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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: the tool returns 'documented', 'sourced and evidence-backed' events, and lists specific event types (firmware regressions, warranty cuts, etc.). However, it lacks details on permissions, rate limits, pagination, or response format.

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, dense sentence with zero waste—every word contributes to clarifying the tool's purpose and scope. It is appropriately sized and front-loaded with the core action.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is largely complete for its purpose. It covers what the tool does and the nature of the data, but lacks output details (e.g., response structure) and some behavioral context (e.g., error handling).

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 description coverage is 100%, so the schema already documents both parameters (slug and severity). The description adds no additional parameter semantics beyond what the schema provides, such as examples or usage nuances, 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's purpose with specific verbs ('Get documented enshittification events') and resources ('for a product'), and distinguishes it from siblings by specifying the type of data returned (evidence-backed degradation events) rather than general product information or listings.

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 clear context for when to use this tool (to retrieve documented product degradation events), but does not explicitly state when not to use it or name alternatives among the sibling tools (urdb_get_product, urdb_list_products, urdb_search).

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 describes the output content (scores, counts) but omits critical behavioral traits like whether this is a read-only operation, rate limits, authentication needs, error handling, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 that front-loads the core action and resource, then details the 7 dimensions and additional data without waste. Every part earns its place by providing essential context, making it appropriately sized and well-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 complexity (detailed multi-dimensional scoring) and lack of annotations and output schema, the description is partially complete. It explains what data is returned but misses behavioral aspects like safety, performance, and response structure. For a tool with no structured output, more guidance on return values would improve completeness.

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 description coverage is 100%, so the schema already documents the single parameter 'slug' with a clear description. The description adds no additional parameter semantics beyond implying it's for a 'specific product', which is redundant with the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 specific action ('Get full integrity breakdown') and resource ('for a specific product'), distinguishing it from siblings like 'urdb_list_products' (list) and 'urdb_search' (search). It explicitly details the 7 dimensions and additional data (change event and recall counts), making the purpose highly specific and differentiated.

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 like 'urdb_list_products' or 'urdb_search'. It implies usage for detailed product analysis but lacks explicit when/when-not instructions or prerequisites, such as needing a product slug from another tool.

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 mentions filtering and sorting capabilities but lacks details on critical behaviors like pagination handling (implied by 'per_page' but not explained), rate limits, authentication needs, or what the output looks like (e.g., list format, error cases). This is a significant gap for a tool with multiple parameters and no output schema.

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 highly concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose and usage examples without any wasted words. It is front-loaded with the core functionality.

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 complexity (5 parameters, no annotations, no output schema), the description is incomplete. It lacks information on behavioral aspects like pagination, error handling, and output format, which are crucial for effective tool invocation. The examples help but don't compensate for these gaps.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by mentioning filtering by 'category, brand, or score range' and providing usage examples, but it doesn't explain parameter interactions or additional semantics. Baseline 3 is appropriate when the schema does the heavy lifting.

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 purpose as 'List products filtered by category, brand, or score range,' which is a specific verb+resource combination. However, it doesn't explicitly distinguish this tool from sibling tools like 'urdb_search' or 'urdb_get_product,' which likely have overlapping or related functionality.

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 clear usage context with examples like 'best integrity laptops' or 'washing machines above 70,' which helps understand when to use this tool. However, it doesn't explicitly state when not to use it or mention alternatives among the sibling tools, such as when to choose 'urdb_search' 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns products with integrity scores (0-100), which is useful context. However, it doesn't disclose important behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or what happens with empty results. The description adds some value but leaves significant gaps.

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 perfectly concise with two sentences that each earn their place. The first sentence states the purpose and output, while the second provides clear usage guidance. There's zero waste or redundancy, and the information is front-loaded appropriately.

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 search tool with 3 parameters, 100% schema coverage, but no annotations and no output schema, the description provides adequate but incomplete context. It covers the purpose and primary use case well, but lacks details about the return format (beyond mentioning integrity scores), error conditions, or behavioral constraints. The description is sufficient for basic use but leaves important operational questions unanswered.

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 description coverage is 100%, so the schema already documents all three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions searching 'by name or keyword' which aligns with the 'q' parameter, but provides no additional syntax, format, or usage details. Baseline 3 is appropriate when the schema does the heavy lifting.

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 purpose with specific verbs ('Search URDB for consumer products') and resources ('consumer products'), and distinguishes it from siblings by mentioning it's for searching by name/keyword rather than getting specific products or lists. It explicitly mentions the integrity score output, which differentiates it from basic search 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?

The description provides explicit guidance on when to use this tool ('Use this first when the user asks about a product or wants product recommendations'), creating a clear priority over other tools. While it doesn't explicitly mention when NOT to use it or name alternatives, the 'first' directive strongly implies this is the primary search tool in the context.

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