Server Quality Checklist

Tool Scores

• get_workspaceC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves workspace details but doesn't disclose critical behavioral traits such as required permissions, rate limits, error handling, or whether it's a read-only operation (though implied by 'Get'). This leaves significant gaps for an AI agent to understand how to invoke it safely and effectively.

  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?

  The description is well-structured and appropriately sized. It front-loads the purpose in the first sentence, followed by clear sections for Args and Returns. Each sentence earns its place by adding value, with no redundant or verbose language.

  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's moderate complexity (2 parameters, no annotations, but with an output schema), the description is partially complete. It covers the purpose and parameters adequately, and the output schema handles return values, so the description doesn't need to explain those. However, it lacks behavioral context (e.g., permissions, errors) that would be helpful for safe invocation.

  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 description adds meaningful semantics for both parameters: 'workspace_id' is explained as 'The ID of the workspace to retrieve,' and 'region' as 'AWS region where the workspace is located (default: us-east-1).' This compensates for the 0% schema description coverage by providing clear, actionable context beyond the schema's basic titles 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's purpose: 'Get detailed information about a specific Amazon Managed Prometheus workspace.' It uses a specific verb ('Get') and resource ('workspace'), but doesn't explicitly distinguish it from sibling tools like 'get_workspace_status' or 'list_workspaces', which likely provide different types of workspace information.

  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. It doesn't mention sibling tools like 'get_workspace_status' (which might provide status vs. detailed info) or 'list_workspaces' (which might list multiple vs. get one), nor does it specify prerequisites or exclusions for usage.

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

• get_workspace_statusB
  3.1/5.0
  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 the return format ('JSON string') but lacks critical behavioral details like authentication requirements, rate limits, error handling, or whether it's a read-only operation. The description doesn't contradict annotations, but it's insufficient for a tool with no annotation coverage.

  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?

  The description is appropriately sized and front-loaded, starting with the core purpose. The 'Args' and 'Returns' sections are structured clearly, but the 'Returns' section could be more concise (e.g., 'JSON with workspace status'). Overall, it's efficient with minimal waste.

  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 annotations, 0% schema coverage, and an output schema present, the description is moderately complete. It covers purpose and parameters adequately but lacks behavioral context (e.g., auth, errors). The output schema reduces the need to explain return values, but more guidance on usage and transparency would improve completeness for this read operation.

  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 description coverage is 0%, so the description must compensate. It adds meaningful semantics for both parameters: 'workspace_id' is explained as 'The ID of the workspace', and 'region' as 'AWS region where the workspace is located (default: us-east-1)'. This clarifies beyond the schema's basic titles, though it doesn't detail format constraints (e.g., region codes).

  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 with a specific verb ('Get') and resource ('current status of an Amazon Managed Prometheus workspace'). It distinguishes from siblings like 'get_workspace' (likely returns different workspace details) and 'list_workspaces' (returns multiple workspaces). However, it doesn't explicitly differentiate from 'query_metrics', which might overlap in context.

  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 like 'get_workspace' or 'list_workspaces'. It lacks context such as prerequisites (e.g., needing workspace ID) or exclusions (e.g., not for querying metrics). Usage is implied through parameter descriptions but not explicitly stated.

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

• query_metricsA
  3.7/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool executes queries and returns JSON results, but lacks details on error handling, rate limits, authentication requirements, or whether it's read-only or mutating. The description doesn't contradict annotations (none exist), but provides only basic operational context.

  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?

  The description is well-structured with a clear purpose statement followed by organized parameter and return sections. Every sentence adds value, though the parameter explanations could be slightly more concise. It's appropriately sized for a 6-parameter tool with technical details.

  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 (6 parameters, technical query execution) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the core purpose and parameters well, though it lacks usage context and some behavioral details. The output schema reduces the need to describe return format in the description.

  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 description coverage is 0%, so the description must compensate. It provides clear explanations for all 6 parameters, including format details (RFC3339 for times, examples like '15s' for step), defaults (region: us-east-1), and context (range queries for start/end/step). This adds substantial value beyond the bare schema, though it doesn't fully explain parameter interactions or constraints.

  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: 'Execute a PromQL query against an Amazon Managed Prometheus workspace.' It specifies the exact action (execute), technology (PromQL), and target resource (Amazon Managed Prometheus workspace), which distinguishes it from sibling tools that focus on workspace management rather than query execution.

  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. While it's clear this is for querying metrics, there's no mention of when to use it over other query methods or tools, nor any prerequisites or constraints beyond the parameters listed. This leaves the agent without context for tool selection.

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

• list_workspacesA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the basic operation (listing workspaces) and return format (JSON string), but doesn't mention important behavioral aspects like pagination, rate limits, authentication requirements, error handling, or whether the operation is read-only (though implied by 'list'). Some useful context 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 perfectly structured and concise with zero waste. It opens with the core purpose, then provides clear Args and Returns sections. Every sentence earns its place by delivering essential information without redundancy or unnecessary elaboration.

  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 low complexity (single parameter, no nested objects) and the presence of an output schema, the description is reasonably complete. It covers the basic operation, parameter semantics, and return format. However, for a tool with no annotations, it could benefit from more behavioral context about authentication, limits, or error scenarios.

  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?

  With 0% schema description coverage and only one parameter, the description adds significant value by explaining the region parameter's purpose ('AWS region to query') and providing the default value ('us-east-1'). This compensates well for the lack of schema descriptions, though it doesn't elaborate on region format constraints or valid values.

  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 ('List all Amazon Managed Prometheus workspaces') and resource ('workspaces in the specified region'), distinguishing it from siblings like get_workspace (singular retrieval) and query_metrics (different operation). It uses precise language that leaves no ambiguity about what the tool does.

  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 by specifying the region parameter, but doesn't explicitly state when to use this tool versus alternatives like get_workspace or get_workspace_status. No guidance is provided about prerequisites, error conditions, or specific scenarios where this tool is preferred over others.

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