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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses that the operation is anonymous, requires no account, returns only a grade band and estimated range (never a single ACS), and includes explicit behavioral warnings (do not invent a point score or describe Lite reading as ACS). This is rich, non-redundant context.

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 long but front-loaded with the core purpose, then structured into what it returns, what it does not return, and usage guidance. While dense, every sentence conveys necessary instructions, though it could be tightened slightly without losing meaning.

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 fully explains return values (band, range, engine reads, narrative, URL), what is excluded, and when to use the sibling 'reflect' tool. It covers all relevant aspects needed for correct invocation and interpretation.

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?

The schema description coverage is 100%, already defining url, brand, and industry with meanings. The description adds no parameter-specific information beyond the schema, but the schema fully covers parameter semantics, so baseline 3 applies.

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 it runs an anonymous Lite Reflection on brand AI Citability, returning a grade band, estimated ACS range, qualitative engine reads, narrative, and a hosted brief URL. It explicitly contrasts LITE with FULL and names 'reflect' as the full alternative, differentiating it from sibling tools.

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 explicit 'when to use' triggers ('how visible is [brand] in AI', 'is [brand] cited by ChatGPT/Gemini/Perplexity', etc.) and instructs to run this for the quick answer, then offer `reflect` for the Full Reflection. It also states no account is required and provides exclusions (never quote a point score).

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