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

Annotations already declare readOnly, idempotent, nondestructive. The description adds: default model, Anthropic BYO key, payment implications, and return format. No contradictions; full disclosure of behavior beyond annotations.

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?

Six sentences, front-loaded with main action, each sentence adds distinct value (default model, payment, return format, use cases). No 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?

Covers purpose, input, output format, and use cases. No output schema, but description lists return fields. Could mention scoring methodology or limitations, but adequate for effective tool selection.

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 100% of parameters with descriptions. The tool description adds context: default model for 'models', pass-through for '_apiKey', and disambiguation purpose for 'context'. Adds value beyond 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 tool probes LLMs for knowledge about an entity and scores visibility (0-100) per model. It uses specific verbs and resources, distinguishing it from siblings like 'ask_pipeworx' (specific to Pipeworx) and 'scan_competitor_ai_presence' (scans competitor presence).

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 use cases: AI-marketing audits, pre-launch brand checks, competitive monitoring. It implies when to use (generic visibility check) but does not explicitly contrast with alternatives or mention when not to use.

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