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

The description goes well beyond the annotations (readOnlyHint, idempotentHint, etc.) by disclosing error behavior ('the error names every valid slug'), semantic distinction ('absent from the index... different from a measured zero'), scope ('Only crypto/Web3 brands are tracked'), refresh cadence ('Re-measured weekly'), and licensing/citation requirements. This adds substantive contextual value.

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?

Despite being a single dense paragraph, every sentence earns its place: purpose, usage, error handling, distinctions, scope, refresh, and licensing. It is front-loaded with the core definition, and no redundant or filler content exists.

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?

For a tool with one parameter and an output schema, the description provides complete context: what data is returned, how to interpret missing data, how to obtain valid inputs, when to use alternatives, and usage constraints (free, no key, attribution). This covers all necessary aspects for an agent to select and invoke the tool 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?

The schema already provides 100% parameter description for 'slug' including format and examples. The description reinforces this ('Takes a slug, not a display name') and adds a practical sourcing strategy (call list_tracked_brands or read from get_visibility_index), which enhances usability beyond 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 opens with a specific verb and resource: 'One brand's standing in the current DABLOCK release' and enumerates concrete metrics (share of answer per engine, rank, quadrant, prompt mentions). It clearly distinguishes itself from siblings by stating 'Use this when a specific brand is named' and later directing to alternatives for other intents.

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?

Explicit when-to-use guidance: 'Use this when a specific brand is named.' It also provides when-not-to-use with named alternatives: 'For the field as a whole use get_visibility_index; for this brand over time, get_history.' Additionally, it instructs on prerequisites: 'call list_tracked_brands first if you are unsure, or read the slug from get_visibility_index.'

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