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ZidingWang

Dual Water Tank MCP

by ZidingWang
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Python
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct role: preview explores data, fit_dual_water_tank fits a single file, and batch_fit_dual_water_tank handles multiple files. There is no overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case: preview_..., fit_..., batch_fit_.... The model name 'dual_water_tank' appears consistently.

    Tool Count4/5

    With only three tools, the set is minimal but scoped to the core tasks of data preview and fitting. It could benefit from additional tools for result retrieval, but still feels appropriately focused.

    Completeness3/5

    The surface covers the essential workflow (preview, single fit, batch fit), but lacks tools to retrieve fitted parameters or batch summaries in a structured manner, relying on file outputs. This is a notable gap for an agent.

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

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

    • No community issues in the last 6 months
    • 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

  • This repository is licensed under Apache 2.0.

  • 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 bears full responsibility for behavioral disclosure. It mentions automatic inference but does not describe key behaviors such as whether the tool is read-only, what outputs it produces, potential side effects (e.g., file creation), or performance considerations like long runtimes. This is insufficient for a tool with 22 parameters.

    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?

    Two sentences, no wasted words, front-loaded with the primary action. Excellent conciseness.

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

    Completeness1/5

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

    Given the tool's complexity (22 parameters, no output schema, no annotations), the description is severely incomplete. It does not specify the return value or output format, lack of guidance on required vs optional parameters, and no mention of error conditions or constraints. An agent cannot reliably use this tool without additional context.

    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 only 27%, and the description does not explain any parameters beyond mentioning automatic inference of direction, signs, and bounds. It adds little value beyond the schema, which itself leaves many parameters (e.g., seed, r_upper, max_points, generations, etc.) without documentation. The description should clarify key parameters and their roles.

    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 fits the dual water tank model to one file/sheet, distinguishing it from sibling tools like batch_fit (batch) and preview_dual_water_tank_data (preview). It also mentions automatic inference of direction, signs, and bounds, adding specificity.

    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 provides no explicit guidance on when to use this tool versus alternatives (e.g., batch fitting or preview). It implies use for single file/sheet fitting but lacks context on prerequisites or scenarios where other tools are preferable.

    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 exist, so the description must disclose behavior. It states the tool 'Reads' and 'infers', implying a read-only analysis. However, it omits details like whether the file is modified, authentication needs, or error handling.

    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?

    A single sentence conveying the tool's purpose and output. No unnecessary words, but could be enhanced with structured formatting for clarity.

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

    Completeness1/5

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

    With 5 parameters, no output schema, and no parameter descriptions in schema or description, the agent lacks critical information to use the tool correctly. The description fails to compensate for missing context.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, yet the description does not explain any of the 5 parameters (data_file, current, sheet_name, voltage_col, capacity_col). The agent gets no help understanding required or optional inputs beyond their names.

    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 'Read' and identifies the resource 'one full-cell data file'. It clearly states the tool's output: inferred columns, direction, span, and current. This distinguishes it from siblings which are for fitting, not previewing.

    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 provides no guidance on when to use this tool versus the sibling tools (batch_fit_dual_water_tank, fit_dual_water_tank). It does not specify prerequisites, limitations, or when not to use it.

    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, the description must disclose all behavioral traits. It mentions writing per-file curves and batch summaries, but does not explain side effects, permission needs, resource usage, output format, or performance 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 two concise sentences that front-load the core action and outputs. Every word contributes meaning without extraneous detail.

    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 19 parameters, no output schema, and no annotations, the description is too brief. It lacks information about output format, batch behavior, and parameter roles, making it incomplete for effective agent use.

    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 low (32%), yet the description adds no parameter explanations. It does not clarify key params like seed, files, current, or direction, leaving the agent to rely on schema alone.

    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 fits all supported files in a directory or a file list, and writes per-file curves and batch summaries. This distinguishes it from siblings like fit_dual_water_tank (single file) and preview_dual_water_tank_data (preview).

    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 use for batch processing multiple files, but does not explicitly contrast with single-file fitting or provide when-not-to-use guidance. No alternatives are mentioned despite siblings existing.

    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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