Server Quality Checklist

Tool Scores

• delete_chartA
  3.5/5.0
  Behavior3/5

  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 clearly indicates this is a destructive operation ('Delete... permanently'), which is critical context. However, it lacks details on permissions, error conditions, or irreversible consequences beyond deletion. It adds some value but not comprehensive behavioral context.

  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?

  The description is appropriately sized and front-loaded, with the core purpose stated first. The header and separator are slightly verbose but not excessive. The Args and Returns sections are structured clearly, though the header could be more concise.

  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 the tool's complexity (destructive operation), no annotations, and an output schema exists (returns confirmation message), the description is reasonably complete. It covers the action, parameter, and return, but could improve with more behavioral details (e.g., permissions, side effects) to fully compensate for the lack of annotations.

  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 documents the single parameter ('chart_id: ID of the chart to delete'), adding meaning beyond the schema's basic title. However, it does not explain format, validation, or sourcing of the ID, leaving gaps in 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 specific action ('Delete a Datawrapper chart permanently') with the resource ('Datawrapper chart'), distinguishing it from sibling tools like 'create_chart', 'update_chart', or 'get_chart'. The purpose is unambiguous and directly addresses what the tool does.

  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 does not mention prerequisites (e.g., needing the chart ID), exclusions (e.g., not for published charts), or comparisons to siblings like 'update_chart' or 'publish_chart'. Usage is implied but not explicitly stated.

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

• get_chartA
  4.3/5.0
  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 of behavioral disclosure. It effectively describes the tool's behavior: it retrieves comprehensive chart data, including configuration and URLs, and outlines potential use cases (e.g., understanding styling, adapting configuration, cloning styling). It does not mention permissions, rate limits, or error handling, but covers core functionality well for a read operation.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is appropriately sized and front-loaded with the core purpose. However, it includes redundant sections: the 'Returns:' and 'Args:' lists repeat information already stated in the body, and the '⚠️ DATAWRAPPER MCP TOOL ⚠️' header is unnecessary clutter. Some sentences could be more streamlined.

  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?

  Given the tool's low complexity (one parameter), lack of annotations, and presence of an output schema (which handles return values), the description is complete enough. It covers purpose, usage context, parameter meaning, and behavioral aspects without needing to detail output structure, making it adequate for the agent's needs.

  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 input schema has 0% description coverage, but the description compensates by explaining the single parameter: 'chart_id: ID of the chart to retrieve.' This adds clear meaning beyond the schema's basic type information. For a tool with only one parameter, this is sufficient to achieve a high score, though it doesn't detail format constraints or examples.

  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 tool's purpose: 'Get information about an existing Datawrapper chart, including its complete configuration, metadata, and URLs.' It specifies the verb ('Get'), resource ('Datawrapper chart'), and scope ('complete configuration, metadata, and URLs'), distinguishing it from siblings like create_chart, delete_chart, or update_chart.

  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 this tool: to retrieve information about an existing chart. It implicitly contrasts with siblings by focusing on retrieval rather than creation, deletion, or modification. However, it does not explicitly state when NOT to use it or name specific alternatives for overlapping use cases.

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

• export_chart_pngA
  4.5/5.0
  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 of behavioral disclosure. It effectively describes key behaviors: it's a read/export operation (implied by 'export'), requires a pre-existing chart, supports high-resolution output, and returns PNG content. It doesn't mention rate limits, authentication needs, or error conditions, but covers the core operational behavior well.

  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?

  The description is well-structured with clear sections (warning header, purpose statement, usage guidelines, parameter explanations, return value). While slightly longer due to the detailed parameter section, every sentence earns its place by providing essential information. The front-loaded purpose and usage guidelines are immediately clear.

  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 the tool's complexity (8 parameters, export operation) and the presence of an output schema (which handles return value documentation), the description provides good completeness. It covers purpose, usage constraints, parameter semantics, and behavioral context. It doesn't explain error cases or authentication requirements, but with an output schema and detailed parameter explanations, it's mostly complete.

  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?

  With 0% schema description coverage, the description compensates by providing a detailed parameter section that explains all 8 parameters with clear semantic meaning beyond just their names. It explains what each parameter controls (e.g., 'Scale multiplier for resolution', 'Margin around visualization'), though it doesn't specify value ranges or constraints. This significantly adds value over the bare schema.

  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 specific action ('Export a Datawrapper chart as PNG and display it inline'), identifies the resource ('Datawrapper chart'), and distinguishes it from siblings by mentioning it requires a chart created first using create_chart. It goes beyond just restating the name by specifying the output format and display method.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides explicit guidance on when to use ('Only use this tool when the user explicitly requests to see the chart image or export it as PNG') and when not to use ('Do not automatically export charts after creation unless specifically asked'). It also references the prerequisite sibling tool ('The chart must be created first using create_chart'), offering clear alternatives and context.

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

• update_chartA
  4.5/5.0
  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 of behavioral disclosure. It does an excellent job describing limitations (chart type immutability), what can and cannot be updated, validation behavior (Pydantic validation), and merge behavior (config merged with existing). It also mentions the return format (confirmation message with editor URL). The only minor gap is no mention of authentication requirements or rate limits.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is comprehensive but lengthy (over 400 words). While most content is valuable, some sections like the styling examples and documentation link could be more concise. The information is well-structured with clear sections, but it's not optimally front-loaded for quick scanning.

  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?

  Given the tool's complexity (mutation operation with 3 parameters, no annotations, but with output schema), the description is remarkably complete. It covers purpose, limitations, usage guidelines, parameter semantics, behavioral details, and references to other tools. The output schema handles return values, so the description appropriately focuses on everything else the agent needs to know.

  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?

  With 0% schema description coverage, the description must compensate for all three parameters. It clearly explains chart_id ('ID of the chart to update'), data ('New chart data (optional). Same formats as create_chart'), and chart_config ('Updated chart configuration using high-level Pydantic fields (optional)'). It provides formatting guidance and examples for chart_config, though more detail on data formats would be helpful.

  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 tool's purpose: 'Update an existing Datawrapper chart's data or configuration using Pydantic models.' It specifies the verb ('update'), resource ('existing Datawrapper chart'), and scope ('data or configuration'), and distinguishes it from sibling tools like create_chart by emphasizing it's for existing charts only.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides explicit usage guidelines: it states when to use this tool (for updating existing charts) and when not to use it (cannot change chart type, must use create_chart instead). It also mentions get_chart_schema as a reference for available fields, giving clear alternatives and prerequisites.

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

• create_chartA
  4.6/5.0
  Behavior4/5

  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 does an excellent job describing workflow patterns, best practices, and constraints (e.g., 'Let Datawrapper handle axis scaling automatically unless there's a specific reason to override'). It explains the return format ('Chart ID and editor URL') and provides extensive examples. The only minor gap is explicit mention of authentication requirements or rate limits.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is comprehensive but lengthy (over 700 words). While well-structured with clear sections (warning, purpose, best practices, examples, workflow, parameter details), it could be more front-loaded. The core purpose appears after the warning section, and some examples could be streamlined. Every sentence adds value, but the overall length reduces conciseness.

  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?

  Given the complexity (3 parameters with nested objects, 0% schema coverage, no annotations, but with output schema), the description is exceptionally complete. It covers purpose, usage guidelines, parameter semantics, workflow patterns, examples, and return values. The output schema exists, so the description appropriately focuses on explaining parameters and behavior rather than return format details.

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

  Parameters5/5

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

  With 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all three parameters. For 'data', it explains recommended formats, preferred order, and alternative approaches. For 'chart_type', it references sibling tools and provides common examples. For 'chart_config', it explains this should be 'a complete Pydantic model dict' and provides extensive examples and styling patterns.

  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 tool's purpose: 'Create a Datawrapper chart with full control using Pydantic models.' It specifies the verb ('Create'), resource ('Datawrapper chart'), and scope ('full control'), distinguishing it from siblings like update_chart or delete_chart. The initial warning section reinforces this is the primary creation tool for Datawrapper integration.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides explicit guidance on when to use this tool versus alternatives. It starts with a strong directive: 'Use this MCP tool for ALL Datawrapper chart creation' and lists specific alternatives to avoid (Python package, direct API). It also references sibling tools like list_chart_types and get_chart_schema for preparatory work, and mentions styling workflows that guide when to apply customization.

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

• get_chart_schemaA
  4.6/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full burden. It discloses that the tool returns a JSON schema with details like properties, types, enums, defaults, and descriptions, which helps the agent understand the output format. However, it doesn't mention potential errors (e.g., invalid chart types), rate limits, or authentication needs, leaving some behavioral gaps. No contradiction with annotations exists.

  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?

  The description is well-structured with sections (e.g., workflow, args, returns) and uses bullet points for clarity. It's front-loaded with the core purpose. However, the warning banner and markdown formatting add some verbosity that isn't strictly necessary, slightly reducing efficiency. Overall, most sentences earn their place by providing useful information.

  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?

  Given the tool's low complexity (1 parameter), no annotations, and the presence of an output schema (which handles return values), the description is complete enough. It covers purpose, usage guidelines, parameter semantics, and output expectations. The reference to external documentation adds extra context, making it suitable for an agent to invoke the tool correctly without gaps.

  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 schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'chart_type' is used to 'get schema for a specific chart type,' implying it's an identifier for chart types (e.g., 'line', 'bar'). While it doesn't list possible values or formats, it clarifies the parameter's role beyond the basic schema. With only one parameter, this is sufficient for a high score.

  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 tool's purpose: 'Get the Pydantic JSON schema for a specific chart type.' It specifies the verb ('Get') and resource ('Pydantic JSON schema'), and distinguishes it from siblings like 'create_chart' or 'update_chart' by focusing on schema discovery rather than chart manipulation. The mention of 'primary tool for discovering styling and configuration options' further clarifies its exploratory role.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides explicit usage guidance: 'Use this tool first to explore options,' indicating it should be used before other tools like 'create_chart' or 'update_chart.' It also references an external resource ('https://datawrapper.readthedocs.io/') for detailed examples, offering a clear workflow. This effectively distinguishes when to use this tool versus alternatives in the sibling list.

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

• list_chart_typesA
  4.6/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries full burden. It discloses that this is a read operation (listing), mentions it's part of Datawrapper MCP integration, and describes the return format ('List of available chart types with descriptions'). However, it doesn't mention potential limitations like rate limits or authentication requirements.

  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?

  Well-structured with clear sections: warning banner, purpose statement, usage guidance, and return description. The warning banner adds context but isn't strictly necessary for tool understanding. The core information is front-loaded and efficiently presented.

  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?

  Complete for a parameterless discovery tool. The description explains purpose, usage context, and output format. With an output schema available, the description doesn't need to detail return values further. It provides all necessary context for an agent to understand when and how to use this tool.

  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 0 parameters, and schema description coverage is 100%. The description appropriately doesn't discuss parameters since none exist. It focuses instead on the tool's purpose and output, which is appropriate for a parameterless tool.

  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 tool's purpose with specific verb ('List') and resource ('all available Datawrapper chart types with brief descriptions'). It distinguishes from siblings by focusing on discovery rather than creation, deletion, or modification of charts.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Explicit guidance is provided: 'Use this tool to discover which chart types you can create' and 'After choosing a type, use get_chart_schema(chart_type) to explore detailed configuration options.' This clearly indicates when to use this tool versus the sibling get_chart_schema tool.

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

• publish_chartA
  4.6/5.0
  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 of behavioral disclosure. It effectively describes key behaviors: it makes charts publicly accessible (implying a mutation/permissions change), returns a public URL, and includes a warning about explicit user requests. However, it lacks details on potential side effects like irreversible changes or authentication requirements.

  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?

  The description is appropriately sized and front-loaded, with the core purpose stated first. However, the initial warning banner ('⚠️ DATAWRAPPER MCP TOOL ⚠️') and separator ('---') add minor clutter without critical information, slightly reducing efficiency.

  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?

  Given the tool's moderate complexity (1 parameter, mutation operation), no annotations, and an output schema present (which handles return values), the description is complete enough. It covers purpose, usage guidelines, parameter meaning, and key behavioral aspects, providing adequate context for an agent to use the tool correctly.

  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 schema description coverage is 0%, so the description must compensate. It clearly explains the single parameter 'chart_id' as 'ID of the chart to publish', adding essential meaning beyond the schema's basic type information. This is sufficient for the single parameter, though it doesn't cover format or validation details.

  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 specific action ('Publish a Datawrapper chart') and the resource ('Datawrapper chart'), distinguishing it from siblings like create_chart, delete_chart, or update_chart by focusing on making charts publicly accessible rather than creating, removing, or modifying them.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  It provides explicit guidance on when to use this tool ('when the user explicitly requests to publish the chart') and when not to use it ('Do not automatically publish charts after creation unless specifically asked'), clearly differentiating it from alternatives like create_chart or update_chart that might be used in other contexts.

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