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

Annotations already declare readOnly/idempotent/non-destructive; the description adds meaningful behavior beyond that: operated_by_ranked products are returned in a separate unranked block, never ordered above others, and evidence tier is provenance not quality. It also documents the common result fields, making the tool's behavior concrete without contradicting 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?

Four dense sentences, each contributing unique information: dataset scope and size, result fields, sibling routing, ordering rule, and evidence-tier caveat. It is front-loaded and contains no filler.

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 carries the full burden of explaining returns, and it does: every result carries url/source/source_url/accessed_on, register-backed variants add register entry and access date, and ranking behavior for Ranked-operated products is stated. Combined with the annotations and sibling routing, an agent has enough to call and interpret this 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 documents query as name/domain/category/licence type and limit has default/min/max constraints, so the description does not need to restate them. It adds output-structure context (result fields, unranked block) but does not further explain how query or limit behave, leaving limit semantics mostly to inference.

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?

Description opens with a specific action ('Search Ranked's dataset...') and defines the resource scope ('Nigerian-relevant businesses, institutions, websites and apps'), then distinguishes itself from live-rank/place siblings. The sibling reference and dataset composition make it easy to tell apart from ranked_rankings and ranked_place.

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 routes live-ranking and place-page needs to ranked_rankings / ranked_place, and the 'file-backed dataset' framing establishes when this tool is appropriate. It does not enumerate all sibling distinctions (e.g., ranked_by_regulator), but the main alternative is clearly identified.

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