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wxomi

phab-arc-mcp

by wxomi
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one fetches review context, the other creates draft inline comments. There is no overlap in functionality, so an agent can easily select the right tool.

    Naming Consistency2/5

    Tool names do not follow a consistent pattern. 'review-phab' is verb-noun, while 'inline-comments-phab' is noun-noun. The shared '-phab' suffix is a minor unifier but the lack of consistent verb usage makes naming unpredictable.

    Tool Count3/5

    With only two tools, the server feels thin but not unreasonable for a narrowly focused review workflow. The count is at the borderline where it could benefit from additional operations, but it is not excessively sparse.

    Completeness2/5

    The tool surface has significant gaps. It creates draft comments but explicitly does not publish them, and there is no way to submit or finalize a review. This creates a dead end for the agent workflow, as the created comments cannot be acted upon fully.

  • Average 3.6/5 across 2 of 2 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 failing

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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?

    With no annotations, the description carries the full burden of behavioral disclosure. It does reveal that the tool fetches a review prompt and revision context, implying a read-only operation. However, it lacks details about permissions, rate limits, or any potential side effects, which is a moderate gap 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, concise sentence that front-loads the action ('Fetches') and immediately states the resource being fetched. There is no extraneous information, making it highly efficient.

    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 that an output schema exists and there is only one parameter, the description provides enough basic context for an agent to understand the tool's primary function. However, it omits usage guidance and details about error handling or authorization, which prevents a perfect score.

    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 description coverage is 0%, meaning the description does not explain the revision_id parameter at all. While the parameter name is intuitive, the description adds no additional meaning beyond the schema. The tool would benefit from explaining what a revision_id is or where to find it.

    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 fetches 'the exact review prompt and revision context needed to review a Differential' using a specific verb and resource. This distinguishes it from the sibling tool inline-comments-phab, which presumably handles comments rather than review context.

    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 mentions 'without MCP sampling' but does not explain when a user would need this tool, what prerequisites exist, or when to use inline-comments-phab instead.

    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 carries the full burden. It discloses the key side effect of not publishing, which is important. But it does not mention other behavioral traits such as idempotency, permissions, rate limits, or how existing draft comments are handled.

    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 immediately states the action, resource, and non-publishing behavior. There is no filler or redundant content, making it highly concise and front-loaded.

    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 6 parameters, 0% schema coverage, and no annotations, a single sentence is insufficient. The description only conveys the overall purpose and non-publication, but leaves essential operational details and parameter semantics unaddressed. The presence of an output schema reduces the need to explain return values, but too many gaps remain.

    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 description coverage is 0%, so the description must compensate for missing parameter meaning. It only hints at 'review findings JSON', which loosely maps to review_json or findings, but leaves revision_id, max_comments, include_title, and is_new_file completely unexplained.

    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 ('creates') and names the exact resource ('draft inline comments on a Differential revision') and the input type ('review findings JSON'). It also clarifies the non-publishing behavior, which clearly distinguishes it from the sibling tool 'review-phab'.

    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 by stating that the tool creates draft comments and explicitly says it does not publish, which is a useful when-not signal. However, it does not explicitly name alternatives or describe scenarios when to prefer 'review-phab'.

    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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