Server Quality Checklist

Tool Scores

• discover_stable_locatorsC
  2.1/5.0
  Behavior2/5

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

  No annotations accompany the tool, so the description must carry the full burden of behavioral disclosure. It mentions 'accessibility-first priority' but fails to state whether the tool modifies state, requires authentication, or has any side effects. Key behaviors like app lifecycle or read-only intent are absent.

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

  Conciseness2/5

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

  The description is a single sentence, which is concise but severely under-informative for a tool with 5 parameters and no annotations. It lacks structure and fails to front-load critical information.

  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 the tool's complexity (5 parameters, no annotations, no output schema), the description is woefully incomplete. It omits return values, parameter details, and context about when to invoke it, leaving the agent with insufficient guidance.

  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%, meaning parameters have no descriptions in the schema. The tool description does not explain any of the 5 parameters (applicationUrl, pageName, headless, scenarioSteps, allowProduction), leaving the agent to guess their meaning and usage.

  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's purpose: using Playwright to discover stable locators with accessibility-first priority. It is specific and distinct from sibling tools like generate_playwright_test or create_bug. However, 'stable locators' could be more precisely defined.

  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 on when to use this tool versus alternatives, nor any prerequisites or exclusions. Given the presence of related sibling tools (e.g., run_playwright_test), explicit differentiation is missing.

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

• generate_playwright_testC
  2.5/5.0
  Behavior2/5

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

  No annotations are provided, and the description does not disclose any behavioral traits such as side effects (e.g., file creation), authentication requirements, or if it is read-only. This is inadequate for a tool that likely generates files.

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

  Conciseness2/5

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

  The description is a single sentence, which is too brief given the tool's complexity. While concise, it sacrifices necessary information and clarity.

  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?

  The description is severely incomplete. It does not explain what the tool returns (no output schema), how parameters relate, or any contextual cues for using it effectively.

  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?

  The schema has 0% description coverage, and the description does not explain any parameters. With 6 complex parameters including nested objects, the description should provide meaning but does not.

  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 generates a Playwright TypeScript framework with Page Object Model, data files, and utilities. This verb+resource combination is specific and distinguishes it from sibling tools like create_bug or generate_test_cases.

  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 alternatives or when not to use it. It does not mention any preconditions or context for its use.

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

• generate_test_scenariosC
  2.6/5.0
  Behavior2/5

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

  The description lacks behavioral details such as side effects, read-only status, or output format. No annotations are provided to compensate.

  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?

  Single sentence is concise and front-loads the main action, but could include more structure without becoming verbose.

  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 5 parameters and no output schema, the description is insufficient for an agent to use the tool correctly without additional context.

  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 coverage is 0% and the description adds no meaning to the 5 parameters beyond the schema's names and types.

  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 generates test scenarios from user stories and acceptance criteria, but does not differentiate from the sibling 'generate_test_cases' tool.

  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 guidance on when to use this tool versus alternatives such as generate_test_cases or create_bug.

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

• run_playwright_testC
  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 carries full burden. It mentions capturing results, screenshots, traces, and videos but does not disclose how these are returned, side effects, duration, or whether it runs headlessly (despite 'headed' parameter defaulting to false).

  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 a single concise sentence, but it lacks structure and important details. While short, it sacrifices completeness for brevity.

  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 the tool has 4 parameters, no output schema, no annotations, and sibling tools, the description is completely inadequate. It does not explain return values, error handling, artifact storage, or how it interacts with other tools.

  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 adds no information about any of the 4 parameters (testFilePath, headed, testCases, projectName). The description fails to explain what each parameter does or how to use them.

  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?

  Description clearly states the verb 'Execute' and the resource 'Playwright tests', and mentions capturing results and artifacts, which distinguishes it from sibling 'generate_playwright_test' that creates tests.

  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 guidance on when to use this tool versus alternatives like 'generate_playwright_test'. The description does not mention prerequisites, context, 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.

• generate_test_casesC
  2.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description bears full burden. It mentions conversion but lacks detail on output format, side effects, or prerequisites (e.g., whether generatedScenarios must come from a prior 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?

  One sentence covering core function with no redundancy. However, could be slightly expanded to include parameter hints without losing conciseness.

  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?

  Given four parameters, a complex input schema, and no output schema or annotations, the description is insufficient. It does not describe the structure of generatedScenarios or the output format, making it hard for an agent to invoke correctly.

  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?

  With 0% schema description coverage, the description adds little beyond the schema. It mentions 'generated scenarios' but does not clarify userStory, acceptanceCriteria, or featureName meanings or relationships, leaving the agent to infer from 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 converts generated scenarios into test cases, differentiating it from siblings like generate_test_scenarios (which generates scenarios) and generate_playwright_test (which produces automation code).

  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, such as generate_playwright_test for automation code or create_bug for reporting issues. The description implies it follows generate_test_scenarios but offers no exclusions.

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

• create_bugA
  3.5/5.0
  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 dry-run vs live behavior and multi-provider support, but misses critical details like authentication requirements, rate limits, or confirmation steps (e.g., the 'confirmed' parameter). A score of 3 reflects partial 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 a single, short sentence that fully captures the tool's primary purpose and key features. It is front-loaded with essential information and contains no filler.

  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?

  Given 14 parameters, nested objects, no output schema, and no annotations, the description is insufficient. It does not explain return values, error handling, dry-run outcomes, or the interaction between parameters like 'autoCreateBug' and 'confirmed'. The complexity demands a more complete description.

  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 only 7%. The description adds minimal parameter meaning beyond the schema—only referencing 'from a failed test' which corresponds to required parameters. Many optional parameters (e.g., priority, severity, provider) remain unexplained. The description does not compensate for the low coverage.

  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 creates a bug ticket from a failed test, specifies three supported platforms (GitHub, Jira, Azure DevOps), and mentions dry-run/live modes. This distinguishes it from sibling tools like generate_test_cases.

  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 after a failed test but does not provide explicit guidance on when to choose this tool over alternatives or when not to use it. It lists supported providers but no criteria for selecting among them.

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