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TonyBro
by TonyBro

Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: create_game_project handles project initialization, get_game_templates provides template retrieval, and update_game_knowledge manages knowledge updates. The descriptions clearly differentiate between project creation, template access, and knowledge management functions.

    Naming Consistency5/5

    All tools follow a consistent verb_noun naming pattern (create_game_project, get_game_templates, update_game_knowledge) with clear, descriptive names. The naming convention is uniform throughout the set, making it easy to understand each tool's function at a glance.

    Tool Count3/5

    With only 3 tools, the set feels thin for a game development server that presumably needs to handle various development tasks. While the tools cover project creation, templates, and knowledge, there are likely missing operations for actual game development workflows like asset management, testing, or deployment.

    Completeness2/5

    The tool surface is significantly incomplete for game development. While it covers project setup and knowledge management, it lacks essential CRUD operations for game assets, code editing, testing, debugging, or deployment. There are no tools for managing game objects, scenes, or actual development tasks beyond initial setup.

  • Average 2.8/5 across 3 of 3 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
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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 full burden. It mentions 'update knowledge' but doesn't disclose behavioral traits like whether this is a read-only fetch, a write operation to a database, requires authentication, has rate limits, or what the output entails. This is inadequate for a tool with potential mutation implications.

    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 directly states the tool's function without fluff. It's appropriately sized and front-loaded, though it could be more specific to improve clarity without losing conciseness.

    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 no annotations, no output schema, and a vague purpose, the description is incomplete. It doesn't explain what 'update knowledge' means in practice, the tool's behavior, or expected outcomes. For a tool with potential complexity (updating knowledge implies external data or writes), this leaves significant gaps for an AI agent.

    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 'topics' clearly documented as an array of strings for research. The description adds no additional meaning beyond this, such as topic examples or constraints. With high schema coverage, the baseline is 3, as the description doesn't compensate but doesn't detract either.

    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 action ('update knowledge') and domain ('game development best practices and technologies'), which is clear but vague. It doesn't specify what 'update knowledge' entails operationally (e.g., fetching latest info, revising internal docs) or how it differs from siblings like 'create_game_project' or 'get_game_templates', leaving purpose ambiguous beyond a general domain.

    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 implies it's for updating knowledge, but it doesn't specify prerequisites, contexts (e.g., after new tech releases), or exclusions (e.g., not for creating projects). With sibling tools present, this lack of differentiation leaves usage unclear.

    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 mentions 'Linear integration and setup', hinting at external dependencies, but fails to specify critical traits like required permissions, whether the operation is idempotent, potential side effects (e.g., creating files at 'projectPath'), or error handling. For a creation 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.

    Conciseness5/5

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

    The description is a single, efficient sentence that front-loads the core action ('Create a new game project') and includes essential context ('with Linear integration and setup') 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.

    Completeness2/5

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

    Given the complexity of creating a project with external integration, no annotations, and no output schema, the description is incomplete. It omits details on what the tool returns (e.g., success status or project ID), behavioral aspects like error cases, and how it differs from siblings. This leaves gaps for an agent to operate 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?

    Schema description coverage is 100%, so the schema already documents all four parameters with descriptions and an enum for 'gameType'. The description adds no additional meaning beyond implying that parameters relate to project creation and Linear integration, but it doesn't clarify relationships (e.g., how 'teamId' ties to Linear) or usage nuances, meeting the baseline for high 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 action ('Create a new game project') and specifies key features ('with Linear integration and setup'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_game_templates' or 'update_game_knowledge', which would require mentioning it's for initial creation rather than retrieval or modification.

    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_game_templates' or 'update_game_knowledge'. It lacks context such as prerequisites (e.g., needing a Linear team ID) or exclusions (e.g., not for updating existing projects), leaving the agent to infer usage based on the tool name 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 the full burden of behavioral disclosure. It states 'Get available game templates', implying a read-only operation, but does not specify aspects like authentication needs, rate limits, pagination, or what 'available' entails (e.g., public vs. private templates). For a tool with zero annotation coverage, this leaves significant behavioral traits unexplained.

    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: 'Get available game templates'. It is front-loaded with the core action and resource, with no wasted words or unnecessary elaboration. This makes it highly concise and well-structured for its purpose.

    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 complete. It states what the tool does but lacks details on behavior, usage context, or output format. Without annotations or an output schema, the agent must rely on the description alone, which is adequate for a basic read operation but leaves gaps in understanding the full context.

    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, meaning no parameters are documented in the schema. The description does not add parameter details, which is appropriate since there are none to describe. It implies no filtering or input is needed, aligning with the schema. Baseline 4 is applied as per rules for 0 parameters.

    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 'Get available game templates' clearly states the action (get) and resource (game templates), making the purpose understandable. However, it lacks specificity about what 'available' means (e.g., all templates, user-accessible ones, or filtered by some criteria) and does not differentiate from sibling tools like 'create_game_project' or 'update_game_knowledge', which are distinct operations. This makes it adequate but vague.

    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. It does not mention prerequisites, context (e.g., before creating a game project), or exclusions, leaving the agent to infer usage based on the tool name alone. With sibling tools present, this lack of explicit comparison or situational advice is a clear gap.

    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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