RankCert

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states what the tool returns and does not mention whether it is read-only, any side effects, limitations, or error behavior. The default week parameter is only in the schema, not the description.

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, front-loaded sentence that directly states the purpose and output. It is concise without waste, though it could add a bit more detail without sacrificing brevity.

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 tool with one optional parameter and no output schema, the description is adequate but minimal. It does not mention the default behavior of the week parameter (though in schema), nor does it clarify the output format beyond listing products. It is sufficient for a straightforward read operation but lacks depth.

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 parameter 'week' is fully documented in the schema with its format and default. The description adds no extra meaning beyond that, meeting 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 clearly states the tool returns the RankCert board for a launch week, listing live products with their verification tier and rank score. The verb 'board' implies a listing, and the content is specified. However, it does not explicitly distinguish from sibling tools like product_signals or verification_stats, though the weekly board scope is evident.

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 no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or typical scenarios. The only hint is 'for a launch week,' which is implicit rather than explicit.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It indicates the tool returns data but does not explicitly state it is read-only, whether authentication is required, how missing slugs are handled, or any rate limits or side effects. This is a significant gap for a tool with zero annotation coverage.

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, efficient sentence with no filler. It front-loads the core purpose and lists the key output fields. It is appropriately sized for a simple one-parameter tool, though it could be slightly more structured.

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?

Given the tool's simplicity (one param, no output schema), the description covers the main purpose and output fields. However, it lacks details about the output structure (single object vs. array), error behavior, or edge cases. Since there is no output schema, the description is the sole source of return-value information, making it only partially complete.

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 the sole parameter 'slug' with 100% description coverage, so the baseline is 3. The description adds minimal extra semantic context by linking the parameter to 'one product', but offers no additional syntax, format, or constraint details 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 clearly states the tool's function: retrieving verification signals for a single product, including kind, band, source, and last confirmed date. It uses a specific verb and resource, and the scope ('One product') differentiates it from siblings like verification_stats without explicitly naming alternatives.

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?

Usage context is implied through the singular scope and the 'signals' focus: an agent can infer it is for fetching detailed signal data for a specific product. However, there is no explicit guidance on when to prefer this over verification_stats or search_products, nor any mention of prerequisites or exclusions.

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?

No annotations are present, so the description carries the behavioral disclosure burden. 'Search' and 'live' imply a read-only, current-data operation, which is useful context. However, it does not describe matching semantics, ordering, pagination, or result format, so behavioral transparency is modest rather than thorough.

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 single sentence is concise and front-loaded, with every phrase adding meaningful information about the resource and search dimensions. There is no filler or repetition of schema details.

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 search tool with four optional parameters and no output schema, the description plus schema is sufficient for basic invocation. However, it lacks detail on behavioral specifics (e.g., result ordering, pagination) and explicit routing relative to sibling tools, leaving moderate room for ambiguity.

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 covers query and tag explicitly, while the description adds alignment for 'verification tier' corresponding to the tier enum. Limit remains undocumented in both. With 50% schema description coverage, the description partially compensates but does not fully clarify all four parameters.

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 begins with a specific verb, 'Search', identifies the resource ('live RankCert products'), and names the search dimensions (free text, tag, verification tier). This makes it easy to distinguish from sibling tools like board_this_week and verification_stats, which are clearly not search operations.

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 implies this is the tool to use when searching products by text/tag/tier, but it does not explicitly state when to prefer it over siblings or when not to use it. The context is clear by exclusion because siblings have different functional names, but the guidance is implicit rather than stated.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only aggregation operation (no modification implied), but it does not explicitly state side effects, safety, or that it is non-destructive. For a simple aggregation tool this is adequate, but the lack of explicit statements leaves some ambiguity.

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, focused sentence with no unnecessary words. It front-loads the action ('aggregate') and scope ('across the whole board'), then provides specific output details ('tier split and which proof sources are actually used'). Every element earns its place.

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 no parameters and no output schema, the description provides a good understanding of what the tool does and what it returns. It names the two key output dimensions (tier split and proof source usage). However, the exact return format is unspecified, which could leave an agent uncertain about the response structure, though the description gives a reasonable expectation.

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 tool has zero parameters, so the schema already covers everything (100% coverage). The description correctly omits parameter details, and there is nothing to add beyond what the empty schema provides. Per the rubric, a baseline of 4 is appropriate for tools with no parameters.

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 function: aggregating verification data across the entire board, specifying the exact aspects (tier split and proof source usage). The verb 'aggregate' and resource 'verification data' make the purpose unambiguous, and it distinguishes itself from sibling tools by focusing on verification data rather than board activity or product signals.

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 implies when to use the tool (when verification stats are needed) but provides no explicit guidance on alternatives or exclusion criteria. Sibling tools like board_this_week and product_signals are not mentioned, so an agent must infer the appropriate context rather than being given clear routing instructions.

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