Server Quality Checklist

Tool Scores

• nanobanana_generate_imageA
  4/5.0
  Behavior4/5

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

  Annotations provide readOnlyHint=false, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond annotations: it explains cost implications of different models, supported aspect ratios, and the file-saving behavior with overwrite option. This enhances understanding of the tool's operational 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 efficiently structured with clear sections (overview, models, aspect ratios, example) and every sentence adds value. The example is particularly helpful for understanding usage without being verbose. The information is well-organized and front-loaded.

  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 complexity of an image generation tool with 5 parameters and no output schema, the description provides good context about models, costs, aspect ratios, and file handling. However, it doesn't explain what the tool returns (e.g., success confirmation, error handling) or provide guidance on prompt engineering best practices.

  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?

  With 100% schema description coverage, the schema already documents all 5 parameters thoroughly. The description adds minimal additional semantic context through the example showing typical usage patterns, but doesn't provide significant new information beyond what's in the schema descriptions.

  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 ('Generate an image'), resource ('using Gemini's native image generation'), and distinguishes from siblings by focusing on image creation rather than queue management. It provides a concrete example that reinforces the purpose.

  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 through the example and model descriptions, suggesting when to choose different models based on speed vs. quality. However, it doesn't explicitly state when to use this tool versus the queue-related siblings or provide clear exclusions or alternatives.

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

• nanobanana_process_queueA
  4.2/5.0
  Behavior4/5

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

  The description adds valuable behavioral context beyond annotations: it explains file movement ('prompt files are moved to completed_dir with timestamp'), operational modes, and overwrite strategies. Annotations cover basic hints (e.g., not read-only, not destructive), but the description enriches this with practical details like no API calls in certain modes. No contradictions with annotations exist.

  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 well-structured and front-loaded with the core purpose, followed by organized sections for modes, overwrite strategies, and an example. Every sentence adds value, with no wasted words, making it efficient and easy to scan.

  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 (batch processing with multiple modes and file operations) and lack of an output schema, the description does a good job covering behavior, parameters, and usage. However, it could improve by mentioning error handling or output format details, which would be needed for full completeness in this context.

  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?

  With 100% schema description coverage, the input schema already documents all parameters thoroughly. The description adds minimal extra semantics, such as clarifying that 'output_dir' is used 'if prompt has relative path' and providing an example with parameter values. This meets the baseline for high schema coverage but doesn't significantly enhance understanding 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's purpose: 'Process all prompt files in the queue directory and generate images.' This specifies the verb ('process'), resource ('prompt files'), and outcome ('generate images'), distinguishing it from sibling tools like 'nanobanana_generate_image' (single generation) and 'nanobanana_list_queue' (listing only).

  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 the tool by detailing three operational modes (validate_only, dry_run, full generation) and overwrite strategies. However, it does not explicitly state when to use this batch processing tool versus the sibling 'nanobanana_generate_image' for single generations, which would be needed for a perfect score.

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

• nanobanana_list_queueA
  4.4/5.0
  Behavior4/5

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

  Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, covering safety and idempotency. The description adds valuable behavioral context beyond annotations: it specifies the tool scans for markdown files, validates them, checks for output file conflicts, and provides previews. However, it doesn't mention rate limits or authentication needs.

  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 well-structured and front-loaded: the first sentence states the core purpose, followed by bullet points detailing outputs, and ends with usage guidance and an example. Every sentence earns its place without redundancy.

  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 moderate complexity, rich annotations, and 100% schema coverage, the description is mostly complete. It lacks an output schema, but the description outlines what the tool provides (validation status, conflict detection, preview). A minor gap is no explicit mention of error handling or output format details.

  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 100%, with clear descriptions for all three parameters (queue_dir, validate, check_conflicts). The description adds minimal value beyond the schema, only implying parameter usage through the example. Baseline 3 is appropriate since the schema does the heavy lifting.

  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 verbs ('list and validate prompt files') and resources ('queue directory'), distinguishing it from siblings like 'nanobanana_generate_image' (which creates images) and 'nanobanana_process_queue' (which processes the queue). It explicitly mentions scanning markdown prompt files, validation, conflict detection, and content preview.

  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: 'Use this to review what will be generated before running process_queue.' This clearly distinguishes it from the sibling 'nanobanana_process_queue' and indicates it's for pre-processing inspection rather than execution.

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