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

Annotations declare readOnlyHint and openWorldHint, so the safety profile is already covered; the description adds real value beyond them by disclosing that the Gemini path makes an external request requiring consent and a configured key. The caveat that provider output is not equivalent to a consumer AI app or Google AI Search result, with no citations assumed, sets correct expectations for downstream interpretation.

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 tight sentences, front-loaded with the action and providers before the consent condition and the interpretability caveat. Each sentence earns its place, though the final disclaimer is slightly compressed to the point of being cryptic ('no citations are assumed').

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?

With no output schema, the description does sketch the return value as an observation for visibility analysis, which helps. But for a slow network-dependent model call with seven parameters and low schema coverage, it omits failure modes, timeouts/rate limits, expected prompt construction, and what the observation actually contains.

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 only 14% (just consentToExternalRequest is documented), so the description carries most of the burden, and it only clarifies the provider dimension (local Ollama versus external Gemini). The promptType enum values, locale, maxOutputTokens, and model naming conventions go entirely unexplained in both schema and description.

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 states a specific verb and resource ('Send one prompt to a configured local Ollama model or ... Google Gemini API') and names both provider paths, so the agent knows exactly what the tool does. It positions the result in the pipeline ('observation ready for EdGEO visibility analysis') but does not explicitly distinguish itself from siblings like edgeo_analyze_visibility, which consumes these observations.

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?

Usage preconditions are stated for the Gemini path (explicit consent plus GEMINI_API_KEY configured), which is genuinely useful routing guidance. However, there is no explicit statement of when to call this versus edgeo_analyze_visibility or edgeo_crawl_site, and no guidance on how many prompts constitute a run. Usage is implied rather than spelled out.

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