Pickrate

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.

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

The annotations already mark the tool as read-only and idempotent, and the description adds the critical authentication requirement (Bearer token) and describes the output structure (outcome and source). This goes beyond the structured data and gives the agent necessary operational details.

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 front-loaded with its purpose and then expands with illustrative questions and return categories. While it includes some redundancy (e.g., 'Lets the user just ask'), each sentence contributes context, and it is not overly verbose.

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 simple read-only tool with a single parameter and no output schema, the description covers the return value in detail (outcome and source), explains authentication, and gives typical use cases. No major gaps are apparent, though it could mention error handling or rate limits, which is not required for this complexity.

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 only parameter, windowDays, is fully described in the schema (default 30, max 90). The description does not add any additional meaning or constraints beyond that, so it meets the baseline for high schema coverage.

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 'Get YOUR own Pickrate agent analytics', clearly stating the verb and resource. It further elaborates with example questions about traffic, signups, and revenue, and explicitly distinguishes this from leaderboard or pick-rate tools by emphasizing 'YOUR own', making its purpose unmistakable.

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?

The description provides context that this tool is for users who want to 'just ask instead of opening a dashboard', indicating when it's appropriate. However, it does not explicitly mention alternatives or when not to use it, such as pointing to getLeaderboard for global rankings, so it stops short of full exclusion guidance.

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

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

Annotations already declare read-only and idempotent. The description adds that the tool returns both Pick Rate and readiness level as separate signals, and explicitly warns that readiness barely predicts Pick Rate—useful behavioral context beyond the 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?

Two compact sentences: the first front-loads the primary output, the second explains the secondary returned value and adds a critical caution. Each sentence earns its place with no redundancy.

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 covers what the tool returns (Pick Rate, rank, readiness level), defines Pick Rate, and provides an interpretive caution. This is fully sufficient for an agent to understand the tool's behavior.

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 for 'tool' is 100% complete, explaining accepted identifier types (name, slug, domain, package). The description adds no additional parameter-specific semantics beyond what's already in the schema, so the baseline of 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 the tool retrieves a single tool's Pick Rate and rank, defining Pick Rate as the share of time AI agents pick it over competitors on unbranded tasks. This specificity distinguishes it from sibling tools like getLeaderboard and getMyAgents.

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 implies use for a single tool rather than a leaderboard, and warns not to infer Pick Rate from readiness level. However, it doesn't explicitly name alternative tools for multi-tool queries or when to use getLeaderboard instead.

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

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

Annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already provide the safety profile. The description adds useful context about the report contents (Pick Rate, rank, who beats it), which goes beyond annotations. However, it does not disclose resolution behavior (e.g., what happens on ambiguity or no match), so it meets but does not exceed the baseline for annotation-covered tools.

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 a single sentence, front-loaded with the verb 'Resolve,' and contains no extraneous words. Every part earns its place, including the parenthetical listing of report contents.

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, no output schema, and rich annotations, the description clearly states what the tool does, what inputs it accepts, and what the output contains. It lacks edge-case details (e.g., error handling, multiple results), but given the low complexity, the description is largely sufficient.

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 single parameter 'query' is fully described in the schema ('Search term: name, slug, domain, or package'), and the description repeats these exact types. Since schema coverage is 100%, the description adds no additional meaning beyond what the schema already provides, staying at the baseline.

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 a specific action ('Resolve') and a specific resource (tool name, slug, domain, or package) to a defined output (Pickrate report with Pick Rate, rank, who beats it). This differentiates it from siblings like getLeaderboard or getPickRate by framing it as a resolution/lookup tool rather than a direct query.

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?

The description clearly implies when to use it: when you have a tool identifier (name, slug, domain, package) and want its Pickrate report. It does not explicitly mention alternatives or exclusions (e.g., using getPickRate for just the rate), but the context is clear enough for an agent to select this tool over siblings.

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