deeplook_lookup

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 describes the output format ('5 lines' with specific content types) and the tool's role in a workflow, but doesn't mention potential limitations like rate limits, error conditions, or authentication requirements. It adds useful context about the output format but leaves other behavioral aspects unspecified.

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 and front-loaded with the core purpose in the first sentence. Both sentences earn their place: the first defines what the tool does, the second provides crucial usage guidance. There's zero wasted text or 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?

Given the tool's simplicity (one parameter, output schema exists), the description is reasonably complete. It explains the purpose, output format, and relationship to sibling tools. The existence of an output schema means the description doesn't need to detail return values. However, with no annotations, it could have mentioned more about the tool's behavioral characteristics.

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 has 0% description coverage for its single parameter, but the description doesn't provide any additional parameter semantics. However, with only one parameter ('company_name'), the meaning is reasonably inferable from context. The description could have added guidance about expected format or validation, but the simplicity of the parameter keeps this from being a major deficiency.

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 with specific verbs and resources: 'Quick company snapshot — phase, price, key signal, and verdict in 5 lines.' It explicitly distinguishes from its sibling tool 'deeplook_research' by positioning this as a fast check before deciding to run the full research tool.

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 to use this tool versus alternatives: 'Use this for fast checks before deciding whether to run a full deeplook_research.' This clearly defines the context and names the alternative tool, giving the agent clear decision criteria.

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