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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful context: the output is AI-generated, includes up to six key themes, cites Stratalize AI, and costs $0.50 USDC per call. This goes beyond the annotations by disclosing cost and output composition.

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 efficiently structured: usage intent first, return content second, then an illustrative example, source, and pricing. The example is useful but adds length; the cost mention earns its place. Overall compact without wasted 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?

The description covers the return shape, use case, source, and cost, which is reasonably complete for a simple read-only tool. However, the unexplained 'topic' parameter and lack of any limitations or caveats leave a noticeable gap for an agent deciding how to invoke it correctly.

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 0%, so the description should compensate for both parameters. It references 'any industry' and gives a Healthcare IT example that covers the 'industry' parameter, but it never explains what 'topic' means or how it relates to 'industry'. A required and an optional parameter both remain under-specified.

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 produces a quick industry intelligence brief and returns an AI-generated market summary, key themes, and sentiment skew. It is specific about the resource and output, though it does not explicitly differentiate from sibling tools like get_sector_ai_intelligence or get_market_structure_signal.

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 opening phrase 'Use when producing a quick industry intelligence brief or validating market narrative for a strategy deck' provides clear contextual guidance. It does not mention exclusions or alternatives, so the agent must infer when other market-related tools would be more appropriate.

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