scorezilla-mcp

Server Quality Checklist

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Latest release: v0.2.1
Disambiguation5/5
Each tool has a clear, distinct purpose: creating a game+board, listing games, listing boards, getting top scores, retrieving API keys, and generating integration code. There is no overlap or ambiguity between them.
Naming Consistency4/5
Tool names follow a verb_noun snake_case pattern. While 'bootstrap' is less standard than 'get' or 'list', the overall style is consistent and predictable.
Tool Count5/5
Six tools cover the core aspects of a leaderboard integration service (game management, board listing, score retrieval, key management, snippet generation) without redundancy or gaps.
Completeness4/5
The tool surface covers essential setup and monitoring operations. Missing update/delete operations for games and boards, but these are less critical for the primary use case of integrating a leaderboard.
Average 4.5/5 across 6 of 6 tools scored. Lowest: 3.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 35 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 must cover behavioral traits. It implies a read operation and mentions a testing use case but does not explicitly state read-only nature, authentication needs, rate limits, or error conditions. Falls short of full disclosure.
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?
Two sentences with clear front-loading of purpose. No extraneous words. Every sentence contributes value.
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?
Lacks details on output format and error conditions. Given the absence of an output schema, the description could briefly mention the structure of returned entries. Use cases are covered but operational completeness is lacking.
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 parameters are already well-documented. The description adds no additional meaning beyond the schema's definitions. Baseline 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 it gets the top-ranked entries on a leaderboard. It distinguishes from siblings like list_boards or bootstrap_leaderboard by specifying leaderboard context and adding specific use cases.
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?
The description provides explicit when-to-use scenarios: after submitting a test score to verify integration and for displaying standings. However, it does not discuss when not to use or mention alternative tools, which would further aid decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It describes the properties of returned boards but does not mention that it is a read-only operation, any side effects, authorization needs, or rate limits. The absence of such details lowers 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?
Description is two well-structured sentences. First sentence states main function. Second sentence provides details and usage context. No redundancy or unnecessary words.
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 simplicity of the tool (one parameter, no output schema), the description covers the key aspects: input source, output characteristics, and usage scenarios. It could mention response format (array), but the list of board properties compensates.
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?
Schema covers the only parameter with a description. Description adds value by explaining that gameId comes from list_games output, which helps the agent obtain the correct input. This extra context justifies a score above baseline.
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?
Description clearly states it lists all leaderboards under a given game, and distinguishes from siblings by explaining its role in finding board IDs before using get_sdk_snippet or get_board_top_n. It also specifies the information each board contains, which provides clarity.
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 advises when to use: to find a board's id before generating a snippet or reading standings, or to show existing boards. It also references list_games as the source of the gameId. However, it does not explicitly state when not to use or compare to all sibling tools.
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?
With no annotations, the description carries full burden. It explains that the tool tailors the snippet based on axis arguments and returns a snippet field. However, it does not disclose side effects, authentication requirements, or rate limits, which would be needed for a 5.
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 paragraph that effectively conveys key information without unnecessary words. It could be slightly more structured (e.g., bullet points) but is still concise and front-loaded.
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 complexity (6 params, 4 enums, no output schema), the description covers primary use cases, distinguishes from siblings, and explains what the output contains. It does not mention potential errors or edge cases, but is sufficiently complete for most scenarios.
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?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining how omission of axis args leads to simplest setup and gives context for each hostingPattern/playerIdentityStrategy beyond the 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 the tool returns a ready-to-paste integration snippet for submitting scores, initializing SDK, or integrating a leaderboard. It distinguishes itself from sibling tool bootstrap_leaderboard by noting that the latter returns a drop-in widget HTML embed.
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 tells when to call: whenever the developer asks about integration, after bootstrap_leaderboard, or anytime they need the code again. Provides guidance on omitting arguments for simplest setup and when to use specific hostingPattern values.
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?
With no annotations, the description fully discloses behavior: it returns public key plaintext, secret key plaintext is always null over MCP, and provides rotation/revocation timestamps. It also warns about what it cannot do (return full secret key). No contradictions with annotations since none exist.
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 concise yet comprehensive: first sentence states purpose, then describes returned fields, then usage guidance and alternative. Every sentence adds value without fluff. It is front-loaded with the main action.
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 output schema, the description thoroughly explains what is returned (kind, prefix, timestamps) and what is not (secret key plaintext). It also references the required predecessor tool (list_games) and links to the dashboard for missing functionality, making it complete for the tool's scope.
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 schema already describes gameId as 'UUID of the game to fetch keys for (from list_games)' with 100% coverage. The description adds context that gameId comes from list_games, but does not add new information about the parameter itself beyond what the schema provides. Baseline is 3.
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 'Get a game's API keys,' specifying the verb 'Get' and the resource 'API keys'. It differentiates from siblings by focusing on keys, which none of the other tools (bootstrap_leaderboard, get_board_top_n, etc.) cover.
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 explicitly tells when to use this tool: 'to retrieve the public key for a client_only integration, or to check which keys exist / have been revoked.' It also provides an alternative for the full secret key (dashboard). It implies that list_games should be used first to obtain the gameId.
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?
With no annotations, the description carries full burden. It describes the return structure and scope (owned by authenticated developer), but does not explicitly mention that the operation is read-only and safe. However, the context implies a safe list operation, and the description adds value beyond the name. A minor gap in explicitly stating safety attributes prevents a perfect score.
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 three sentences, front-loaded with the primary action, and every sentence serves a purpose. No wasted words, and it is well-structured for quick parsing.
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 the tool's simplicity (no parameters, no output schema), the description fully covers what it does, what it returns (id, slug, name, createdAt), and provides usage context and alternatives. It is complete enough for an AI 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?
There are no parameters, and the input schema is empty with 100% coverage. The description does not need to add parameter semantics, so a baseline score of 4 is appropriate as per guidelines.
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 lists all games owned by the authenticated developer, and distinguishes itself from siblings by suggesting an alternative tool (bootstrap_leaderboard) for a specific scenario. The verb 'list' and resource 'games' are specific and unambiguous.
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 states to use this first for orientation before creating or inspecting resources, and provides a conditional guideline: if the result is empty and the developer wants to add a leaderboard, to call bootstrap_leaderboard. This gives clear when-to-use and when-not-to guidance.
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?
With no annotations, the description fully carries the burden. It discloses that it creates a game and board, returns specific snippet fields, and explains how optional parameters alter behavior (e.g., anti-cheat, identity strategy). No contradictions.
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 paragraph but front-loads the primary purpose. While dense, every sentence adds value. Could be more structured, but appropriate for the complexity.
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?
Despite having 10 parameters and no output schema, the description thoroughly explains the response structure (snippets.sdk, snippets.widget, recommendation) and how each optional parameter affects the output. Complete for a complex tool.
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?
Schema has 100% description coverage, so baseline is 3. The description adds high-level context, like which combination of options yields the 'simplest anonymous + client-only setup', enhancing understanding beyond schema.
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 creates a new game and its first board in one call, returns integration code, and distinguishes itself from sibling tools by specifying 'when starting from scratch' and not to call if games already exist.
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 says to use when starting from scratch and not to call if developer already has games, with an alternative action ('call list_games first'). Provides clear 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.

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