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 ('Export') but lacks details on permissions needed, whether it's a read-only or write operation, rate limits, or what the output entails (e.g., file download link, binary data). This is inadequate for a tool with potential side effects like file generation.

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, starting with the core purpose in the first sentence. The parameter explanations are listed efficiently in bullet-point style under 'Args:', though some could be more concise (e.g., 'etc.' in export_type is vague). Overall, it avoids unnecessary verbosity.

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, 0% schema description coverage, and no output schema, the description is incomplete. It covers the basic action and parameters but misses critical behavioral context (e.g., output format, side effects) and usage guidelines relative to siblings. For a 5-parameter tool with potential file operations, this leaves significant gaps for an agent.

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 0%, so the description must compensate. It lists all 5 parameters with brief explanations (e.g., 'Image format (png, svg, etc.)' for export_type), adding basic semantics beyond the schema's titles. However, it doesn't provide deeper context like valid export_type values beyond examples or scale constraints, leaving gaps in 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 ('Export') and resource ('a Penpot design object as an image'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_rendered_component' or 'search_object', which might also involve object retrieval or rendering, 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. With sibling tools like 'get_rendered_component' and 'search_object' available, there's no indication of scenarios where 'export_object' is preferred, such as for image file generation versus in-app viewing, 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists files from the cache, implying a read-only operation, but does not specify details like whether the list is paginated, sorted, filtered, or includes metadata. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's function without unnecessary words. It is front-loaded and efficiently conveys the core purpose, 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 tool has no parameters and no output schema, the description adequately covers the basic purpose. However, it lacks details on behavioral aspects (e.g., output format, caching specifics) and usage guidelines, which are important for an agent to invoke it correctly. The simplicity of the tool means the description is minimally viable 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 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description does not need to add parameter semantics, but it correctly implies no inputs are required. A baseline score of 4 is appropriate as it aligns with the lack of parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('files currently stored in the cache'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_file' or 'get_project_files', which might also retrieve files but from different sources or with 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, such as 'get_file' (which might retrieve a specific file) or 'get_project_files' (which might list files in a project context). There is no mention of prerequisites, exclusions, or recommended contexts 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals two important behavioral traits: 1) the tool caches the retrieved file, and 2) it's specifically not intended for code generation purposes. However, it doesn't mention potential side effects, error conditions, or response format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized with two main sentences and a parameter section. The first sentence states the purpose, the second provides usage guidance, and the Args section documents the parameter. There's minimal waste, though the formatting could be cleaner.

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, no output schema, and 0% schema description coverage, the description provides adequate basics (purpose, usage guidance, parameter meaning) but lacks details about return values, error handling, caching behavior specifics, or authentication requirements that would be helpful for an AI agent.

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 0% schema description coverage, the description must compensate for the lack of parameter documentation. It provides the parameter name 'file_id' and clarifies it's 'The ID of the Penpot file', which adds meaningful context beyond the bare schema. However, it doesn't specify format requirements or validation rules.

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 ('Retrieve a Penpot file by its ID') and resource ('Penpot file'), and distinguishes it from sibling tools by explicitly naming 'get_object_tree' as an alternative for code generation. This provides excellent 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 explicit guidance on when NOT to use this tool ('Don't use this tool for code generation') and names a specific alternative ('use get_object_tree instead'). This gives clear context for tool selection among siblings.

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 describes what the tool returns (tree structure and screenshot) but lacks behavioral details such as whether this is a read-only operation, potential rate limits, authentication needs, error handling, or how the screenshot is generated (e.g., rendering time, size). For a tool with 5 parameters and no annotations, 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 appropriately sized and front-loaded, starting with the core purpose followed by parameter details in a structured list. Every sentence adds value, such as explaining parameter purposes and referencing other tools. Minor improvements could include briefer phrasing, but overall it's efficient and well-organized.

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 5 parameters, no annotations, and no output schema, the description is moderately complete. It covers parameter semantics well and references another tool for schema details, but lacks information on return values, error cases, or behavioral traits. For a tool with this complexity, it should provide more context on output structure and usage constraints 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?

Schema description coverage is 0%, so the description must compensate. It provides clear semantics for all 5 parameters: 'file_id' and 'object_id' identify the target, 'fields' specifies what to include with a reference to another tool, 'depth' controls traversal with -1 meaning full depth, and 'format' sets output format. This adds substantial meaning beyond the bare schema, though it could elaborate on default behaviors beyond the schema's defaults.

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') and the resource ('object tree structure for a Penpot object'), including specific output fields like 'tree' and 'image.mcp_uri'. It distinguishes from siblings like 'get_file' or 'search_object' by focusing on tree structure and screenshot rendering. However, it doesn't explicitly contrast with 'penpot_tree_schema', which is mentioned as a reference tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when needing object tree structure with a rendered screenshot, but doesn't explicitly state when to use this versus alternatives like 'get_file' for basic file info or 'search_object' for finding objects. It references 'penpot_tree_schema' for field details, providing some context, but lacks clear exclusions or comparative guidance with 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves files but doesn't describe return format (e.g., list structure, file metadata), pagination, rate limits, authentication needs, or error conditions. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 concise with two sentences: one for the purpose and one for the parameter. It's front-loaded with the core functionality. However, the formatting includes unnecessary indentation and whitespace, slightly detracting from structure.

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 (a read operation with no annotations, no output schema, and 0% schema coverage), the description is incomplete. It doesn't explain what 'files' means in this context (e.g., file types, metadata), how results are returned, or potential limitations. For a tool that likely returns a list of resources, more context is needed 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 description adds minimal parameter semantics: it explains that 'project_id' is 'The ID of the Penpot project.' With 0% schema description coverage (schema has no descriptions), this provides basic meaning. However, it doesn't clarify format (e.g., UUID), sourcing, or validation rules. Since there's only one parameter, the baseline is 4, but the lack of detail beyond a tautological explanation reduces it to 3.

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: 'Get all files contained within a specific Penpot project.' It specifies the verb ('Get') and resource ('files'), and distinguishes it from siblings like 'get_file' (singular) and 'list_projects' (different resource). However, it doesn't explicitly differentiate from 'get_cached_files' or 'export_object', which could be related operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when-not scenarios, prerequisites, or compare it to siblings like 'get_file' (for a single file) or 'search_object' (for filtered searches). The agent must infer usage from the tool name and description 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 the tool returns an image, but doesn't describe format, size, caching behavior, error handling, or authentication needs. For a tool with zero annotation coverage, this leaves critical behavioral traits unspecified.

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. It's front-loaded with no wasted words, 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 complexity (retrieving rendered images), lack of annotations, no output schema, and low parameter coverage, the description is incomplete. It doesn't address return values, error cases, or operational context, leaving the agent with insufficient information for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions 'component_id' but doesn't explain what a component ID is, its format, or where to find it. With one undocumented parameter, the description adds minimal value beyond the schema's basic structure.

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 ('Return') and resource ('rendered component image by its ID'), making the purpose understandable. However, it doesn't distinguish this tool from siblings like 'get_file' or 'get_cached_files', which might also retrieve files or images, 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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions, leaving the agent without usage instructions. This is a significant gap in helping the agent select the correct tool.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Retrieve a list') but does not cover critical traits like pagination, rate limits, authentication needs, or what 'all available' entails (e.g., permissions, archived projects). This leaves significant gaps for a read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It is front-loaded and appropriately sized for a simple retrieval 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?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. However, it lacks details on return format, pagination, or error handling, which are important for a list retrieval tool, making it incomplete for optimal 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not add parameter details, aligning with the schema's completeness, but could have mentioned implicit constraints like authentication or scope.

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 ('Retrieve') and resource ('list of all available Penpot projects'), making the purpose unambiguous. However, it does not differentiate from sibling tools like 'get_project_files' or 'search_object', which might also involve project retrieval, so it misses full sibling distinction.

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_project_files' or 'search_object'. The description implies a broad retrieval but lacks context on use cases or exclusions, leaving the agent to infer 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but fails to describe key traits such as whether it's a read-only operation, potential rate limits, authentication needs, or what the JSON output structure entails. 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, direct sentence that efficiently conveys the core function without any wasted words. It is front-loaded with the essential information, making it highly concise and well-structured for quick comprehension.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema), the description is minimal but insufficient. It lacks context about the schema's scope (e.g., full API vs. partial), format details, or how it differs from 'penpot_tree_schema'. Without annotations or output schema, more completeness 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?

The tool has zero parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, so it appropriately avoids redundancy. A baseline of 4 is applied since no parameters exist, and the description doesn't mislead about inputs.

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 ('Provide') and resource ('Penpot API schema as JSON'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'penpot_tree_schema', which appears to serve a similar schema-related function, preventing 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 offers no guidance on when to use this tool versus alternatives like 'penpot_tree_schema' or other schema-related operations. It lacks context about prerequisites, timing, or comparisons with sibling tools, leaving the agent without 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 what the tool does but lacks details on traits like whether it's read-only, requires authentication, has rate limits, or returns structured data. For a 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 that directly states the tool's function with zero waste. It is front-loaded and appropriately sized for a simple tool, making it easy for an agent to parse and understand 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 simplicity (0 parameters, no output schema) and lack of annotations, the description is minimally adequate but has clear gaps. It explains what the tool does but omits behavioral context and usage guidelines relative to siblings, making it incomplete for optimal agent decision-making in a server with multiple related 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 tool has 0 parameters, and schema description coverage is 100%, so there is no need for parameter semantics in the description. The baseline for this scenario is 4, as the description appropriately avoids redundant information and focuses on the tool's purpose without unnecessary details.

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 ('Provide') and resource ('Penpot object tree schema as JSON'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'penpot_schema' or 'get_object_tree', which likely serve related but different purposes, preventing 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 offers no guidance on when to use this tool versus alternatives. With sibling tools such as 'penpot_schema' and 'get_object_tree' available, there is no indication of context, prerequisites, or exclusions, 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 the tool searches for objects by name and supports regex patterns, which adds some context. However, it doesn't cover critical aspects like whether this is a read-only operation, what happens if no matches are found, if there are rate limits, or the format of the return value (especially since there's no output schema). For a search tool with zero annotation coverage, this leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, with the main purpose stated first in a clear sentence. The Args section is structured and adds necessary details without redundancy. However, the use of triple quotes and extra whitespace slightly detracts from efficiency, but overall, it's concise and well-organized.

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 2 parameters, no annotations, and no output schema, the description is incomplete. It explains the parameters but lacks information on behavioral traits (e.g., error handling, performance), output format, or how results are returned. Without annotations or an output schema, more context is needed for the agent 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 meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'file_id' is 'The ID of the Penpot file to search in' and 'query' is a 'Search string (supports regex patterns)', providing clarity on their roles. Since the schema only lists titles ('File Id', 'Query') without descriptions, this compensates well, though it doesn't detail constraints like format or length.

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: 'Search for objects within a Penpot file by name.' It specifies the verb ('Search'), resource ('objects within a Penpot file'), and method ('by name'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_object_tree' or 'get_file', which might also retrieve objects or file 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. It mentions searching by name but doesn't compare to siblings like 'get_object_tree' (which might list all objects) or 'get_file' (which might retrieve file metadata). There's no mention of prerequisites, such as needing a valid file ID, or exclusions, leaving the agent to infer usage context.

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