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Onur-Ardic

GitHub PR Reviewer MCP

by Onur-Ardic
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: github_pr_review generates an analysis report, github_pr_diff fetches the raw diff content, and github_pr_files lists changed files. There is no ambiguity between them.

    Naming Consistency5/5

    All tool names follow the same 'github_pr_' prefix with a descriptive suffix. While suffixes are not strictly verbs, the pattern is completely consistent and predictable across the set.

    Tool Count5/5

    With only 3 tools, the server is tightly scoped to the PR review workflow. Each tool adds meaningful functionality without redundancy, making the count ideal for the stated purpose.

    Completeness5/5

    The tool set covers the full review workflow: retrieving the diff, listing files, and generating the review report. There are no obvious missing operations that would prevent an agent from effectively reviewing a Pull Request.

  • Average 3.4/5 across 3 of 3 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 status not available

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  • This repository includes a README.md file.

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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 carries full burden. It tells the tool fetches diff content, implying a read operation, but does not disclose return format, limitations, or any side effects. This lacks depth for safe autonomous use.

    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 function, with no filler or repetition. It is well-structured and front-loaded.

    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 no output schema. The description gives a basic idea of what is returned (changes details), but lacks specifics such as output format, pagination, or any caveats. It is minimally viable but not comprehensive.

    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 documents the only parameter (pr_url) with 100% coverage. The description adds no additional semantics beyond reinforcing the PR URL, so it meets the baseline but does not enhance understanding.

    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 retrieves the diff content of a GitHub Pull Request, using a specific verb ('getirir' - fetches) and resource (PR diff). It is distinct enough from sibling names like github_pr_files and github_pr_review, though it does not explicitly differentiate itself.

    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 only states what it does, with no mention of use cases, prerequisites, or exclusions.

    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 must shoulder the responsibility of behavioral disclosure. It mentions analyzing changes and files but does not disclose authentication requirements, rate limits, output format, or whether the operation is read-only. This leaves significant behavioral uncertainty.

    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 two sentences, front-loaded with the primary purpose and scope. Every word contributes to understanding the tool, with no redundancy or filler.

    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?

    There is no output schema, so the description should explain what the 'detailed code review report' contains or its structure. It only vaguely references analysis without specifics, leaving the agent uncertain about return values. It also fails to reference sibling tools for context.

    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 fully documents the single parameter 'pr_url' with an example. The description adds no additional semantic 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 tool's purpose: takes a GitHub PR link and creates a detailed code review report by analyzing PR details, changes, and files. This distinguishes it from sibling tools like github_pr_diff and github_pr_files, which focus on specific aspects of a 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?

    The description implies usage for obtaining a comprehensive review report, but it does not explicitly mention when to use this tool versus alternatives like github_pr_diff or github_pr_files. There is no direct 'use this instead of' guidance or exclusions.

    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. The description only states the basic action (fetching a list) without disclosing any behavioral traits such as authentication requirements, rate limits, response format details, or whether it includes file paths, statuses, or other metadata. This is minimal for a tool with no annotation support.

    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, front-loaded sentence that clearly communicates the tool's purpose. There is no redundant information or unnecessary phrasing, making it highly concise and well-structured.

    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 (one parameter, no output schema). The description sufficiently states the return type (a list of files), which is the main expected output. However, it could be more complete by mentioning whether the list includes only file names or additional details, but given the simplicity, the description is mostly adequate.

    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% (pr_url is fully described as the GitHub Pull Request URL). The description does not add any parameter meaning beyond what the schema already provides, so the baseline score of 3 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 clearly states the tool's function: it fetches the list of files changed in a GitHub Pull Request. The verb 'getirir' (fetches) and the specific resource ('GitHub Pull Request'te değiştirilen dosyaların listesi') distinguish it from sibling tools like github_pr_review (review) and github_pr_diff (diff).

    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?

    There is no explicit guidance on when to use this tool versus alternatives. However, the description implies usage for retrieving the list of changed files, and the sibling names (review, diff) suggest different use cases, but no direct comparison or exclusions are 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 there are no obvious security issues.
  • Evaluate tool definition quality.

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