Server Quality Checklist

Tool Scores

• compare_imagesC
  2.6/5.0
  Behavior2/5

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

  No annotations are provided, so the description must disclose behavioral traits. It only states the high-level purpose without detailing what the output looks like (e.g., diff image, boolean, text description), whether the operation is safe, or any side effects. The cryptic 'Absorbed pattern from image_mcp' adds no clarity.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is short (two sentences), but the second sentence is vague and unhelpful. While concise, it lacks structure and misses important information like parameter details or output behavior.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness1/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given no output schema, no annotations, and incomplete parameter documentation, the description fails to provide a complete understanding of the tool. The agent cannot determine what the tool returns, how the 'task' parameter affects behavior, or any prerequisites.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, and the description does not elaborate any parameter semantics. 'source_a' and 'source_b' are self-explanatory, but 'task' is left undefined. The description adds no value beyond the parameter names.

  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 compares images, specifically before/after screenshots or UI states, using a specific verb and resource. It distinguishes from sibling tools like describe_image, extract_text, etc., which serve different purposes.

  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?

  No explicit guidance on when to use this tool versus alternatives (e.g., describe_image for single image analysis). The description implies usage for comparison but does not provide context, exclusions, or when-not-to-use scenarios.

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

• describe_imageC
  2.8/5.0
  Behavior2/5

  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 mentions 'multi-model fallback' and 'sidecar vision model', but does not disclose key behaviors like error handling, image format support, or output structure. The description is also incomplete, ending abruptly, which reduces transparency.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is front-loaded with the most critical information (requirement for text-only models), but it is cut off and includes a markdown heading that breaks flow. It could be more concise and structured without the abrupt ending.

  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?

  With no output schema and no annotations, the description should provide more context about return values, error cases, and behavior details. The current description is incomplete and leaves the agent with significant unknowns regarding what the tool produces and how it behaves.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 50%, yet the description adds no information about parameters. It does not explain 'source', 'context', 'question', or 'mode' beyond what the schema already provides. For undocumented parameters like 'context', no guidance is given.

  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 tool converts images to detailed text and indicates it's required when the main model cannot see images (e.g., DeepSeek text). This provides a clear verb+resource purpose, but it does not explicitly differentiate from sibling tools like 'compare_images' or 'extract_text'.

  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 gives specific context for when to use the tool (when main model cannot see images, user attaches image/screenshot) but does not provide guidance on when not to use it or how to choose among siblings. The usage context is implied but lacks explicit alternatives.

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

• vision_statusA
  3.5/5.0
  Behavior2/5

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

  With no annotations provided, the description must fully disclose behavior. It states what is shown but does not mention any behavioral traits like authentication requirements, performance characteristics, or side effects. The read-only nature is implied but not explicit.

  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?

  A single, well-structured sentence that front-loads the key information. Every word is relevant and there is no redundancy.

  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?

  Given the tool has no parameters and no output schema, the description provides a fair overview of what is shown. However, it could be more complete by detailing the output format or fields, especially since output schema is missing.

  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 tool has zero parameters, so the baseline is 4. The description does not need to add parameter information; schema coverage is 100%.

  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 verb 'Show' clearly indicates a read operation, and the description specifies the exact resources: vision API config, model fallback chain, cache setting. This distinguishes it from sibling tools like compare_images or extract_text that perform different tasks.

  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?

  No explicit guidance on when to use this tool vs alternatives. The description implies it's for checking configuration, but does not mention when not to use it or provide context for choosing between sibling tools.

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

• extract_textA
  3.7/5.0
  Behavior2/5

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

  No annotations provided, and description does not disclose any behavioral traits beyond OCR. No mention of limitations, safety, or side effects, leaving the agent underinformed.

  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?

  Extremely concise with two sentences that front-load the core purpose. No unnecessary 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?

  Given no output schema and minimal annotations, the description is too brief. It does not explain return values, error cases, or how to use the optional context and question parameters effectively.

  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 67% with two of three parameters described. Description adds no extra meaning beyond the schema; context parameter remains undocumented.

  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 it is an OCR tool for screenshots/logs to extract verbatim text. Distinguishes from sibling tools like compare_images and describe_image.

  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?

  Explicitly says 'Use when you need verbatim text from an image,' providing clear usage context. Lacks explicit when-not-to-use or alternative mention, but still functional.

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

• vision_rulesA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description transparently states it returns markdown rules. It is a simple, non-destructive tool, but could mention idempotency or side effects.

  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?

  One clear sentence, front-loaded with purpose, no unnecessary 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 zero parameters and no output schema, the description adequately explains what the tool does and its purpose, though it could specify that it's for initial setup.

  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 exist, so baseline 4 applies. Description adds value by explaining the output's purpose without needing parameter details.

  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 returns markdown rules for CLAUDE.md to enable auto-calling of vision tools, distinguishing it from sibling tools that perform vision actions.

  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?

  Usage is implied: when configuring the agent to auto-call vision tools. No explicit exclusions or alternatives, but sibling tools are clearly different tasks.

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