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

Annotations already indicate readOnlyHint, idempotentHint, and non-destructive nature. The description adds valuable behavioral context: the default free model, optional paid Anthropic probing with a BYO key, and the structure of the return value (per-model score, confidence, signals, raw_response + combined view). It does not cover rate limits or pricing beyond the Anthropic key note, but given annotation coverage, the description provides sufficient transparency.

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: two sentences with clear front-loading of purpose, followed by specifics on models, key usage, and return format. Every sentence adds information without 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 4 parameters (1 required), no output schema, and medium complexity, the description covers all necessary aspects: what the tool does, how to configure models and keys, what the return includes, and typical use cases. The agent can determine correct invocation and set expectations.

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% (all 4 parameters described in schema). The description adds nuance: clarifying that '_apiKey' is only needed if 'anthropic' is in models, and that 'context' helps disambiguate. This adds some value beyond schema but largely reinforces existing descriptions. Baseline 3 due to high schema coverage.

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 uses a specific verb ('probe') and identifies the resource ('LLMs for visibility of a business/brand/product/topic'). It clearly distinguishes from siblings by specifying that this tool scores visibility per model, whereas 'scan_competitor_ai_presence' (sibling) likely focuses on competitor scanning. The examples and scope are well-defined.

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 states explicit use cases: 'AI-marketing audits, pre-launch brand checks, competitive monitoring.' It does not explicitly say when not to use or mention alternatives among siblings, but the stated use cases provide clear context for when to invoke this tool.

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