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

Adds value beyond annotations: default model, required key for Anthropic, direct payment, and return structure. Annotations already indicate safety; description adds cost and model behavior.

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?

Three sentences with clear front-loading of purpose. Every sentence adds necessary information; no superfluous words.

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?

Describes return format (per-model {score, confidence, signals, raw_response} + combined view) despite no output schema. Could detail combined view more, but sufficient for an audit tool.

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 covers all parameters with descriptions (100% coverage). The description adds context: default model is free, Anthropic requires key, context disambiguates. This goes beyond schema details.

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 probes LLMs for entity knowledge and returns visibility scores. It is specific but does not explicitly differentiate from siblings like 'scan_competitor_ai_presence' or 'entity_profile'.

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?

Explicitly provides use cases: 'AI-marketing audits, pre-launch brand checks, competitive monitoring.' However, it does not describe when to avoid this tool or mention alternatives.

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