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

With no annotations provided, the description carries full burden for behavioral disclosure. It describes what the tool returns (featured/highlighted products from homepage) but doesn't mention important behavioral aspects like whether results are cached, how frequently they update, authentication requirements, rate limits, or error conditions. The description adds basic context but leaves significant behavioral 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 serve distinct purposes: the first states what the tool does, the second provides usage guidance. There's zero wasted language, and the information is front-loaded with the core functionality stated immediately.

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 zero-parameter tool with no annotations and no output schema, the description provides adequate basic context about what's retrieved and when to use it. However, it doesn't describe the return format, data structure, or what 'featured/highlighted' means operationally. Given the simplicity of the tool, the description is minimally complete but lacks depth about the output.

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 with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and it adds value by explaining what content is retrieved (featured/highlighted Russian software from specific homepage) rather than repeating schema information.

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 verb 'Get' and resource 'list of featured/highlighted Russian software products' with specific location context 'shown on the каталогпо.рф homepage'. It distinguishes from sibling tools by focusing on featured homepage content rather than listing manufacturers or general searching, though it doesn't explicitly name the siblings for comparison.

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: 'Good starting point when unsure what to search for.' This gives practical guidance about when this tool is appropriate versus when to use search tools. However, it doesn't explicitly mention when NOT to use it or name specific alternative tools like 'search_russian_software'.

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 pagination and specific return data (product counts, 3 preview products), which is helpful. However, it doesn't disclose important behavioral aspects like rate limits, authentication requirements, error conditions, or what happens when no manufacturers match.

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 - two sentences that each earn their place. The first sentence states the core functionality with key details, and the second sentence provides usage context. No wasted words or redundant information.

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 listing tool with 2 well-documented parameters and no output schema, the description provides adequate context about what the tool returns. However, without annotations and with no output schema, it could benefit from more detail about the response structure, error handling, or performance characteristics.

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 has 100% description coverage, so parameters are well-documented in the structured schema. The description doesn't add any parameter-specific information beyond what's already in the schema (page and limit parameters with their constraints). This 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 clearly states the verb 'List' and resource 'Russian software manufacturers' with specific details about what's included (product counts, 3 preview products each). It distinguishes from sibling tools by focusing on manufacturers rather than software products, though it doesn't explicitly name the siblings for comparison.

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 about when to use this tool ('useful to discover vendors for a category, or see who is most active in the registry'), which helps differentiate it from the sibling tools that focus on software rather than manufacturers. However, it doesn't explicitly state when NOT to use it or name the alternative tools.

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 effectively describes what the tool does (search and return products with specific fields), mentions key contextual details like certification and compatibility, and implies it's a read-only operation without destructive effects. It lacks explicit details on rate limits or error handling, but provides sufficient behavioral context for a tool with no 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?

The description is appropriately sized and front-loaded, with two sentences that efficiently convey the tool's purpose, output, and usage context without any wasted words. Each sentence adds clear value, making it highly concise 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 moderate complexity (search with two parameters), no annotations, and no output schema, the description does a good job of covering key aspects like purpose, output fields, and usage context. It could improve by detailing the return format or error cases, but it provides enough information for effective use, especially with the well-documented input schema.

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 input schema has 100% description coverage, clearly documenting both parameters ('query' and 'limit') with details like language support and range constraints. The description does not add any additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 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 specific action ('Full-text search'), resource ('Russian software catalog'), and scope ('каталогпо.рф'), distinguishing it from sibling tools like 'get_featured_russian_software' and 'list_russian_manufacturers' by focusing on search functionality rather than listing featured items or manufacturers.

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 usage ('Use for import-substitution: find Russian alternatives to foreign software'), which helps guide when to use this tool. However, it does not explicitly state when not to use it or name specific alternatives among the sibling tools, keeping it from a perfect score.

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