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Server Quality Checklist

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  • Latest release: v0.0.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: context for a file, impact analysis, codebase map, definition search, and project summary. No overlap or ambiguity.

    Naming Consistency5/5

    All tools follow the consistent pattern 'graft_<noun>' with simple, descriptive names (context, impact, map, search, summary). Perfect consistency.

    Tool Count5/5

    5 tools is well-scoped for a focused code analysis server. Each tool earns its place covering essential exploration tasks without unnecessary bloat.

    Completeness4/5

    The set covers core codebase exploration: summary, search, context, impact, and structural map. Minor gaps like diff or history exist but the surface is practical for typical use.

  • Average 3/5 across 5 of 5 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 is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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

  • Behavior2/5

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

    No annotations are provided, so the description must fully disclose behavioral traits. The description only mentions 'ranked tree map by structural importance' without explaining side effects, read-only nature, or nuances like how personalization works with the 'query' parameter. The behavior is under-specified.

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

    Conciseness3/5

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

    The description is a single sentence, making it concise, but it lacks structure and fails to provide necessary context. It is not overly verbose, but the brevity compromises completeness.

    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 absence of an output schema and annotations, the description should explain what the tool returns (e.g., a list, tree structure, or map). It does not, leaving an agent uncertain about the expected output.

    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 for its two parameters, clearly explaining 'query' as personalization and 'budget' as max tokens. The tool description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.

    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 it is a 'ranked tree map of the codebase by structural importance,' which conveys a general purpose but lacks specificity. It does not clearly differentiate from siblings like 'graft_search' or 'graft_impact,' as it does not explain what 'structural importance' means or how this map is generated.

    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 such as 'graft_context' or 'graft_summary.' The description does not mention prerequisites, context, or scenarios where this tool is appropriate.

    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 full burden. It does not disclose whether affected files include transitive dependencies, limits, or required file existence.

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

    Conciseness3/5

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

    The description is a single sentence, front-loaded with key info. However, it is overly terse, potentially under-specified for a tool with no output schema or annotations.

    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?

    The tool has one parameter and no output schema; the description should explain what 'affected' means (direct vs transitive) and any limits. It fails to provide sufficient context for correct invocation.

    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% for the single 'path' parameter. The description adds no additional meaning beyond the schema, thus baseline score of 3 is appropriate.

    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 states the tool returns files affected by changing a given file, using a specific verb ('changing') and resource ('files affected'). It distinguishes from sibling tools like graft_search, though it lacks detail on scope.

    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 on when to use this tool versus alternatives. It does not specify prerequisites or mention sibling tools for different use cases.

    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 full responsibility for behavioral disclosure. It only states the tool retrieves data for a file but does not mention whether it is read-only, any required permissions, the nature of the output, or potential side effects. This is insufficient for an agent to safely invoke the 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 sentence that is front-loaded with the core action. It is concise and to the point, but could be slightly more informative without adding length.

    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 has only one required parameter and no output schema, the description is minimally sufficient. However, it lacks details about return format, pagination, or limitations, and does not help an agent decide between this and sibling tools in a meaningful way.

    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 provides a full description for the 'path' parameter ('File path relative to project root'), achieving 100% coverage. The description does not add any additional meaning beyond what the schema already states, so it meets the baseline expectation without adding value.

    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 identifies the tool's function: retrieving dependencies and definitions for a specific file. It uses a specific verb+resource pattern, but could be more precise about what 'definitions' entails. It does not explicitly distinguish from siblings like graft_impact or graft_search, but the purpose is distinct enough to infer.

    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 its siblings (graft_impact, graft_map, graft_search, graft_summary). The description lacks any contextual cues about prerequisites or alternative scenarios, leaving the agent to guess.

    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 present, and the description does not disclose behavioral traits such as read-only nature, authentication requirements, or performance characteristics. The burden of transparency is unaddressed.

    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 extremely concise at 6 words, but it is not a complete sentence; it is a noun phrase. Despite this, it communicates essential information efficiently.

    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 provides a reasonable overview of what the tool returns (key files and tech stack). However, it lacks details on format, scope, or how 'key files' are determined, leaving some ambiguity.

    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 zero parameters, so per guidelines the baseline is 4. The description adds no parameter info, but none is 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 tool provides a 'project overview with key files and tech stack', which is specific and distinct from sibling tools like graft_search or graft_impact. However, it could be more explicit in differentiating from close alternatives.

    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 lacks any context about prerequisites, limitations, or recommended scenarios.

    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 minimally states the tool's purpose but does not disclose behavioral traits like case sensitivity, wildcards, pagination, or any side effects.

    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 sentence that is front-loaded and contains no unnecessary words, earning its place.

    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 low complexity (2 params, no output schema, no annotations), the description is adequate but minimal; it could explain the result format or provide search behavior.

    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 baseline is 3. The description adds 'Name pattern to search for' and 'Filter by kind: function, class, type, etc.', which offers slight additional context beyond the 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 'Find definitions by name or kind.' uses a specific verb 'find' and a specific resource 'definitions', clearly distinguishing it from sibling tools like graft_context or graft_impact.

    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 via name or kind but does not provide explicit guidance on when to use this tool over alternatives, nor does it mention any exclusions.

    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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