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Server Quality Checklist

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  • Latest release: v1.3.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: syntax checking, compilation, deploy link generation, and version retrieval. There is no overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., check_tolk_syntax, get_compiler_version), making them predictable and easy to understand.

    Tool Count5/5

    With 4 tools, the server is well-scoped for Tolk smart contract development, covering essential operations without unnecessary bloat.

    Completeness4/5

    The tool set covers the main workflow: syntax check, compilation, and deploy link generation. However, it lacks tools for tasks like directly fetching contract addresses or deploying contracts, which are minor gaps.

  • Average 4.1/5 across 4 of 4 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
    • Last stable release on
    • 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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      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

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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 provided, so description carries the burden. It discloses that compilation uses @ton/tolk-js, resolves standard libraries automatically, and returns specific outputs. However, it does not mention error handling, permissions, or potential side effects, leaving gaps in transparency.

    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?

    Description is a single efficient paragraph covering all key aspects without redundancy. It is front-loaded with the main action and includes necessary details. Minor improvement could be structuring bullet points for readability.

    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 (5 params, nested objects, no output schema), the description adequately explains inputs and outputs, including automatic library resolution. It lacks details on output format expectations and error scenarios, but is sufficient for an agent to understand the tool's purpose and basic usage.

    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 coverage is 100%, so the schema already explains parameters. The description adds value by summarizing output and clarifying automatic library resolution and pathMappings usage. This extra context is helpful but not extensive, so a 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 the tool compiles Tolk smart contract source code using @ton/tolk-js, specifying inputs (source map, entrypoint) and outputs (Fift code, BoC, code hash, compiler version). It distinguishes from siblings by focusing on compilation vs syntax checking or deploy link generation.

    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 explains how to provide sources but lacks explicit when-to-use guidance or alternatives. It does not mention when to use check_tolk_syntax first or what constraints exist. The usage context is implied but not differentiated.

    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 are provided, so the description carries the full burden. It mentions computing address and returning deeplinks, but does not disclose side effects, error conditions, or whether network access is required.

    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 concise sentences front-load the main purpose and provide key details without waste. Every sentence adds 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?

    Given the tool generates deeplinks with no output schema, the description lacks return format details (e.g., how many links, usage in wallet). It is adequate but not fully complete for agent invocation.

    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?

    Input schema has 100% coverage with detailed parameter descriptions (e.g., linking codeBoc64 to compile_tolk output, specifying defaults for workchain and amount). The tool description adds no extra but schema is sufficient.

    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 generates a TON deployment deeplink for a compiled Tolk contract, distinguishing it from sibling tools like compile_tolk and check_tolk_syntax.

    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 does not explicitly state when to use this tool versus alternatives. It implies usage after compilation but lacks when-not-to-use guidance or alternative tool references.

    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?

    With no annotations, the description must disclose all behavioral traits. It states the tool returns version information, implying a read-only operation, but does not explicitly confirm no side effects or other behaviors. Given the trivial nature, this is borderline adequate.

    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: one sentence that conveys purpose and usage context with no filler or redundancy. Every word earns its place.

    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?

    For a tool with no parameters and a simple return (version string), the description is complete enough to inform usage. It does not detail the exact format of the version string, but that is implicit and acceptable.

    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, so schema coverage is 100%. The baseline for 0 parameters is 4, and the description adds no parameter info because none exist. No deduction needed.

    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 returns the compiler version, using a specific verb 'Returns' and specifies the resource 'Tolk compiler version'. It distinguishes from sibling tools (syntax check, compile, deploy link) by focusing on version retrieval.

    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 explicitly advises using this tool 'to check which compiler version is available', providing clear context. However, it does not mention when not to use it or suggest alternatives, which would strengthen guidance.

    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?

    Without annotations, the description clearly states the return behavior: 'OK + code hash on success, or error details on failure'. It also mentions support for pathMappings in import resolution. No contradictory claims.

    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?

    Three sentences, each adding distinct value: purpose, use case, and parameter highlight. No redundancy or extra 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 tool has 3 parameters, nested objects, and no output schema, the description covers behavior, return format, and a key parameter detail. It is sufficient for an agent to understand when and how to use it.

    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?

    Input schema covers all parameters with descriptions (100% coverage). The description adds value by explaining the purpose of 'pathMappings' for custom alias import resolution, which goes beyond the schema's generic description.

    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?

    Clearly states the tool checks Tolk source code for syntax and type errors, and explicitly distinguishes it from 'compile_tolk' by noting it does not return full compilation output. Verb and resource are specific.

    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?

    Describes the tool as providing a 'faster feedback loop for iterative development', implying it is for quick checks. While it does not explicitly name alternatives, the sibling tool 'compile_tolk' contrasts with the description's emphasis on speed and lighter output.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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