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Festuskipkoech

github-pr-review

Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: listing PRs, getting diffs, getting comments, posting inline comments, approving, and requesting changes. No overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with underscores (e.g., approve_pr, get_pr_diff), making them predictable and easy to distinguish.

    Tool Count5/5

    Six tools is an ideal size for a focused PR review server, covering the essential actions without being overwhelming or sparse.

    Completeness4/5

    The set covers the core PR review workflow (list, diff, comments, approve, request changes) but lacks features like merging or dismissing reviews, which are minor gaps given the server's specific scope.

  • Average 3.4/5 across 6 of 6 tools scored. Lowest: 2.7/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
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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 behavior. It fails to mention side effects, required permissions, or the fact that the message parameter is actually required despite being described as optional. This inconsistency reduces transparency.

    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 very concise at one sentence, but it omits important details and contains an inconsistency. It is not well-structured for an agent to infer correct usage.

    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 simple tool (2 parameters, output schema exists), the description is minimal but lacks guidance on return values or edge cases. The contradiction between description and schema further reduces completeness.

    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 100% but the description contradicts the schema: the message is described as optional but is required in the schema. This confusion overrides the baseline of 3.

    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 action (approve) and resource (pull request), and mentions the optional message. It distinguishes from siblings like request_changes and post_review_comment.

    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 does not provide any guidance on when to use this tool versus alternatives (e.g., request_changes or post_review_comment). No context on prerequisites or suitable 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?

    No annotations exist, so the description carries the full burden. It only says 'request changes' without disclosing behavioral traits like whether it creates a review, blocks merging, or is reversible. No return value information is provided despite an output schema being present.

    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 concise sentence that is front-loaded with the core action. However, it may be overly brief for a mutation tool.

    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 tool's simplicity (2 parameters, output schema exists), the description is insufficient. It lacks context about the effect of the action, prerequisites, or what the response contains. A mutation tool should provide more detail.

    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 description adds no extra meaning beyond the parameter names and types. The 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 the tool requests changes on a pull request with a review message. The verb 'request changes' is specific and distinct from sibling tools like approve_pr or post_review_comment.

    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 (e.g., post_review_comment or approve_pr). The description does not mention use cases or exclusions.

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

  • Behavior1/5

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

    No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description only repeats the purpose without adding any details about rate limits, authentication, side effects, or output characteristics.

    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 with no wasted words. It is efficient and front-loads the purpose.

    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's simplicity (one parameter, output schema exists), the description is minimally adequate. It does not mention prerequisites or context, but it is complete enough for 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 description coverage is 100%, so the baseline is 3. The description does not add additional meaning beyond what the schema already provides for the single parameter.

    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 verb 'Get' and the resource 'file changes and diff for a specific pull request.' It distinguishes from siblings like approve_pr and get_pr_comments, which handle different aspects of pull requests.

    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 that the tool should be used when a user needs the diff of a pull request. However, it does not explicitly state when not to use it or compare it to alternatives like get_pr_comments for comments.

    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 provided, so description carries full burden. It does not disclose whether it creates a pending review, submits immediately, or requires permissions. Missing behavioral details like side effects or prerequisites.

    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?

    Single sentence, front-loaded with essential information. No wasted 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?

    Description covers the core action and parameters. Output schema exists but not needed here. For a simple tool with 4 params, description is nearly complete; lacks only minor behavioral clarity.

    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?

    All 4 parameters have descriptions in the input schema (100% coverage). The description adds no new meaning beyond consolidating the schema info. 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?

    Description clearly states the action (post), the resource (inline comment), and the specifics (file, line, via review submission). It distinguishes from sibling tools like get_pr_comments or approve_pr.

    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?

    No explicit guidance on when to use vs alternatives like request_changes. Usage is implied by context (PR review), but no exclusions or conditions provided.

    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 must carry the full burden. It only states 'get all review comments' without disclosing behaviors like idempotency, resolved/unresolved status, pagination, or whether it's a read-only operation.

    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?

    A single, clear sentence that front-loads the purpose. No wasted 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?

    For a simple retrieval tool with one parameter and an output schema (not shown), the description is adequate. It does not cover pagination or filtering but the low complexity makes it sufficient.

    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 sole parameter (pr_number) is described in the schema with 'The pull request number to retrieve comments for.' The tool description adds no additional meaning beyond what the schema already provides, so 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 verb 'Get' and the resource 'all review comments on a specific pull request', which is distinct from sibling tools like approve_pr, get_pr_diff, etc.

    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 usage is implied: use when you need all comments for a given PR. No explicit exclusions or alternatives are provided, but the simplicity of the tool makes the context clear.

    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 only states a read operation with no side effects, but lacks details on authorization, rate limits, pagination, or behavior when no PRs exist. The description is minimal and offers no extra behavioral context beyond the obvious read action.

    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, short sentence that conveys the essential purpose with no wasted words. It is front-loaded and efficiently communicates the tool's function.

    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 no parameters and an output schema exists (though not shown). The description is adequate for the straightforward task. It could optionally mention that the output is a list of PRs, but the output schema likely covers that. Overall, it provides the necessary information to understand what the tool does.

    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 input schema is empty (0 parameters). Per the guidelines, 0 parameters yields a baseline of 4. The description adds no parameter information because none is needed. Schema coverage is trivially 100%.

    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 ('list'), the resource ('open pull requests'), and the scope ('in the configured repository'). The tool name also aligns perfectly with its purpose, and the sibling tools (approve, comment, diff) are distinct actions, so there is no ambiguity.

    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. However, the purpose is intuitive given the sibling tools; it implies usage when a list of open PRs is needed, but no explicit when-not-to-use guidance is provided.

    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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