fetch_ai_visibility

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

With no annotations, the description carries full burden. It discloses the tool generates prompts, runs rankings, and returns specific metrics. It also notes the requirement for OPENAI_API_KEY. No contradictions, and the read-only nature is implied.

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?

Description is three sentences with clear structure: first states purpose, second outlines process, third gives usage tip. No unnecessary words, all sentences earn their place.

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 and simple parameters, the description adequately explains the return values, dependencies, and prerequisites. Could mention potential errors or expected environment variable, but overall sufficient.

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 coverage is 100%, providing baseline of 3. Description adds value by linking brand and industry parameters to fetch_audit_data output, enhancing semantic understanding beyond schema descriptions.

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 verb ('Measure') and resource ('brand visibility in AI/answer-engine results'), with specific details about the process and outputs. It distinguishes itself from siblings by focusing on AI visibility rather than general auditing or PDF rendering.

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?

Provides explicit guidance to pass brand and industry from fetch_audit_data when available, implying a typical workflow. Does not explicitly state when not to use or mention alternatives, but the context is clear enough.

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