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Server Quality Checklist

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  • Latest release: v1.0.6

  • Disambiguation5/5

    Each tool targets a clear, distinct operation: adding, listing, generating from, and removing configured repositories. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow the consistent verb_noun pattern in snake_case: add_repos, list_repos, generate_standup, remove_repos. This is perfectly predictable.

    Tool Count5/5

    With only 4 tools, the set is tightly scoped to its purpose of managing repository configuration and generating standup notes. Each tool earns its place with no redundancy.

    Completeness5/5

    The tool surface covers the full lifecycle of configuration: add, list, remove, and the core generation action. No obvious missing operations for the stated purpose.

  • Average 3.6/5 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 status not available
  • 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    With no annotations, the description carries the full burden of behavioral disclosure. It only states the operation without mentioning side effects, idempotency, validation, or error behavior. The description implies an additive action but gives no details about what happens to existing configuration or invalid paths.

    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, concise sentence that states the verb and object directly. It contains no redundant or extraneous information, making it efficient and easy to parse.

    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?

    The tool is simple with one parameter and an output schema, but the description lacks behavioral context such as whether duplicate paths are handled, whether existing entries are preserved, or what the output contains. Given the absence of annotations, this is a clear gap, though the low complexity prevents it from being severely inadequate.

    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 provides complete coverage for the single 'paths' parameter with the description 'Absolute paths to git repositories'. The tool description adds no additional parameter-level meaning beyond this, so the baseline of 3 is appropriate given the high schema description coverage.

    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 uses the specific verb 'Add' targeting 'repository paths' and 'configuration', clearly stating the tool's function. This distinguishes it from sibling tools like list_repos and remove_repos, which have different actions.

    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 sibling tools or specific scenarios, leaving the agent to infer usage from the tool name and context.

    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. It states the action but does not disclose whether removal is destructive, whether missing paths cause errors, whether changes are persistent, or how it affects other tools like list_repos. This is minimal transparency for a mutation tool.

    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, compact sentence that is front-loaded with the action and target. Every word is relevant, and there is no verbosity or unnecessary detail.

    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?

    The tool is simple with one fully described parameter and an output schema present (though its content is unknown). However, the description lacks context about the tool's effects on the configuration, success/failure behaviors, and prerequisites. For a mutation tool with no annotations, more contextual info would be expected, but the simplicity of the operation keeps this at a satisfactory level.

    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 has 100% coverage with the parameter described as 'Repository paths to remove'. The description echoes this exactly, adding no new meaning. Baseline is 3 for full schema coverage, and the description doesn't compensate beyond that.

    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 action ('Remove') and the specific resource ('repository paths') with scope ('from the configuration'). This distinguishes it from sibling tools like add_repos and list_repos.

    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, such as add_repos or list_repos. There is no mention of complementary tools or explicit context for when removal 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It explains what the tool generates and from where, but does not disclose whether it modifies anything, requires specific permissions, has side effects, or how it handles missing configurations. This is a significant gap for a tool that presumably reads git history.

    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, concise sentence that immediately states the tool's action and source. There is no redundant or irrelevant information, and the key details are 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?

    The tool is simple with optional parameters and an output schema present, so the description does not need to explain return values. The core purpose is clear, and sibling tools establish the repository management context. However, the lack of behavioral transparency (e.g., whether it is read-only) prevents a perfect score.

    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 already provides thorough descriptions for both parameters (hours with default, repos as alternative paths). Since schema coverage is 100%, description adds little beyond reinforcing the concept of 'configured repositories', which aligns with the repos param. 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 uses a specific verb ('Generate') and resource ('standup notes from git commits in configured repositories'), clearly distinguishing it from sibling tools that manage repositories (add_repos, list_repos, remove_repos). The title reinforces the function.

    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 clear context on what the tool does and its input source (configured repositories), which implicitly sets expectations of use. However, it does not explicitly state when to use this tool versus alternatives or mention any prerequisites like needing to configure repositories first via sibling tools.

    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 carry the behavioral burden. The verb 'List' implies a read-only operation, but it does not explicitly state there are no side effects, whether authentication is required, or how it behaves with an empty configuration. Minimal but not misleading.

    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, concise sentence that leads with the verb and wastes no words. It is perfectly sized for the tool's simplicity.

    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's low complexity, no parameters, and an existing output schema, the description is nearly complete. It could clarify what 'currently configured' means (e.g., from a config file), but for a straightforward list operation it is mostly sufficient.

    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, and the schema clearly shows an empty properties object. The description adds nothing about parameters, but none is needed. Baseline of 4 applies.

    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 uses a specific verb 'List' with a clear resource 'repositories' and the qualifier 'currently configured', which adds scope and distinguishes it from sibling tools like add_repos and remove_repos. It precisely states the tool's function.

    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 gives no explicit guidance on when to use this tool versus alternatives. It implies that listing is the way to view configured repositories, but it does not mention conditions, prerequisites, or when add/remove might be more appropriate.

    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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  • 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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