Server Quality Checklist

Tool Scores

• get_screenA
  3.7/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden. It mentions the optional HTML return but does not disclose potential size impacts, pagination, or any side effects. Minimal but not misleading.

  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?

  Two concise sentences that directly state the tool's purpose and key parameter option. No wasted words.

  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?

  No output schema, so 'details and metadata' is vague. While the tool is simple, an agent might benefit from knowing what fields are returned. Adequate but not fully complete.

  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%, and the description adds minimal extra meaning beyond what the schema already states. For screen_id, it repeats the schema; for include_html, it rephrases slightly.

  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 'get details and metadata for a specific screen,' which distinguishes it from siblings like generate_screen (create) and list_screens (list all).

  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?

  No explicit guidance on when to use this versus alternatives, though sibling names imply the correct use case. The description does provide context for an optional parameter (include_html).

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

• generate_screenA
  4/5.0
  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 outputs both a screenshot (PNG) and HTML, which is a key behavioral trait. However, it does not cover other aspects like potential costs, authentication needs, rate limits, or side effects. This is moderate transparency.

  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 two sentences long, front-loaded with the core functionality in the first sentence and usage guidance in the second. Every word earns its place; no fluff or 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 has 4 parameters, no output schema, and no annotations, the description provides sufficient context for basic usage: what it generates and when to use it. It could be improved by mentioning the response format or error handling, but for a generation tool with clear output, it is fairly complete.

  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 for its 4 parameters. The description adds minimal extra meaning beyond the schema, except for the context of 'premium iOS mobile UI mockup' which gives design direction. Baseline 3 is appropriate as schema does 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 generates a premium iOS mobile UI mockup from a text brief, with both screenshot and HTML output. It distinguishes itself from siblings (get_screen, iterate_screen, list_screens) by focusing on creation rather than retrieval or iteration.

  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 explicitly says 'Use this when the user asks to design, mock up, or visualize a mobile app screen.' This provides clear context for when to use, though it does not explicitly list when not to use or mention alternatives. However, the context of sibling tools implies those alternatives.

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

• iterate_screenA
  4/5.0
  Behavior3/5

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

  With no annotations, the description carries full burden for behavioral disclosure. It implies mutation ("refine") but does not specify whether changes are reversible, what permissions are needed, or how the tool handles multiple iterations. The examples are non-destructive, but explicit security or side-effect info is missing.

  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 two sentences, front-loaded with the primary action, and includes practical examples without extraneous text. Every sentence adds value and the structure is efficient.

  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 no output schema and no annotations, the description adequately explains the tool's purpose and gives usage examples. However, it does not describe the return value (e.g., updated screen object) or confirm that screen_id must come from generate_screen, which is noted only in the schema. A bit more context on how to use the result would improve completeness.

  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?

  Input schema has 100% coverage, so baseline is 3. The description adds minimal extra meaning beyond the schema's parameter descriptions (e.g., "feedback" examples). The optional "name" parameter is described in both, but the description reinforces but does not significantly augment 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 refines an existing generated screen based on feedback, distinguishing it from siblings like generate_screen (creation) and get_screen (retrieval). The examples of feedback ("change color", "add a section") further clarify its purpose.

  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 specifies that this tool is for follow-up edits after generation, providing clear usage context. However, it does not explicitly state when not to use it (e.g., for new screens or non-generated screens) or mention prerequisites like valid screen_id from generate_screen.

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

• list_screensA
  4.2/5.0
  Behavior4/5

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

  The description implies a read-only operation without side effects, which is transparent for a list tool. No annotations exist, but the description is clear.

  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 efficiently conveys the tool's purpose and optional parameter without extraneous information.

  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?

  For a simple list tool with one optional parameter and no output schema, the description is adequate. It could be more complete by mentioning the return format, but it still provides sufficient context for an AI agent.

  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 a clear description of the 'project' parameter. The tool description adds 'optionally filtered by project name' but does not add significant new 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 action ('list') and resource ('generated screens') with an optional filter. It distinguishes from siblings like generate_screen and get_screen.

  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 implies when to use (listing all screens) and mentions optional filtering, but does not explicitly state when not to use or compare to alternatives like iterate_screen.

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