Server Quality Checklist

Tool Scores

• generate_setA
  3.9/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It discloses the output naming convention and return structure ('per-item results plus any warnings'), which is useful. However, it does not explicitly state that files are written to disk, nor does it describe failure/partial-failure behavior, leaving gaps for a write operation.

  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 sentences, front-loaded with the core action. Each sentence earns its place: the first states purpose, the second provides naming and return behavior. 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?

  The tool is complex (9 params, nested objects, no output schema), and the description gives the essential purpose but not enough to fully understand the return format or edge cases. It mentions per-item results and warnings, but not specifics. Schema covers parameters well, so the description need not repeat that; however, the lack of output schema makes the return description feel thin.

  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 89%, so the baseline is 3. The description adds the naming convention (Item N becomes {lang}_{NN}.png), but this is already captured in the outputDir schema description. It does not add further meaning to parameters beyond what the schema provides.

  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 verb and resource: 'Batch-renders an ordered screenshot set for one preset and language.' It distinguishes from siblings by emphasizing 'set' and 'batch,' which contrasts with single-render tools like compose_screenshot.

  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: it is used for batch rendering of multiple screenshots at once, scoped to one preset and language. However, it does not explicitly mention alternatives or when not to use it, so it misses the highest bar.

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

• compose_screenshotA
  4/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden of disclosing behavior. It mentions auto-uppercasing and exact store dimensions, which is helpful, but it does not disclose file writing/overwriting behavior, error conditions, or dependence on preset availability. More detail would improve 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 with no fluff. It front-loads the core purpose and lists the key composing elements efficiently. Every sentence earns its place.

  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 10-parameter tool with a nested frame object and enums, the description provides a coherent overview of the composition process and output characteristics, while the schema details the parameters. It is complete enough for a straightforward usage scenario, though it omits some behavioral edge cases.

  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?

  Schema coverage is 100%, so baseline is 3. The description adds semantic context by explaining that the headline is composed of verb + descriptor, auto-uppercased for the language, and that output dimensions depend on the chosen preset. This helps connect the parameters meaningfully.

  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 function: 'Renders one store-ready marketing screenshot' with specific components (brand background, headline, device frame). It distinguishes from sibling tools like generate_set by emphasizing singular output ('one screenshot').

  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 for a single screenshot but provides no explicit guidance on when to choose this tool over alternatives like generate_set. No exclusions or alternative references are given, so usage context is implied but not clearly defined.

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

• create_showcaseA
  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. It adds the behavioral note about relaying the `note` field once, but does not disclose write semantics, error handling, or prerequisites (e.g., that inputs must be generated screenshots). Some transparency is provided, but gaps remain.

  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 core purpose, and every sentence adds value. No redundant or wasteful text.

  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 covers the tool's purpose, typical use, and a key behavioral instruction (note field). It lacks detail on return value structure beyond the note, but schema covers parameters well. Fairly complete for its complexity.

  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 description adds meaning beyond the schema by specifying inputs are 'generated screenshots' and explaining the `note` field in the result. Schema descriptions are already detailed, so the description adds contextual use-case info, earning above baseline.

  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 'composes a horizontal preview strip from generated screenshots' with specific use cases (READMEs, decks, social posts), which is a specific verb-resource combination. This distinguishes it from siblings like compose_screenshot (single screenshot) and generate_set (set generation).

  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 provides context ('for READMEs, decks, and social posts') and mentions a note field to relay, implying post-compose use. However, it does not explicitly state when to use this tool versus alternatives (e.g., compose_screenshot) or when not to use it.

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

• validate_screenshotA
  4.1/5.0
  Behavior3/5

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

  Discloses key checks (dimensions, format, alpha channel) and behavior without a preset ID, but does not mention side effects, permissions, or error responses. With no annotations, more depth on return values or edge cases would be beneficial.

  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, front-loaded sentences with no filler. Every phrase contributes meaningful information.

  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?

  Provides behavioral details but lacks output format or success/failure indicators. Given no output schema, the description should more clearly state what the tool returns on validation pass or failure.

  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?

  Schema covers both parameters fully. Description adds functional context for 'preset' (reports matching preset when omitted), enhancing understanding beyond the schema alone.

  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?

  Describes a specific verb ('checks') and resource ('image against store requirements'), and distinguishes from siblings by detailing validation criteria (dimensions, format, alpha channel) and behavior without a preset ID.

  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?

  Clearly indicates when to use the tool (for validation against store requirements), but lacks explicit exclusionary guidance or comparison to sibling tools like 'list_presets' or 'compose_screenshot'.

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

• list_presetsA
  4.6/5.0
  Behavior4/5

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

  The description indicates a read-only operation by stating 'Returns...', which implies no side effects. No annotations exist, but the description adequately covers the behavior for this simple list tool.

  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 front-load the purpose and usage guidance, with no wasted words.

  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, the description explains what is returned (store, exact dimensions, layout metrics) and provides usage context. Minor gap: could elaborate on 'platform presets', but sufficient for typical use.

  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?

  No parameters in the schema, so the description does not need to add parameter details. The baseline score of 4 is appropriate as the description adds no redundancy.

  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 returns 'all supported platform presets' with specific details (store, dimensions, metrics), distinguishing it from sibling tools like compose_screenshot or generate_set which are about creation, not listing.

  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 advises 'Call this first to decide which presets to generate', providing clear guidance on when to use this tool relative to other operations.

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