meaningful and a block is never a guess. It also states the output (blocked references and real API), providing transparency beyond the schema.

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 concise and front-loaded: the first sentence captures the main purpose, and the second paragraph adds brief usage guidance. Every sentence earns its place with no repetition or fluff.

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 tool with no output schema or annotations, the description covers the essential context: what it does, what it returns, when to run it, and its certainty guarantee. It does not discuss error handling or prerequisite conditions, but for the tool's complexity, this is reasonably 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 description coverage is 100%, so the baseline is 3. The description adds minimal new parameter-level meaning: 'Python source' maps to code, and 'this project' loosely ties to path, but this does not go beyond what the schema already provides for each parameter.

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 states a specific action ('Check Python source for references that provably do not exist') and specifies the exact scope: invented packages, invented methods, and missing helpers. This clearly distinguishes it from sibling tools (surface, context) by focusing on validation/verification rather than exploration.

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 gives clear usage context: 'Run this on code you are about to write.' It also explains when results are meaningful ('a clean result is meaningful'). However, it does not explicitly contrast with sibling tools or when not to use it, so it misses the 'when-not' aspect.

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