hive_keyword_ranks

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

With annotations already covering read-only, idempotent, and safe behavior, the description adds substantial context: return format (ordered app ids with rating counts), a 1,000-row cap (days × depth), and explicit credit cost tiers (10/20/40 for 7/30/90 days). It also cross-references hive_app_details for name resolution.

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?

Three sentences, front-loaded with purpose, then row limit and cross-reference, then credit pricing. Every sentence adds value with no repetition or 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?

For a five-parameter read-only tool with no output schema, the description fully explains what the return data looks like (ordered app ids with rating counts), the row limit, and the cost model, leaving no critical gap 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 coverage is 100%, so the baseline is 3, but the description adds a derived constraint: the 1,000-row limit is 'days × depth' and explains the relationship between days and results per day. It also clarifies that 'day by day' refers to the temporal dimension of results.

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 states a specific verb+resource: returns who ranks where for any search term in one storefront, day by day, with ordered app ids and rating counts. This is highly specific and clearly distinguishes it from generic app search or keyword metric 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 a follow-up action ('pass the ids to hive_app_details for names') but does not explicitly state when to use this tool versus alternatives like check_rank or hive_keyword_metrics. Usage context is implied by the purpose, but no exclusions or comparisons are provided.

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