Server Quality Checklist

Tool Scores

• execute_notebook_codeA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description covers setup dependency, default URL, execution types, return types, and errors. However, it does not disclose side effects (modifying notebook state) or safety considerations (e.g., code execution risks). Good but not fully comprehensive.

  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 sections for setup, args, returns, raises. Front-loaded with purpose. Example code block is helpful. Minor bloat: redundant 'MCP best practices' line and repeated text. Still efficient for the complexity.

  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?

  Covers all parameters, returns, errors, and setup dependency. Output schema exists, so return details not required. Lacks explanation of invalid notebook_path handling or deeper return structure usage. Adequate for a tool with moderate complexity.

  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?

  Schema coverage is 0%, so description compensates fully. Explains notebook_path with .ipynb addition, execution_type with two named options, position_index for execute_cell, and package_names for install_packages. Adds critical meaning beyond types and defaults.

  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?

  Clearly states 'Execute code in a Jupyter notebook on the user-provided server.' Differentiates from sibling tools (modify_notebook_cells, query_notebook, setup_notebook) by focusing on execution operations. Consolidates all execution types into one tool.

  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?

  Provides explicit setup requirement (must call setup_notebook first) and describes default behavior. Lists two execution types with corresponding parameters. Lacks explicit alternatives (e.g., when to use modify_notebook_cells instead), but the context is strong enough for an agent to infer.

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

• modify_notebook_cellsA
  4.7/5.0
  Behavior5/5

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

  With no annotations, the description fully bears the burden of disclosing behavior. It details execution default, error types (ValueError, McpError, IndexError), and return values per operation, leaving no behavioral ambiguity.

  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 long but well-organized with clear sections (Args, Returns, Raises) and front-loaded purpose. Minor redundancy exists (e.g., repeating default execute behavior), but overall it is efficient for the information provided.

  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 no output schema, the description comprehensively covers return values for all operations and lists potential errors. It also clarifies the dependency on setup_notebook, making the tool fully self-contained in context.

  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?

  Schema coverage is 0%, so the description must explain each parameter. It does so thoroughly, including examples, default values, and conditionally required fields (e.g., position_index for edit/delete). This adds significant value beyond the 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 tool modifies notebook cells (add, edit, delete) and explicitly distinguishes from siblings by noting it consolidates all cell modification operations. The verb 'modify' and specific operations listed make the purpose unambiguous.

  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 explicit guidance on prerequisite setup (calling setup_notebook) and default behavior (execute=True). It does not explicitly contrast with siblings like execute_notebook_code, but the context is clear enough for an agent to infer appropriate usage.

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

• setup_notebookA
  4.7/5.0
  Behavior4/5

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

  Discloses that it connects to an existing server, stores the server URL for subsequent calls, and creates an empty notebook if needed. Does not mention overwriting behavior or authentication, but covers core behavioral traits. Annotations are absent, so description carries the burden.

  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 bold emphasis on key points, an example, and bullet-style parameter explanations. It is somewhat lengthy but each part adds value; slight redundancy in storage explanation could be trimmed.

  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 no output schema, the description sufficiently explains the return value as a dict with status. It covers the tool's role in the workflow, parameter details, environmental assumption, and positioning relative to siblings. Complete for a setup tool with two parameters.

  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 compensates fully: explains notebook_path as relative to Jupyter server root, and server_url with explicit recommendation, default, common values, and storage behavior. This provides essential meaning beyond the 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 tool prepares a notebook and connects to a kernel, with specific actions: 'Prepare notebook for use and connect to the kernel' and 'Will create a new empty Jupyter notebook if needed'. This distinguishes it from sibling tools like modify_notebook_cells and execute_notebook_code.

  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?

  Explicitly declares 'CALL THIS FIRST' and states it must be called before other notebook tools. Provides example usage showing the correct sequence and mentions alternatives like modify_notebook_cells for adding content. Also notes the required prerequisite of a running Jupyter server.

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

• query_notebookA
  4.9/5.0
  Behavior5/5

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

  Without annotations, the description fully discloses behavioral traits: it's read-only (no mutations), handles connection to Jupyter server with defaults, and enumerates all query types with their effects. It also lists possible exceptions (ValueError, McpError) for error handling transparency.

  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 (introduction, configuration note, args, returns, examples, raises). However, it is somewhat verbose, especially with the configuration note being repeated in the args section. A slightly more concise version would be ideal, but the organization is good.

  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?

  Despite no annotations, the description is comprehensive: it covers all 6 parameters, 4 query types with behaviors, return types, default values, error cases, and provides multiple examples. The output schema is effectively described in the Returns section, making the tool fully understandable without external documentation.

  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 compensates thoroughly. It explains each parameter in detail, including the distinction between execution_count and position_index, the automatic .ipynb extension, and the purpose of server_url. This adds essential meaning beyond 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 it queries notebook information and metadata, consolidating all read-only operations. It distinguishes itself from sibling tools like execute_notebook_code and modify_notebook_cells, making its purpose unambiguous.

  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 (read-only queries) versus alternatives (execute or modify). It also offers a recommended workflow with setup_notebook, explains server URL configuration, and warns against common parameter confusion, leaving no doubt about usage context.

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