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 retrieves a glyph, implying a read-only operation, but doesn't disclose behavioral traits such as error handling (e.g., for invalid icon names), performance (e.g., response time), or output format (e.g., Unicode character details). This is a significant gap 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 front-loads the core purpose without unnecessary details. Every word contributes to understanding the tool's function, 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a Unicode string, error messages) or behavioral aspects like idempotency or side effects. For a tool with two required parameters and no structured output, more context is needed to ensure reliable use by 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 100%, with clear descriptions for both parameters, including an enum for 'style'. The description adds no additional meaning beyond the schema, such as explaining icon naming conventions or style implications. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema adequately documents the 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 action ('Get') and the resource ('glyph for a specific icon with a particular style'), making the purpose understandable. It distinguishes from siblings like 'list_icons' or 'search_icons' by focusing on retrieving a single glyph. However, it doesn't explicitly differentiate from 'get_icon_glyphs' (plural), which might be a batch version, leaving some ambiguity.

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_icon_glyphs', 'list_icons', or 'search_icons'. It lacks context about prerequisites (e.g., needing valid icon names) or exclusions, leaving the agent to infer usage from the tool name and parameters 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 what the tool does but does not disclose behavioral traits such as whether it's a read-only operation, potential rate limits, error handling, or the format of returned data. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that front-loads the key information ('Get all glyphs...') without any wasted words. It is appropriately sized for the tool's complexity and earns its place by clearly stating the purpose and scope.

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 (1 parameter, no output schema, no annotations), the description is minimally complete. It states the purpose but lacks details on behavioral aspects like data format or error handling. Without annotations or an output schema, the description should do more to compensate, but it meets the basic requirement for a simple lookup tool.

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 parameter 'icon_name' fully documented in the schema. The description adds no additional meaning beyond the schema, such as examples of valid icon names beyond those in the schema or constraints. Since the schema does the heavy lifting, 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 the resource 'glyphs (unicode characters) for a specific icon across all available styles', making the purpose specific and actionable. It distinguishes from sibling tools like 'get_icon_glyph_by_style' (which likely gets glyphs for a single style) and 'list_icons' (which lists icons rather than glyphs), providing clear 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 implies usage when needing glyphs for a specific icon across all styles, but does not explicitly state when to use this tool versus alternatives like 'get_icon_glyph_by_style' or 'search_icons'. It provides clear context (e.g., 'for a specific icon') but lacks explicit exclusions or named alternatives, falling short of a perfect score.

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. It states the tool 'gets' instructions, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns structured data vs. text, or handles errors. For a tool with no annotation coverage, 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 front-loads the core purpose without unnecessary words. It directly states the action ('Get'), target ('platform-specific usage instructions'), and subject ('Hugeicons'), with zero redundancy or fluff. Every word earns its place.

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

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

Given no annotations, no output schema, and a single parameter with full schema coverage, the description is incomplete. It doesn't explain what the output looks like (e.g., text, JSON, examples), how to interpret results, or error handling. For a tool that presumably returns instructional content, more context on 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 the parameter 'platform' fully documented in the schema including its enum values. The description doesn't add any parameter semantics beyond what the schema provides, such as explaining what 'usage instructions' mean for each platform or default behaviors. Baseline 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 states the tool's purpose as retrieving 'platform-specific usage instructions for Hugeicons', which is clear but vague. It specifies the resource ('usage instructions') and target ('Hugeicons'), but lacks detail on what these instructions entail or how they differ from general documentation. It distinguishes from siblings by focusing on platform guidance rather than icon retrieval, but could be more specific about the output format or content 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, context for platform selection, or how it relates to sibling tools like list_icons or search_icons. Without explicit when/when-not instructions or named alternatives, users must infer usage from the purpose 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 the action but doesn't add context about what 'all available' entails (e.g., pagination, rate limits, authentication needs, or response format). This leaves significant gaps for a tool that likely returns a large dataset.

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 fluff. It's front-loaded and appropriately sized for a simple tool, earning its place with zero waste.

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 list operation with no output schema) and lack of annotations, the description is incomplete. It doesn't address behavioral aspects like response format, data volume, or potential limitations, which are crucial for an agent to use this 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, aligning with the schema. A baseline of 4 is applied since it doesn't add unnecessary information.

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

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

The description clearly states the verb 'Get' and the resource 'list of all available Hugeicons icons', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_icons' or 'get_icon_glyphs', which prevents 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 like 'search_icons' or 'get_icon_glyphs'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent with minimal 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 describes the search functionality but lacks details on behavioral traits such as whether the search is case-sensitive, how results are returned (e.g., pagination, format), rate limits, or error handling. The description adds minimal context beyond the basic action, leaving 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 concise and well-structured in two sentences: the first states the purpose, and the second provides usage guidance with an example. Every sentence earns its place by adding clarity and practical information without unnecessary details, making it front-loaded and efficient.

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 (a search function with one parameter) and no output schema or annotations, the description is adequate but incomplete. It covers the basic purpose and parameter usage but lacks details on output format, error cases, or integration with sibling tools. For a search tool without structured output information, more context on what to expect from results would improve completeness.

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

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

The input schema has 100% description coverage, with the 'query' parameter documented as 'Search query to find relevant icons. Separate multiple searches with commas.' The description adds value by providing an example ('e.g., 'home, notification, settings'') that clarifies the format for multiple searches, but it does not significantly expand on the schema's semantics. With high schema coverage, the baseline is 3, as the description compensates slightly but not substantially.

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 icons by name or tags.' It specifies the verb ('Search') and resource ('icons'), and mentions the search criteria ('by name or tags'). However, it does not explicitly differentiate from sibling tools like 'list_icons' or 'get_icon_glyphs', which might offer alternative ways to retrieve icons.

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 implied usage guidance by mentioning how to search for multiple icons ('Use commas to search for multiple icons'), which suggests this tool is for filtered searches. However, it does not explicitly state when to use this tool versus alternatives like 'list_icons' (which might list all icons without filtering) or 'get_icon_glyphs' (which might retrieve specific icon data). No exclusions or clear alternatives are named.

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