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

No annotations are provided, so the description carries full burden. It mentions 'bulk' but doesn't disclose behavioral traits such as rate limits, authentication needs, performance implications, error handling for partial failures, or what the output looks like. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves operationally.

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 ('Search for multiple asset queries') and qualifies it with 'in bulk'. There is zero waste—every word contributes to understanding the tool's scope without redundancy or fluff.

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 no annotations, no output schema, and a tool that performs search operations (which can have complex behaviors like pagination, sorting, or error handling), the description is incomplete. It doesn't address return values, performance considerations, or how results are structured for bulk queries. For a tool with potential complexity, more context is needed to guide effective use.

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 fully documents the 'assets' parameter and its nested properties. The description adds no additional meaning beyond implying bulk processing, which is already suggested by the array structure. Baseline 3 is appropriate as the schema does the heavy lifting, but the description doesn't compensate or clarify nuances like query syntax or result ordering.

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 ('Search') and resource ('multiple asset queries'), specifying it handles multiple queries in bulk. It distinguishes from siblings like 'search_assets' (singular) and 'search_relevant_assets' (different scope), though it doesn't explicitly name these alternatives. The purpose is specific but could be more precise about what 'asset' refers to in this context.

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?

No guidance is provided on when to use this tool versus alternatives like 'search_assets' or 'search_relevant_assets'. The description implies bulk processing but doesn't specify thresholds (e.g., use for >5 queries) or exclusions. Without context on trade-offs or prerequisites, the agent lacks clear usage direction.

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 states the action ('Get replies') but does not describe key behaviors like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or the format of returned data. This leaves significant gaps for an agent to understand how to invoke it safely and effectively.

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, direct sentence ('Get replies to a specific comment') that is front-loaded and wastes no words. It efficiently conveys the core purpose without unnecessary elaboration, making it highly concise and well-structured for quick understanding.

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 (fetching replies with pagination via limit/offset), lack of annotations, and absence of an output schema, the description is insufficient. It does not address behavioral aspects like pagination mechanics, data format, error cases, or how it integrates with sibling tools, leaving the agent with incomplete context for reliable use.

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 all parameters (project_id, comment_id, limit, offset) with their types, defaults, and purposes. The description adds no additional semantic information beyond what the schema provides, such as explaining relationships between parameters or usage nuances, so it meets the baseline for high schema coverage without compensating further.

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 'Get replies to a specific comment' clearly states the verb ('Get') and resource ('replies to a specific comment'), making the purpose immediately understandable. However, it does not explicitly differentiate this tool from sibling tools like 'get_project_comments', which might fetch comments rather than replies, leaving some ambiguity about sibling relationships.

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, such as 'get_project_comments' for fetching comments instead of replies, or how it relates to other comment-related operations. It lacks explicit context, prerequisites, or exclusions, offering minimal usage direction.

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 full burden for behavioral disclosure but offers minimal information. It doesn't mention whether this is a read-only operation, what authentication might be required, rate limits, pagination behavior beyond the parameters, or what format the returned posts will have. The description only states what the tool does at a high level.

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 communicates the core purpose without any wasted words. It's appropriately sized for a simple retrieval tool and gets straight to the point.

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 feed retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'posts' contain, what 'WebSim feed' refers to, the return format, or any behavioral characteristics. The agent would need to guess about the nature of the returned data and operational constraints.

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 with clear documentation for both 'limit' and 'offset' parameters. The description doesn't add any additional semantic context about these parameters beyond what's already in the schema, so it meets the baseline expectation when schema coverage is complete.

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 the resource 'latest posts from WebSim feed', making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get_trending_feed' or 'search_feed', which appear to serve similar feed-related functions.

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 'get_trending_feed' or 'search_feed'. There's no mention of prerequisites, context, or comparison with sibling tools, leaving the agent to guess about appropriate usage scenarios.

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 states a read operation ('Get') but does not mention permissions, rate limits, pagination, error handling, or what the return format looks like. For a tool with no annotations, 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 directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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 lack of annotations and no output schema, the description is incomplete. It does not explain what 'assets' entail, the return structure, or any behavioral aspects like safety or performance. For a tool with no structured support, the description should provide more context to be fully helpful.

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, with clear documentation for both parameters (project_id and version). The description adds no additional semantic details beyond what the schema provides, such as format examples or constraints, 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 clearly states the verb 'Get' and the resource 'assets for a specific project version', which is specific and actionable. However, it does not distinguish this tool from sibling tools like 'search_assets' or 'search_relevant_assets', which might also retrieve assets, so it lacks sibling differentiation.

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 'search_assets' or 'list_all_projects'. It implies usage for a specific project version but offers no exclusions, prerequisites, or explicit comparisons to other 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 only states the basic action ('Get') without detailing whether this is a read-only operation, what permissions are needed, how errors are handled, or what the return format looks like. This leaves significant gaps for a tool that presumably fetches data.

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 directly states the tool's purpose without any unnecessary words. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what data is returned (e.g., project details, structure), potential errors, or behavioral traits like idempotency or rate limits, which are important for a data-fetching tool in a context with many sibling tools.

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, with the single parameter 'project_id' documented as 'WebSim project ID'. The description adds no additional meaning beyond this, so it meets the baseline of 3 where 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 verb ('Get') and resource ('a WebSim project'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'get_project_by_slug' or 'list_all_projects', which would require explicit differentiation for a score of 5.

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 doesn't mention when to choose 'get_project_by_id' over 'get_project_by_slug' or 'list_all_projects', nor does it specify any prerequisites or exclusions for usage.

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 full burden. It states it's a read operation ('Get'), implying non-destructive behavior, but doesn't disclose error conditions, authentication needs, rate limits, or what happens if the project doesn't exist. For a tool with zero annotation coverage, this is insufficient.

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 purpose without unnecessary words. Every part earns its place, 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 low complexity (2 required parameters, no output schema, no annotations), the description is minimally adequate but lacks completeness. It doesn't explain return values or error handling, which are crucial for a retrieval tool, leaving gaps in contextual understanding.

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%, with both parameters ('user' as 'Username' and 'slug' as 'Project slug') documented in the schema. The description adds no additional meaning beyond implying these are required for lookup, so it meets the baseline of 3 without compensating further.

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 ('a WebSim project'), specifying it's retrieved by user and slug. However, it doesn't distinguish this from sibling tools like 'get_project_by_id' or 'list_user_projects', which would require explicit differentiation for a score of 5.

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?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'get_project_by_id' and 'list_user_projects', the description lacks any context on prerequisites, use cases, or exclusions, leaving the agent without direction.

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 full burden for behavioral disclosure. While 'Get' implies a read operation, the description doesn't mention authentication requirements, rate limits, pagination behavior (beyond what's in the schema), error conditions, or what format the comments are returned in. For a tool with 3 parameters and no output schema, this 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 a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a straightforward retrieval tool and front-loads the essential information. Every word earns its place with zero 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?

Given the tool has 3 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the returned comments look like, how they're structured, whether they include metadata like timestamps or authors, or any behavioral constraints. For a data retrieval tool without output schema, more context about the return format is needed.

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%, with all parameters well-documented in the schema itself. The description doesn't add any additional parameter context beyond what's already in the schema (project_id, limit with default, offset with default). This meets the baseline expectation when schema coverage is complete, but provides no extra semantic value.

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 ('comments for a WebSim project'), making the purpose immediately understandable. It distinguishes this tool from other comment-related tools like 'get_comment_replies' by specifying it retrieves project comments rather than replies. However, it doesn't explicitly differentiate from all sibling tools beyond this basic scope.

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. With sibling tools like 'get_comment_replies' and 'get_posts_feed' available, there's no indication whether this tool is for initial comment retrieval versus specialized scenarios. No prerequisites, exclusions, or comparative context are mentioned.

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 states the action ('Get projects') but lacks details on permissions, rate limits, pagination behavior (beyond schema defaults), or response format. This is inadequate for a tool with 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for its function, with zero wasted content.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'descendants' entail (e.g., nested projects), return values, or error conditions. For a tool with parameters and potential complexity in hierarchical data, more context is needed to guide the agent effectively.

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 fully documents the parameters (project_id, limit, offset). The description adds no additional meaning beyond implying the tool operates on WebSim projects, which is already covered in the schema. Baseline 3 is appropriate as the schema handles parameter semantics effectively.

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 ('projects that are descendants of a WebSim project'), making the purpose understandable. It distinguishes from some siblings like 'get_project_by_id' or 'list_all_projects' by specifying descendant retrieval, though it doesn't explicitly differentiate from all similar tools like 'list_user_projects' in terms of scope.

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 doesn't mention prerequisites, exclusions, or compare it to sibling tools like 'list_all_projects' or 'list_user_projects' for context, leaving the agent to infer usage based on the name alone.

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 full burden. It states 'Get all revisions' but doesn't disclose behavioral traits like whether this is a read-only operation, if it requires authentication, what the return format looks like (e.g., list of objects with timestamps), or any rate limits. The description is minimal and lacks essential operational context.

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 directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'revisions' are, what data they include, or the return format, leaving significant gaps for an AI agent to understand how to interpret results or handle errors.

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%, with all parameters (project_id, limit, offset) well-documented in the schema. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't clarify what 'revisions' entail or how parameters interact with them), 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 clearly states the action ('Get all revisions') and resource ('of a WebSim project'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from potential siblings like 'get_project_by_id' or 'list_all_projects' in terms of what 'revisions' specifically means versus general project data.

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. With siblings like 'get_project_by_id' and 'list_all_projects' available, there's no indication of whether this is for version history, audit trails, or other revision-specific contexts, nor any prerequisites or exclusions mentioned.

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 states 'Get statistics' but doesn't clarify if this is a read-only operation, what permissions might be required, whether it's cached or real-time, or if there are rate limits. For a tool with zero annotation coverage, this leaves significant behavioral gaps, though it at least implies a non-destructive read.

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 purpose ('Get statistics for a WebSim project'). There's no wasted verbiage or redundancy, making it immediately scannable and appropriately sized for a simple tool with one parameter.

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 lack of annotations and output schema, the description is incomplete for a tool that likely returns complex statistical data. It doesn't hint at the structure or types of statistics returned (e.g., numeric metrics, time-series data), which could be critical for an AI agent to interpret results. With no structured fields to rely on, the description should do more to set expectations.

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, with the 'project_id' parameter fully documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 ('statistics for a WebSim project'), making the purpose immediately understandable. It distinguishes from siblings like 'get_project_by_id' or 'get_project_assets' by focusing on statistics rather than project metadata or assets. However, it doesn't specify what types of statistics are included (e.g., usage metrics, performance data), keeping it from a perfect score.

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. With siblings like 'get_project_by_id', 'get_project_assets', and 'get_user_stats', there's no indication of whether this tool is for aggregated data, real-time metrics, or historical trends. It lacks explicit when/when-not instructions or named alternatives, leaving usage context unclear.

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 states what the tool does but lacks details on aspects like rate limits, authentication needs, error handling, or the format of returned keywords. For a tool with no annotation coverage, this is a significant gap in transparency.

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 directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it easy for an agent to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'related keywords' means in practice, how they are generated, or what the return format looks like. For a tool with no structured output information, more context is needed to guide the agent effectively.

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 a default). The description doesn't add any semantic details beyond what the schema provides, such as examples or constraints, so it meets the baseline score 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 'get' and the resource 'keywords related to a search query', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_top_searches' or 'search_relevant_assets', which might have overlapping functionality, so it doesn't reach the highest score.

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 such as 'search_relevant_assets' or 'get_top_searches'. There's no mention of specific contexts, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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 full burden for behavioral disclosure but only states what the tool does, not how it behaves. It doesn't mention whether this is a read-only operation, if it requires authentication, rate limits, what format the results come in, or any other behavioral characteristics.

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, clear sentence with no wasted words. It's appropriately sized for a simple retrieval tool and gets straight to the point without unnecessary elaboration.

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 annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'top search queries' means (by what metric? over what timeframe?), what the return format looks like, or any behavioral constraints. The agent would be left guessing about important operational details.

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?

With 100% schema description coverage, the input schema already fully documents both parameters (limit and offset). The description adds no additional parameter information beyond what's in the schema, so it meets the baseline but doesn't provide extra value.

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 the resource 'top search queries on WebSim', making the purpose immediately understandable. However, it doesn't differentiate from siblings like 'get_trending_feed' or 'search_assets' which might also involve search-related data retrieval.

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. With siblings like 'search_assets', 'search_feed', and 'get_trending_feed' that might overlap in functionality, there's no indication of what makes this tool distinct or when it's the appropriate choice.

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 full burden. It mentions 'Get' which implies a read operation, but doesn't disclose behavioral traits like rate limits, authentication needs, or what 'trending' entails (e.g., algorithm, time frame). This is inadequate for a tool with no 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 that directly states the tool's purpose with no wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 low complexity (simple read operation with two parameters), 100% schema coverage, and no output schema, the description is minimally adequate. However, it lacks details on behavioral aspects and sibling differentiation, which could improve completeness for agent use.

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%, with clear descriptions for 'limit' and 'offset' parameters. The description doesn't add any meaning beyond the schema, such as explaining how 'trending' might affect pagination, so it meets the baseline for high coverage without extra value.

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 the resource 'trending WebSim projects feed', making the purpose understandable. However, it doesn't differentiate from siblings like 'get_posts_feed' or 'search_feed', which might also retrieve feeds, so it's not fully specific to sibling context.

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?

No guidance is provided on when to use this tool versus alternatives such as 'get_posts_feed' or 'search_feed'. The description only states what it does without context, leaving the agent to infer usage based on tool names alone.

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 states 'Get trending WebSim rooms' but doesn't explain what 'trending' means, whether this is a read-only operation, how results are sorted, or any rate limits or authentication needs. This leaves significant gaps in understanding the tool's 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 with no wasted words. It's front-loaded with the core purpose, making it easy to scan and understand quickly without unnecessary elaboration.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'trending' entails, the return format, or any behavioral traits like pagination or sorting. For a tool with no structured metadata, this minimal description leaves too many open questions about how to use it effectively.

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, with clear documentation for 'limit' and 'offset' parameters including defaults. The description adds no additional semantic information beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without compensating value.

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 'Get trending WebSim rooms' clearly states the verb 'Get' and resource 'trending WebSim rooms', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_trending_feed' or 'get_posts_feed', which might have overlapping domains but different scopes.

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 doesn't mention sibling tools like 'get_trending_feed' or 'search_feed' that might serve similar purposes, nor does it specify any prerequisites or contextual cues for selection.

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 states the action ('Get details') but does not cover critical aspects like whether this is a read-only operation, authentication requirements, rate limits, error handling, or the format of returned details. This leaves significant gaps for an agent to understand the tool's 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 directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It does not explain what 'details' are returned, how errors are handled, or any behavioral traits. For a tool that likely involves user data retrieval, more context on response structure and operational constraints is needed.

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, with the parameter 'user' documented as 'Username'. The description does not add any additional meaning beyond this, such as format examples or constraints. Since the schema already provides adequate documentation, the baseline score of 3 is appropriate.

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 ('WebSim user'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_user_followers' or 'get_user_stats', which also retrieve user-related data but focus on different aspects.

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, such as 'search_users' for broader queries or 'get_user_followers' for social data. It lacks any context on prerequisites, exclusions, or specific scenarios where this tool is preferred.

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 states it 'gets' followers, implying a read-only operation, but doesn't specify permissions required, rate limits, pagination behavior beyond the schema's limit/offset, or what the return format looks like (e.g., list of usernames or user objects). This leaves significant gaps for a tool with 3 parameters.

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 purpose without any wasted words. It's appropriately sized for a straightforward retrieval tool, making it easy for an agent to parse quickly.

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 has 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the return values (e.g., structure of follower data), error conditions, or usage context relative to siblings. For a data retrieval tool in a social context, this leaves the agent under-informed about behavioral aspects.

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 fully documents the parameters (user, limit, offset). The description adds no additional meaning beyond implying the 'user' parameter identifies a WebSim user, which is already clear from the schema's description. 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 ('Get') and resource ('followers of a specific WebSim user'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_user_following' or 'get_user', which could retrieve related user data, so it doesn't reach the highest score.

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. For example, it doesn't mention when to choose 'get_user_followers' over 'get_user_following' (which likely retrieves users being followed) or 'get_user' (which might include follower data), leaving the agent to infer usage from context alone.

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 states it's a read operation ('Get'), but lacks details on permissions, rate limits, pagination behavior (beyond implied by limit/offset), error handling, or response format. This is a significant gap for a tool with 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, 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 has 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like response format, error cases, or usage context, leaving gaps that could hinder an AI agent's ability to use the tool effectively.

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 description adds no parameter semantics beyond what the input schema provides, which has 100% coverage with clear descriptions for 'user', 'limit', and 'offset'. The baseline score of 3 is appropriate since the schema adequately documents the parameters, though the description doesn't enhance understanding.

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 the resource 'users that a specific user is following', making the purpose unambiguous. However, it doesn't explicitly differentiate from its sibling 'get_user_followers', which retrieves followers rather than following, though this distinction is implied by the tool names.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, such as whether the user must exist or be public, or contrast it with similar tools like 'get_user_followers' or 'search_users' for broader user queries.

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 full burden for behavioral disclosure. It states this is a 'Get' operation (implying read-only), but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what format the statistics are returned in. For a statistics tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.

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 communicates the core purpose without any wasted words. It's appropriately sized for a simple tool with one parameter and gets straight to the point. Every word earns its place in this minimal but complete statement of function.

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 lack of annotations, no output schema, and the description's minimalism, this is incomplete for a statistics tool. The description doesn't explain what statistics are returned, their format, or any behavioral considerations. While the purpose is clear, the context needed for effective tool selection and invocation is insufficient, especially compared to richer sibling tools in the same server.

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 coverage is 100% with the single parameter 'user' documented as 'Username'. The description adds no additional parameter semantics beyond what the schema already provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 'statistics for a specific WebSim user', making the purpose immediately understandable. It distinguishes from siblings like 'get_user' or 'get_user_followers' by focusing on statistics rather than basic user info or social connections. However, it doesn't specify what types of statistics are included, keeping it from a perfect score.

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. With siblings like 'get_user' (likely basic user info), 'get_user_followers/following' (social data), and 'get_project_stats' (project-level statistics), there's clear potential for confusion about which tool to select for different statistical needs. The description offers no when/when-not guidance or named alternatives.

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 full burden for behavioral disclosure. While 'Check' implies a read-only operation, it doesn't specify what 'accessible' means (e.g., network connectivity, authentication status, service health), what the response format might be, or any error conditions. This 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 a single, clear sentence that states the core purpose without any wasted words. It's perfectly front-loaded and appropriately sized for a simple health check tool.

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 health check tool with no output schema, the description is minimally adequate. It states what the tool does but lacks details about what constitutes 'accessible' or what the response contains. Given the simplicity of the tool, it's complete enough to be functional but could be more informative.

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, and the input schema has 100% description coverage (though empty). The description appropriately doesn't discuss parameters, which is correct for a no-parameter tool, earning a high baseline score.

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 a specific verb ('Check') and resource ('WebSim API accessibility'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools, which are all data retrieval operations, so it falls short of a perfect score.

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 doesn't mention prerequisites, timing considerations, or how it differs from the many sibling data-fetching tools, leaving the agent with no usage context.

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' (via limit/offset parameters) and specifies 'public' projects, which adds useful context about scope and data access. However, it does not cover other behavioral aspects like rate limits, authentication needs, or error handling.

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 key information ('List all public WebSim projects with pagination') without unnecessary details. Every word contributes to understanding the tool's function.

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 low complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the core action and pagination but lacks details on return values, error cases, or integration with sibling tools, leaving gaps for an AI agent to infer usage.

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, fully documenting the 'limit' and 'offset' parameters with defaults. The description adds no additional parameter semantics beyond what the schema provides, such as format details or constraints, 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 clearly states the action ('List all') and resource ('public WebSim projects'), making the purpose understandable. However, it does not explicitly differentiate from siblings like 'list_user_projects' or 'get_project_by_id', which would require mentioning scope limitations or 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?

The description provides no guidance on when to use this tool versus alternatives such as 'list_user_projects' for user-specific projects or 'search_feed' for filtered results. It lacks explicit when/when-not instructions or prerequisite contexts.

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 only states the basic action without mentioning permissions, rate limits, pagination behavior (implied by limit/offset but not explained), or response format. This leaves significant gaps for a tool with parameters.

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 zero wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like permissions, rate limits, or response structure, which are important for a tool that lists user-specific data with pagination parameters.

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 fully documents all parameters (user, limit, offset). The description adds no additional parameter semantics beyond what's in the schema, resulting in the baseline score 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 ('projects for a specific user'), making the purpose understandable. However, it doesn't distinguish from sibling tools like 'list_all_projects' or 'get_project_by_id', which would require explicit differentiation for a perfect score.

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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention when to choose 'list_user_projects' over 'list_all_projects' or 'get_project_by_id', nor does it specify 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 provided, so the description carries the full burden of behavioral disclosure. While 'Search' implies a read-only operation, the description doesn't mention any behavioral traits such as rate limits, authentication requirements, pagination behavior, or what constitutes a 'WebSim asset'. For a search tool with zero annotation coverage, this is a significant gap in transparency.

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 zero wasted words. It's appropriately sized and front-loaded with the core purpose, making it easy for an AI agent to parse quickly. Every word earns its place by conveying essential information without 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?

Given the complexity of a search operation with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'WebSim assets' are, how results are structured, or behavioral aspects like pagination or error handling. For a tool with multiple siblings and no structured output documentation, more context is needed to ensure proper usage.

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, with clear documentation for 'query', 'limit', and 'offset' parameters. The description adds no additional semantic meaning beyond what the schema provides (e.g., it doesn't explain query syntax, result ordering, or what 'assets' include). With high schema coverage, a baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

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 'Search for WebSim assets' clearly states the verb ('Search') and resource ('WebSim assets'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'search_feed', 'search_relevant_assets', or 'bulk_asset_search', leaving ambiguity about when to use this specific search tool versus 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?

The description provides no guidance on when to use this tool versus alternatives. With multiple search-related siblings (e.g., 'search_feed', 'search_relevant_assets', 'bulk_asset_search'), there's no indication of context, prerequisites, or exclusions. This lack of differentiation could lead to incorrect tool selection by an AI agent.

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. While 'Search' implies a read-only operation, the description doesn't mention important behavioral aspects like whether this is a paginated search, what authentication might be required, rate limits, or what the response format looks like. For a search tool with zero annotation coverage, this is a significant gap.

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 extremely concise at just 6 words, front-loading the core purpose ('Search WebSim feed') and efficiently adding the key feature ('with sorting options'). Every word earns its place with zero waste or 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?

Given that this is a search tool with no annotations, no output schema, and multiple similar sibling tools, the description is insufficiently complete. It doesn't explain what 'WebSim feed' contains, how results are returned, or how this differs from other search/feed tools in the server. The agent would need to guess about important contextual details.

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 description mentions 'sorting options' which aligns with the 'sort' parameter in the schema, but doesn't add meaningful semantic context beyond what's already documented in the input schema (which has 100% description coverage). The baseline score of 3 is appropriate since the schema does the heavy lifting of parameter documentation.

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 a specific verb ('Search') and resource ('WebSim feed'), and mentions 'with sorting options' which adds useful context. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_trending_feed' or 'search_assets', which would require a 5.

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. With multiple sibling tools like 'get_trending_feed', 'search_assets', and 'search_relevant_assets', there's no indication of what makes this tool distinct or when it should be preferred over those options.

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. It states the tool searches for assets, implying a read-only operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or what 'relevant' means in terms of ranking. This leaves significant gaps for an agent.

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 zero waste. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary details, earning its place concisely.

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 (search operation with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain return values, error handling, or behavioral context, making it inadequate for an agent to fully understand the tool's usage.

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%, with clear documentation for 'query' and 'limit' parameters. The description adds no meaning beyond the schema, as it doesn't explain parameter semantics like query syntax or limit constraints. Baseline score of 3 is appropriate since 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 'Search for assets relevant to a query' clearly states the verb ('search') and resource ('assets'), but it's vague about what 'assets' are and doesn't distinguish from siblings like 'search_assets' or 'bulk_asset_search'. It provides a basic purpose but lacks specificity.

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?

No guidance is provided on when to use this tool versus alternatives such as 'search_assets' or 'bulk_asset_search'. The description implies usage for searching assets with a query, but there's no explicit context, exclusions, or comparison to sibling 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Search for WebSim users' implies a read-only operation, but it doesn't describe what the search returns (e.g., user profiles, IDs), whether it's paginated (though parameters suggest it), authentication requirements, rate limits, or error conditions. The description is too minimal to adequately inform the agent about behavioral traits beyond the basic action.

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 extremely concise at just four words, with no wasted language. It's front-loaded with the core action. However, it's arguably too brief, bordering on under-specified rather than efficiently informative. Still, every word earns its place by stating the essential purpose.

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 pagination parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the search returns, how results are ordered, error handling, or authentication needs. For a search tool with three parameters and no structured output documentation, the description should provide more context about the operation's behavior and results.

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%, with all parameters (query, limit, offset) well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain what the query searches against or format examples). Given the high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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 'Search for WebSim users' clearly states the verb (search) and resource (WebSim users), making the basic purpose understandable. However, it doesn't distinguish this tool from sibling search tools like search_assets or search_feed, nor does it specify what kind of search this performs (e.g., by name, email, username). The purpose is clear but lacks differentiation from similar 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 no guidance on when to use this tool versus alternatives. There are multiple sibling tools for getting user information (get_user, get_user_followers, get_user_following, get_user_stats) and other search tools, but the description doesn't indicate whether this is for finding users by name, for paginated browsing, or when to prefer this over get_user. No usage context or exclusions are mentioned.

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