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hha-nguyen

Huly MCP Server

by hha-nguyen
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JavaScript
Hybrid

Server Quality Checklist

50%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: create_issue handles creation, list_issues handles listing issues, and list_projects handles listing projects. There is no overlap or ambiguity between these three operations.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with snake_case: create_issue, list_issues, list_projects. The naming is predictable and uniform throughout the set.

    Tool Count3/5

    With only 3 tools, the set feels thin for a project management domain like Huly, lacking operations such as update_issue, delete_issue, or get_project. However, it covers basic listing and creation, making it borderline appropriate.

    Completeness2/5

    The tool surface is significantly incomplete for managing issues and projects. It includes create_issue and list_issues but misses update_issue and delete_issue, and list_projects lacks corresponding create_project, get_project, or update_project operations, leaving agents with dead ends.

  • Average 2.9/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action ('List issues') without describing traits like pagination, rate limits, authentication needs, or what 'Huly' refers to. 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.

    Conciseness5/5

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

    The description is extremely concise with a single sentence 'List issues from Huly', which is front-loaded and wastes no words. It efficiently conveys the core purpose without unnecessary details.

    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 and output schema, the description is incomplete. It does not explain what 'Huly' is, the return format, or any behavioral context, making it inadequate for a tool that likely returns a list of issues without further guidance.

    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 input schema has 100% description coverage, with one optional parameter 'project' documented as 'Filter by project identifier (optional)'. The description adds no additional meaning beyond the schema, 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.

    Purpose3/5

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

    The description 'List issues from Huly' clearly states the verb ('List') and resource ('issues'), but it's vague about scope and lacks differentiation from sibling tools like 'create_issue'. It doesn't specify whether this lists all issues, filtered issues, or something else, which reduces clarity.

    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 like 'create_issue' or 'list_projects'. The description does not mention any context, prerequisites, or exclusions, leaving the agent without usage instructions.

    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 this is a creation tool, implying a write operation, but doesn't mention permissions required, rate limits, error handling, or what happens on success (e.g., returns an issue ID). This leaves significant gaps for a mutation tool.

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

    Conciseness4/5

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

    The description is a single, efficient sentence that gets straight to the point without unnecessary words. However, it could be more front-loaded by immediately stating the core purpose, and the phrase 'with correct fields' is somewhat vague, slightly reducing clarity.

    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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., issue ID, success confirmation), error conditions, or behavioral nuances like whether duplicate issues are allowed, which are critical for an agent to use it effectively.

    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 input schema has 100% description coverage, clearly documenting all 6 parameters with their types, enums, and requirements. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 for adequate but not enhanced 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 action ('Create a new issue') and target resource ('in Huly'), which provides a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'list_issues' beyond the basic create vs. list difference, missing an opportunity to clarify when to use each.

    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 'list_issues' or 'list_projects'. It mentions 'with correct fields' but doesn't specify what constitutes correct fields or any prerequisites, leaving the agent with minimal context for decision-making.

    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 it's a list operation, implying read-only behavior, but doesn't specify any constraints like pagination, sorting, filtering, or rate limits. For a tool with zero annotation coverage, this is insufficient transparency.

    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 unnecessary words. It's front-loaded and appropriately sized for a simple list tool, 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.

    Completeness3/5

    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. It covers the basic purpose but lacks details on usage context, behavioral traits, or output format. For a list tool with no structured support, it should provide more guidance to be fully complete.

    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 0 parameters with 100% coverage, so the schema fully documents the absence of parameters. The description doesn't add parameter details, which is appropriate here. The baseline for 0 parameters is 4, as no additional parameter semantics are needed.

    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 verb ('List') and resource ('projects in Huly'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_issues', which would require a 5. The description is specific but lacks sibling distinction.

    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 'list_issues' or 'create_issue'. It doesn't mention any context, prerequisites, or exclusions for usage. This leaves the agent without direction on tool selection.

    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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