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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: output is LLM-narrated, for human consumption, and includes quantified recommendations with time horizons and a presenter script. No contradictions with 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?

The description is dense but well-organized: purpose, output summary, usage guidance, and inputs all in one paragraph. The 'Delivered by Manue' sentence is slightly tangential but adds personality without bloating. It is front-loaded with the essential purpose.

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 the tool's moderate complexity and presence of an output schema, the description covers the key aspects: what it returns, when to use it, and what inputs are needed. The async behavior is only in the schema, but that is acceptable since the schema documents it. The description is complete enough for an agent to select and invoke 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 100%, so the baseline is 3. The description reiterates the inputs (company name + pitch, 1-10 competitors) but adds no new semantic nuance beyond the schema's own property descriptions. It does not mention the optional `focus` or `async` parameters, but those are already well-documented in the 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 produces an LLM-narrated competitive-intelligence briefing for human consumption, explicitly distinguishing it from the sibling tool `competitive_deep_dive` which provides raw structured data. It enumerates specific deliverables (severity-rated moves, pricing radar, recommendations, slide script) that make its purpose unmistakable.

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?

It explicitly says to use this tool when the buyer wants a narrative briefing or deck, and names the alternative `competitive_deep_dive` for raw structured multi-source data. This directly answers when-to-use versus alternatives.

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