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

Annotations already carry readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the tool's scope ('digital presence, review signal, competitive position, pricing posture, visibility gaps') and that recommendations are 'evidence-cited', which goes beyond the annotations. No contradictions; the description is consistent with the read-only nature.

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 two short paragraphs: the first front-loads the purpose and key features in a single sentence, the second provides three succinct, relevant examples. No filler or repetition; every sentence earns its place.

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 complexity (multi-aspect teardown) and that it has an output schema, the description sufficiently explains what it does and the kind of output (structured, evidence-cited recommendations). It could mention potential prerequisites or limitations (e.g., only small businesses, need for accessible data), but the 'flagship' framing and examples give enough guidance for an agent to call 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 100% and each parameter is already well-described (e.g., business_name 'as it appears on its own signage/website', city_metro 'narrows the trade area and comp set', category with guidance on guessing). The description's examples reinforce usage but do not add new semantic detail beyond the schema. Baseline 3 applies because the schema carries the param meaning.

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 names the exact function ('full structured teardown of ONE named small business') and lists the concrete aspects it covers (digital presence, review signal, competitive position, pricing posture, visibility gaps, recommendations). It also declares itself 'the flagship tool — start here' which clearly distinguishes it from lower-level siblings like competitor_landscape or pricing_benchmark.

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 gives a clear directive ('start here for any single-business question') and three example invocations that illustrate reasonable scenarios (evaluating a business, diagnosing problems, pre-purchase diligence). It stops short of explicitly naming alternatives or stating when NOT to use it, but the flagship positioning implies it's the entry point, so an agent can infer when to pick it over others.

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