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GlossMod

GlossModMCP

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by GlossMod

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.2.0

  • Disambiguation5/5

    Each tool has a distinct purpose: get_games for searching/listing games, get_game_detail for a specific game's details, get_mods for listing mods (requires game_id), and get_mod_detail for mod details. No overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (get_games, get_game_detail, get_mods, get_mod_detail). Clear and predictable.

    Tool Count5/5

    4 tools is well-scoped for a read-only mod database. It covers the essential operations without overloading the surface.

    Completeness4/5

    Covers the core workflow of browsing games and mods. The only gap is that mod search requires a game_id, so you cannot directly search mods by name across all games. Otherwise complete for the domain.

  • Average 4.3/5 across 4 of 4 tools scored. Lowest: 3.6/5.

    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 is passing
  • This repository is licensed under MIT License.

  • 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

  • Behavior3/5

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

    No annotations are provided, so the description carries the burden. It states the operation is a get and describes the returned info (user and game details). However, it does not disclose safety aspects, auth requirements, or rate limits. The URL pattern adds some context.

    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 short and to the point, with three sentences. The URL pattern provides useful context. No unnecessary information.

    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?

    With no output schema, the description partially explains what is returned (user and game info) but lacks detail on the structure. For a simple tool with one parameter, it is adequate but not comprehensive.

    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 only parameter, mod_id, is self-explanatory from its name and title. The description does not add any additional meaning beyond what the schema provides, but the schema is minimal with 0% coverage. Baseline of 3 is appropriate.

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

    Purpose5/5

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

    The description clearly states that the tool retrieves detailed information of a specified mod, including user and game information. The verb '获取' (get) and resource 'Mod 详细信息' are specific, and the tool name distinguishes it from siblings like get_mods and get_game_detail.

    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 implies usage when detailed info of a specific mod is needed, but it lacks explicit guidance on when to use this tool versus alternatives like get_mods. No when-not-to-use or exclusion criteria are provided.

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

  • Behavior4/5

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

    No annotations provided, so the description must disclose behavioral traits. It mentions including mod statistics and provides a URL pattern, which adds context. However, it does not explicitly state that the operation is read-only or idempotent, though it is implied.

    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 concise and well-structured, front-loading the purpose and then providing a clear workflow. No unnecessary text, but the step-by-step instructions could be slightly more compact.

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

    Completeness5/5

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

    The description covers all essential aspects for a simple detail retrieval tool: purpose, prerequisite, workflow, and a derived URL. It differentiates well from sibling tools and provides enough context for correct 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?

    Schema coverage is 0% for the single parameter game_id, and the description only adds a usage constraint (must come from get_games) but does not explain the parameter's semantics or format. This is insufficient to compensate for the missing schema descriptions.

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

    Purpose5/5

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

    The description clearly states that the tool retrieves detailed information for a specified game, including mod statistics, and distinguishes it from sibling tools like get_games (search) and get_mods/get_mod_detail (mod-specific).

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

    Usage Guidelines5/5

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

    Explicitly provides a prerequisite (game_id must come from get_games) and a two-step workflow, guiding when and how to use the tool versus alternatives.

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

  • Behavior4/5

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

    No annotations provided, so description carries full burden. It discloses that this is a list operation with pagination and filtering. It mentions prerequisites and supports multiple game IDs. It does not discuss rate limits or error states, but is transparent about the read-only nature and required inputs.

    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?

    Well-structured with sections for prerequisite, workflow, and parameter details. It is front-loaded with the purpose. While somewhat lengthy, every sentence adds value given the zero schema coverage.

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

    Completeness4/5

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

    Given the tool complexity (6 parameters, prerequisites, sorting, filtering), the description covers the essential workflow and parameter details. It also provides a URL pattern for mod details, which aids in using the output. Lacks explicit return format description, but the URL hint compensates.

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

    Parameters5/5

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

    Schema has 0% description coverage, so description adds significant value. It explains each parameter: page, page_size, game_id (single/multiple), search, order (with enum mapping), and time (with enum mapping). This goes well beyond the schema titles.

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

    Purpose5/5

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

    The description clearly states it retrieves a list of mods, with a specific prerequisite (game ID from get_games). It distinguishes from siblings like get_mod_detail (single mod) and get_games (game list).

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

    Usage Guidelines4/5

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

    Explicitly states prerequisite (must call get_games first) and provides a typical workflow. Lists multiple filters and sorting options. However, it does not explicitly mention when not to use this tool or alternatives.

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

  • Behavior5/5

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

    No annotations exist, so the description fully bears the burden. It details pagination, search, filtering, sorting, and even provides the entire return structure. There are no hidden side effects; the tool is clearly read-only.

    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 well-structured with clear sections (important note, workflow, parameters, return structure, example, URL). It is somewhat lengthy but every part adds value; front-loading of key info is good.

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

    Completeness5/5

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

    Given no annotations and no output schema, the description covers all needed context: how to use the tool, what parameters do, the structure of the return data, and how to link results to sibling tools. It is complete for an agent to use 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?

    With 0% schema description coverage, the description must explain parameters. It adequately describes search, game_type, page, and page_size. However, sort_by and sort_order are not explained, though their names are somewhat self-explanatory.

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

    Purpose5/5

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

    The description clearly states that the tool retrieves a list of games and is the entry point for game-related queries. It distinguishes itself from siblings like get_mods by explaining that the returned game_id is used in subsequent calls.

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

    Usage Guidelines5/5

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

    The description provides explicit workflow: first use search to get a game_id, then use that ID in other functions. It gives examples and warns that this is the required entry point for game queries, making usage intentions very clear.

    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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