Get the ranked list of tools for a category by Pick Rate. Omit category to list available categories (optionally scoped by domain).
| Name | Required | Description | Default |
|---|---|---|---|
| domain | No | When listing categories, scope to one leaderboard tree. Optional. | |
| category | No | Category slug (e.g. 'payments', 'auth', 'search'). Optional. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds behavioral nuance: the ranking is specifically by Pick Rate, and omitting category changes the output to a category list. No hidden side effects are disclosed, but nothing more is needed for a read operation.
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?
Two concise sentences with no wasted words. The primary action is front-loaded, and the optional-mode instruction is clearly separated.
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 read-only tool with two optional parameters and no output schema, the description fully covers both usage modes and ordering logic. There is no missing behavioral information that would affect invocation.
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 baseline is 3. The description adds meaningful semantics beyond the schema: explaining that omitting category lists categories, and that domain scopes the category listing. This clarifies parameter interplay that raw property descriptions don't fully convey.
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 the tool's primary function: 'Get the ranked list of tools for a category by Pick Rate.' It also explains the alternative mode when category is omitted, which distinguishes it from siblings like getPickRate (likely a single-tool metric) and lookupTool (search).
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?
Provides clear usage context: use with a category to get the ranked list, or omit category to list available categories, optionally scoped by domain. It does not explicitly name alternatives or exclusions, but the dual-mode instruction gives sufficient when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
getPickRate and lookupTool both return Pick Rate and rank for a tool, differing mainly in identifier resolution; this boundary could confuse agents. Other tools are clearly distinct in purpose.
All tools follow a camelCase pattern, but most start with 'get' while one uses 'lookup', a minor inconsistency that doesn't harm readability.
Four tools cover the core use cases of viewing leaderboards, querying a tool's rate, resolving identifiers, and accessing personal analytics without excess.
The surface covers main query types for Pickrate data, though lacks methods for comparative or historical analytics, which are likely out of scope.
