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by SDias14
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools are clearly distinct: one reads document contents, the other edits by replacing a string. No ambiguity exists between them.

    Naming Consistency4/5

    Both use a verb_noun pattern (read_doc_contents, edit_document), but the noun part is slightly inconsistent ('doc_contents' vs 'document'). Minor deviation from perfect consistency.

    Tool Count3/5

    With only 2 tools, the server feels thin for a document-focused interface. It is borderline on the lower end of acceptable, as a minimal read/edit pair can work but lacks breadth.

    Completeness2/5

    The surface is severely limited—no create, delete, list, or search capabilities. For a document management domain, this leaves major gaps that would require agents to use other tools or fail.

  • Average 3.5/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 3 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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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 provided, the description carries the full burden of behavioral disclosure. It fails to state whether the replacement applies to all occurrences or only the first, what happens if old_str is not found, or whether the edit is reversible. The schema adds the exact-match requirement, but the description itself reveals no behavioral detail beyond the core 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?

    The description is a single efficient sentence, front-loaded with the action, with zero wasted words (minor grammar aside). Every element serves the purpose.

    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?

    For a simple 3-parameter tool with no output schema and no annotations, the description falls short by omitting critical semantics such as whether all occurrences or just the first are replaced and the behavior when old_str is absent. These gaps prevent an agent from invoking the tool correctly in all cases.

    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 all three parameters are already documented in the schema, establishing a baseline of 3. The description reinforces the old-to-new replacement relationship but adds no new parameter semantics beyond what the schema already provides.

    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 operation: edit a document by replacing a string with a new string. The verb (replace/edit) and resource (document content) are specific, and the find-replace nature naturally distinguishes it from the sibling read_doc_contents, which only reads.

    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, no exclusions, and no prerequisites. The sibling read_doc_contents is never referenced, so an agent gets no help choosing between reading and editing for a given task.

    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?

    No annotations are present, so the description carries the full burden. It does disclose that the tool returns the contents as a string, which is useful. However, it does not explicitly state that the operation is read-only or non-destructive, nor does it mention potential side effects, errors, or permission requirements. Given the simplicity of a read operation, the description provides basic behavioral info but lacks deeper transparency.

    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, focused sentence that immediately states the action and return type. It contains no filler, redundant information, or unnecessary detail. Every word earns its place.

    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, clear purpose, and no output schema. The description covers the essential action and result. While it does not mention potential errors or permissions, these are common expectations for a read operation. Given the low complexity, the description is sufficiently complete.

    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 describes the single parameter 'doc_id' with 100% coverage ('Id of the document to read'). The description adds no additional meaning beyond what the schema provides. Since coverage is high, the baseline is 3, and the description does not enhance parameter understanding.

    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 (read) and the resource (document), and specifies the return value ('and return it as a string'). This is distinct from the sibling tool 'edit_document', which implies a modification tool. The purpose is unambiguous and specific.

    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 mention when to use this tool vs edit_document or other alternatives. It only says what it does, but the naming of the sibling tool suggests a read-only use case. No explicit 'when not to use' or alternative recommendations are provided, so the guidance is implied rather than stated.

    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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