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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: append_row adds rows, create_sheet creates sheets, get_sheet_info retrieves metadata, read_sheet reads data, and write_sheet writes data. The descriptions clearly differentiate between operations on data versus structure.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with snake_case naming (e.g., append_row, create_sheet, read_sheet). The verbs are action-oriented and predictable, making the set easy to navigate.

    Tool Count4/5

    Five tools is reasonable for a Google Sheets server, covering core operations like reading, writing, appending, creating sheets, and getting info. It's slightly lean but functional; minor additions like update or delete operations could enhance it without being necessary.

    Completeness4/5

    The tools cover essential CRUD-like operations for Google Sheets: create (create_sheet), read (read_sheet, get_sheet_info), and write/append (write_sheet, append_row). A minor gap is the lack of explicit update or delete tools, but agents can work around this using write_sheet for updates.

  • Average 2.9/5 across 5 of 5 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
  • This repository is licensed under MIT License.

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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 full burden for behavioral disclosure. It states the action ('append row') but doesn't mention whether this requires specific permissions, what happens if the spreadsheet doesn't exist, whether the operation is atomic, or what error conditions might occur. For a mutation tool with zero annotation coverage, this is insufficient.

    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, clear sentence in Japanese that directly states the tool's function without any unnecessary words. It's perfectly front-loaded and wastes no space on redundant information.

    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 mutation tool with no annotations and no output schema, the description is too minimal. It doesn't address what happens after appending (success indicators, error responses), doesn't mention constraints or limitations, and doesn't help the agent understand how this differs from similar spreadsheet manipulation tools.

    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 description coverage is 100%, with all three parameters clearly documented in the schema. The description doesn't add any parameter-specific information beyond what the schema already provides, so it meets the baseline for adequate but not exceptional parameter documentation.

    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 action ('append row') and target resource ('spreadsheet'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'write_sheet' or 'create_sheet', which might have overlapping functionality for spreadsheet modification.

    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 alternatives like 'write_sheet' or 'create_sheet'. There's no mention of prerequisites, constraints, or typical use cases, leaving the agent to guess based on tool names alone.

    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 carries the full burden of behavioral disclosure. It states the action ('creates') but doesn't cover critical traits like required permissions, whether this is a destructive operation, error handling, or what happens if a sheet with the same name exists. This is inadequate for a mutation tool with zero annotation coverage.

    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 in Japanese that directly states the tool's purpose with zero wasted words. It is appropriately sized and front-loaded, making it easy to parse quickly.

    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 the complexity of a creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., success confirmation, new sheet details), error conditions, or behavioral nuances, leaving significant gaps for the agent to infer.

    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 description coverage is 100%, with both parameters ('spreadsheetId' and 'sheetName') clearly documented in the schema. The description adds no additional meaning about the parameters beyond what the schema provides, so it meets the baseline score for high schema coverage without compensating value.

    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 '新しいシートを作成します' (creates a new sheet) clearly states the verb ('creates') and resource ('sheet'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential siblings like 'append_row' or 'write_sheet' that might also modify sheets, so it doesn't reach the highest clarity level.

    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 alternatives. It doesn't mention prerequisites (e.g., needing an existing spreadsheet), exclusions (e.g., not for modifying existing sheets), or comparisons to sibling tools like 'append_row' or 'write_sheet', leaving the agent with no usage context.

    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 carries the full burden of behavioral disclosure. It only states the action ('取得します') without detailing traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what '基本情報' (basic information) entails in terms of return format or scope. This leaves significant gaps for a tool with no annotation coverage.

    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 in Japanese that directly states the purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

    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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what '基本情報' includes (e.g., metadata, properties), behavioral aspects like error handling, or how it differs from siblings. For a tool with no structured data beyond the input schema, more context is needed to be fully helpful.

    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 has 100% description coverage, clearly documenting the single required parameter 'spreadsheetId'. The description adds no additional meaning beyond this, as it doesn't elaborate on parameter usage or constraints. According to the rules, with high schema coverage, the baseline is 3 even without param info in the description.

    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 action ('取得します' - get/retrieve) and resource ('スプレッドシートの基本情報' - basic information of a spreadsheet), providing a specific purpose. However, it doesn't explicitly differentiate from sibling tools like 'read_sheet', which might have overlapping functionality, preventing a perfect score.

    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 alternatives like 'read_sheet' or other siblings. There's no mention of prerequisites, context, or exclusions, leaving the agent with minimal usage direction beyond the basic purpose.

    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 of behavioral disclosure. While it states the tool reads data, it doesn't describe what happens on errors (e.g., invalid spreadsheetId or range), whether it requires specific permissions, the format of returned data, or any rate limits. For a read operation with zero annotation coverage, this leaves significant gaps in understanding its behavior.

    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 in Japanese that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple read operation and front-loads the core functionality.

    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 the tool has no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't address what data is returned (e.g., array of values, formatting), error handling, or usage context compared to siblings. For a read tool with 2 parameters, more behavioral context would be helpful.

    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 description coverage is 100%, with both parameters clearly documented in the input schema (spreadsheetId and range with examples). The description adds no additional semantic context beyond what's in the schema, such as explaining range syntax variations or spreadsheetId sourcing. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 action ('読み取ります' - reads) and resource ('スプレッドシートの指定された範囲のデータ' - data from a specified range in a spreadsheet). It distinguishes from siblings like 'append_row' or 'write_sheet' by focusing on reading rather than modifying data. However, it doesn't explicitly differentiate from 'get_sheet_info' which might also retrieve spreadsheet data.

    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 alternatives like 'get_sheet_info' (which might retrieve metadata rather than cell data) or 'write_sheet' (for writing data). There's no mention of prerequisites, error conditions, or typical use cases beyond the basic function.

    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 carries the full burden of behavioral disclosure. It states the tool writes data to a spreadsheet range, implying a mutation operation, but doesn't specify whether this overwrites existing data, requires specific permissions, or has side effects like formatting changes. This is a significant gap for a write tool with zero annotation coverage.

    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 in Japanese that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

    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 write operation tool with no annotations and no output schema, the description is insufficient. It lacks details on behavioral traits (e.g., overwrite behavior, error conditions), usage context compared to siblings, and expected outcomes. This leaves the agent poorly equipped to use the tool effectively in complex scenarios.

    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 description coverage is 100%, with clear descriptions for all three parameters (spreadsheetId, range, values). The description adds no additional meaning beyond what the schema provides, such as explaining the format of 'values' or constraints on 'range'. Given the high schema coverage, a baseline score of 3 is appropriate.

    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 action ('書き込みます' - writes) and resource ('スプレッドシートの指定された範囲' - specified range of spreadsheet), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'append_row' or 'create_sheet', which is why it doesn't reach 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 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 alternatives like 'append_row' (which might add data without overwriting) or 'create_sheet' (which creates new sheets). There's no mention of prerequisites, such as needing an existing spreadsheet, or exclusions, leaving the agent with little context for tool selection.

    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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