Hugeicons

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: list_icons provides a full catalog, search_icons finds specific icons, get_icon_glyphs retrieves all glyphs for an icon, get_icon_glyph_by_style gets a specific glyph, and get_platform_usage offers usage instructions. The descriptions make boundaries explicit, preventing misselection.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case: get_icon_glyph_by_style, get_icon_glyphs, get_platform_usage, list_icons, and search_icons. The naming is predictable and readable throughout the set.
Tool Count5/5
With 5 tools, the count is well-scoped for an icon library server, covering core operations like listing, searching, retrieving glyphs, and usage instructions. Each tool earns its place without being too sparse or bloated.
Completeness4/5
The tool set covers key workflows: discovery (list_icons, search_icons), retrieval (get_icon_glyphs, get_icon_glyph_by_style), and usage (get_platform_usage). A minor gap is the lack of metadata tools (e.g., get_icon_details or list_styles), but agents can work around this with the provided tools.
Average 3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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. The description only states what the tool does ('Get...instructions') without detailing behavioral traits such as whether it's read-only, requires authentication, has rate limits, or what the output format looks like. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple parameter but unclear output), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't provide enough context for an agent to understand what 'usage instructions' entail, how they're returned, or any behavioral aspects, making it inadequate for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, and the description doesn't add any meaning beyond the schema. It doesn't explain what 'platform' means (e.g., possible values like 'web', 'mobile', or specific platforms), its format, or constraints. With low schema coverage, the description fails to compensate, leaving the parameter poorly documented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Get platform-specific usage instructions for Hugeicons', which provides a clear verb ('Get') and resource ('usage instructions'), but it's somewhat vague about what 'usage instructions' entail. It doesn't differentiate from sibling tools like 'get_icon_glyph_by_style' or 'list_icons', which focus on icons rather than platform usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 any context, prerequisites, or exclusions, leaving the agent to infer usage based on the name alone. This lack of explicit guidance reduces effectiveness in tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Get[s] the glyph', implying a read-only operation, but doesn't disclose any behavioral traits such as error handling, performance characteristics, or what happens if the icon/style combination doesn't exist. This leaves significant gaps for an agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (2 required parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what a 'glyph' or 'unicode character' entails in the return value, nor does it provide context on parameter usage or error cases. This leaves the agent with insufficient information to use the tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It mentions 'icon_name' and 'style' implicitly, but doesn't add meaningful semantics beyond what's obvious from the parameter names. No details on valid values, formats, or examples are provided, which is insufficient given the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('Get') and resource ('glyph for a specific icon with a particular style'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'get_icon_glyphs' or 'list_icons', which likely provide different types of icon information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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' or 'search_icons'. It mentions 'specific icon' and 'particular style', which implies usage for detailed icon retrieval, but lacks explicit when/when-not instructions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 doesn't describe behavioral traits such as whether it's a read-only operation, potential rate limits, error handling, or what the return format looks like (e.g., list of glyphs, JSON structure). This leaves significant gaps 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.
Conciseness5/5
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 redundant or unnecessary information. It is appropriately sized and front-loaded, 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.
Completeness2/5
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 low schema coverage, the description is incomplete. It doesn't explain return values, error cases, or behavioral constraints, which are crucial for an agent to use the tool effectively. This is inadequate for a tool with such minimal structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds some meaning by clarifying that 'icon_name' refers to 'a specific icon', but with 0% schema description coverage and only one parameter, the baseline is 4. However, it doesn't provide details like valid icon names, format expectations, or examples, so it doesn't fully compensate for the lack of schema documentation, resulting in a score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get all glyphs') and the resource ('for a specific icon across all available styles'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_icon_glyph_by_style' (which presumably gets glyphs for a specific style rather than all styles), so it doesn't reach the highest level of sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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_glyph_by_style' or 'list_icons'. It lacks explicit when/when-not instructions or prerequisites, leaving the agent to 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.
Behavior2/5
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 a list' implies a read operation, it doesn't address important behavioral aspects like pagination, rate limits, authentication requirements, or what format the list returns. The description is minimal and lacks 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter listing tool without annotations or output schema, the description provides the basic purpose but lacks important context. It doesn't explain what the list contains (just names? metadata?), how results are structured, or any limitations. While minimal, it's adequate for the simplest case but could benefit from more operational detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist, maintaining focus on the tool's purpose rather than unnecessary parameter explanations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get a list') and resource ('all available Hugeicons icons'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its siblings like 'search_icons' or 'get_icon_glyphs' - it simply states what it does without comparative context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance about when to use this tool versus alternatives. With siblings like 'search_icons' and 'get_icon_glyphs' available, there's no indication of when this comprehensive listing tool is preferable to more targeted alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the search functionality and input format, but lacks details on behavioral traits such as pagination, rate limits, authentication needs, error handling, or what the response looks like (e.g., format, fields). This is a significant gap for a tool with potential complexity in search results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with two concise sentences that directly address the tool's function and usage. Every sentence earns its place by providing essential information without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (search functionality with potential for varied results), lack of annotations, and no output schema, the description is incomplete. It covers basic usage but omits critical context such as response format, error conditions, or limitations (e.g., search scope, result ordering). This leaves gaps for an AI agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 1 parameter with 0% description coverage, so the description must compensate. It adds meaningful context by explaining that the 'query' parameter is used to search 'by name or tags' and provides an example syntax ('Use commas to search for multiple icons'), which clarifies the parameter's purpose beyond the bare schema. However, it doesn't detail constraints like character limits or tag format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('icons'), and specifies search criteria ('by name or tags'). However, it doesn't explicitly differentiate this search functionality from sibling tools like 'list_icons' or 'get_icon_glyphs', which might also retrieve icons in some manner.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 query-based retrieval rather than listing all icons. However, it doesn't explicitly state when to use this tool versus alternatives like 'list_icons' or 'get_icon_glyphs', nor does it mention any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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