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73882

feature-separate-eval-mcp

by 73882

Server Quality Checklist

58%
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  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool covers a distinct stage of the evaluation workflow: status lists pending records, check performs a pre-flight evaluability test, and run executes the actual evaluation. There is no meaningful overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow the same feature_separate_eval_ prefix plus a single clear verb: status, check, run. The naming pattern is entirely consistent and predictable.

    Tool Count5/5

    Three tools is appropriate for this focused evaluation pipeline. Each tool provides a distinct, necessary function, and none are redundant or ornamental.

    Completeness5/5

    The tool set covers the full workflow from discovering the next pending record, to verifying evaluability, to running the evaluation and persisting results. No critical missing operation is evident for the server's stated purpose.

  • Average 3.9/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 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

  • Behavior4/5

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

    With no annotations provided, the description carries the behavioral burden. It does well by disclosing that data is sent to a configured Judge, that patent records trigger an external PatSnap call requesting only CLMS, that results are persisted, and that network access must be approved. It does not cover all possible side effects or failure behavior, but the most consequential behaviors are transparent.

    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 three tightly written sentences. It front-loads the core purpose, then provides the essential process detail, and ends with an important safety condition. No repeated or redundant information is present.

    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 description covers purpose, the Judge interaction, the patent-network special case, persistence, and the allow_network constraint. Given the tool has 7 parameters, no annotations, and sibling tools for status/checking, it would benefit from explaining keep_pending and the two max-feature parameters, and from routing the agent to the correct sibling when appropriate.

    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 0%, so parameter semantics must come from the description. It adds meaning for allow_network, patent_number, judge_model, and implicitly record_id by mentioning decompositions, Judge, PatSnap, and the confirmation condition. However, keep_pending, max_feature_density, and max_features_per_claim remain unexplained, so there are clear gaps.

    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's job: 'Evaluate one decomposition and return its human report and persisted result.' This is a specific verb and resource, and the mention of a returned report distinguishes it from the likely status/check siblings. It stops short of explicitly contrasting itself with those siblings, so it gets a 4 rather than a 5.

    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 when to use the tool: when a decomposition needs to be evaluated. It gives a concrete conditional for patent records and an explicit safety rule for allow_network, which is useful. However, it does not mention the sibling tools or state when to use this tool instead of feature_separate_eval_status or feature_separate_eval_check.

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

  • Behavior4/5

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

    With no annotations, the description carries the burden of behavioral disclosure. It adds a meaningful behavioral trait: 'never uses network,' which signals a read-only, side-effect-free operation beyond what the schema shows. It does not discuss side effects, but listing operations are inherently non-mutating.

    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 one compact sentence with no filler. The core behavior is front-loaded, and the network disclaimer adds relevant context without bloating the text.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a zero-parameter read-only status tool with an output schema present, the description is sufficiently complete. It states what the tool lists and explicitly notes the network behavior, leaving no critical ambiguity for invocation.

    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, so parameter-level semantics are irrelevant. Baseline 4 applies because there is no parameter burden for the description to carry.

    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 uses a specific verb ('List') and concrete resources ('recorded decompositions and the next pending record'), making the purpose immediately clear. It does not explicitly name sibling tools, but the behavior described is distinct enough from check/run.

    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 about when to use this tool versus its siblings. 'Never uses network' hints at a safe, non-I/O operation, but no when-to-use or when-not-to-use context is provided.

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

  • Behavior4/5

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

    With no annotations provided, the description carries the full burden. It discloses that patent records query only the CLMS field from the PatSnap host, require allow_network=true after user confirmation, are checked locally for free-text records, and do not invoke Judge. This adds meaningful behavioral context beyond what the schema provides.

    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 compact and front-loaded with the core purpose, followed by concise edge-case-specific guidance. Every sentence adds value, and there is no redundant or padding text.

    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 description explains the key behavioral distinction, but it leaves operational ambiguity around how to specify a patent record vs a free-text record. Since there are three parameters with zero schema description coverage, the description should more explicitly connect record_id and patent_number to the two record types. The presence of an output schema reduces the need to describe return values, but parameter usage remains incomplete.

    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 0%, so the description must compensate. It does explain allow_network's role and links network permission to patent vs free-text record types. However, it does not explicitly define how record_id and patent_number map to these record types or when each is required, leaving some parameter semantics implicit.

    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 states a specific action ('Check whether one record is evaluable') and adds a clear differentiator: it does so 'without calling Judge.' This separates it from the sibling tools feature_separate_eval_run (executes evaluation) and feature_separate_eval_status (reports status).

    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 for when to use the tool, distinguishing patent records from free-text records and specifying network requirements for each. It does not explicitly name alternatives or state when not to use the tool, but the behavior is contextually clear.

    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.
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