Server Quality Checklist

Tool Scores

• view_raw_dataC
  2.7/5.0
  Behavior1/5

  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. The phrase 'View the raw data' implies a read-only operation, but it does not explicitly state side effects, data safety, authentication needs, or how output is structured. There is no information about slicing limits or potential performance implications, which is a significant gap for an 11-parameter tool.

  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 extremely concise (one sentence) and directly states the core purpose without redundancy. It is front-loaded and efficient, though it may be too terse given the tool's complexity, but conciseness itself is well-served.

  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?

  Despite having a rich schema and output schema, the description does not explain the tool's behavior such as how raw data is formatted, the effect of row/column slicing, or interaction with filter parameters. For a tool with 11 parameters and complex semantics (e.g., nested key access, glob patterns), this single sentence is insufficient to convey the full capability, leaving the agent to discover behavior through the schema alone.

  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 provides descriptions for all 11 parameters (100% coverage), including nested key retrieval, filter operators, and column/gene selection. Since the schema fully documents parameter meanings, the description does not need to add extra details, and 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 ('View') and resource ('raw data of an AnnData object'), which is distinct from the sibling tools get_summary and get_descriptive_stats that imply aggregated views. However, it does not explicitly differentiate itself, relying on the tool name and minimal description.

  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 siblings, nor any prerequisites or context such as when raw data viewing is appropriate. It is a single sentence with no alternatives or exclusions mentioned, leaving the agent to infer usage.

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

• get_summaryB
  3.1/5.0
  Behavior2/5

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

  With no annotations, the description carries the full burden. It states the input source but does not disclose whether the operation is read-only, what side effects might occur (e.g., network access), or what a 'summary' includes beyond the name.

  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 that immediately states the core function. No wasted words or structure issues.

  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 tool is simple, has an output schema, and 100% parameter coverage. However, it lacks usage guidelines and behavioral transparency, leaving contextual gaps that prevent it from being fully complete for an agent deciding when to invoke it.

  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 coverage is 100%, with the description for 'path' already specifying absolute path or URL and file types (.h5ad/.zarr). The tool description adds no additional parameter context, so baseline 3 is appropriate.

  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 'Get a summary of an AnnData object from a file or URL,' using a specific verb and resource. It distinguishes the purpose inherently from siblings by focusing on a high-level summary rather than raw data or descriptive statistics.

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

  Usage Guidelines1/5

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

  No guidance is provided about when to use this tool versus the sibling tools (view_raw_data, get_descriptive_stats). There are no context notes, alternatives, or exclusions.

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

• get_descriptive_statsA
  3.8/5.0
  Behavior3/5

  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 computes statistics and supports optional filtering, but it does not explicitly state that the operation is read-only, mention performance considerations, or describe any side effects. The nature of the tool makes read-only behavior likely, but this is not explicitly disclosed.

  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, concise sentence that front-loads the tool's purpose. It contains no redundant information and every word adds value. This is an exemplar of conciseness.

  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 (9 parameters) and the presence of an output schema, the description is adequately complete. It introduces the core purpose and filtering capability, while the structured schema and output schema handle detailed parameter and return specifications. It could offer more guidance on usage scenarios, but the rich schema compensates.

  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 provides 100% parameter coverage with detailed descriptions for all 9 parameters. The tool description adds minimal parameter context, such as 'attribute or attribute value' hinting at the key/filter relationships, but the schema already does the heavy lifting, so the baseline of 3 is appropriate.

  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 identifies the tool's function: computing basic descriptive statistics for AnnData attributes, optionally filtered. It uses specific verbs and resources, and the distinction from siblings (view_raw_data, get_summary) is evident from the emphasis on statistics rather than raw viewing or summarization.

  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 usage when descriptive statistics are needed, but it does not explicitly contrast with alternatives like get_summary or view_raw_data, nor does it state exclusions. It provides enough context that the AI can infer the general use case but lacks explicit guidance.

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