Server Quality Checklist

Tool Scores

• describe_tableA
  3.6/5.0
  Behavior3/5

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

  Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds that the tool returns schema and retention metadata, but does not disclose additional behavioral details like pagination or required permissions beyond what annotations imply.

  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, front-loaded sentence with no unnecessary words, effectively conveying the core function.

  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 getter with two required parameters, good annotations, and no output schema, the description sufficiently explains the return value at a high level. However, it lacks detailed usage context such as when to prefer this over search_tables, so completeness is slightly below perfect.

  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 describes both parameters fully (100% coverage) with clear descriptions, including case-sensitivity for tableName. The description adds no additional parameter-specific meaning, so the baseline of 3 applies.

  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 uses the verb 'Get' and specifies the exact resource: canonical schema and retention metadata for a Log Analytics table. This clearly distinguishes it from sibling tools like search_tables or query_workspace.

  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 is provided about when to use this tool versus alternatives such as search_tables or list_workspaces. The description only states what it does, without any exclusions or alternative recommendations.

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

• search_tablesA
  3.8/5.0
  Behavior3/5

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

  Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds that it uses ARM metadata, clarifying it operates on metadata rather than querying data. However, it does not disclose additional behaviors such as pagination, return format, or search semantics beyond what the schema provides.

  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, dense sentence that immediately conveys the tool's purpose. No redundant or filler content exists.

  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/search tool with strong annotations and full schema coverage, the description is nearly complete. It lacks explicit details about the return value, but with no output schema and a straightforward use case, the provided information is sufficient.

  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 description coverage is 100%, with both workspaceResourceId and search having descriptive text. The description itself does not add parameter-level detail, but that is acceptable given the complete schema 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 lists or searches tables in a Log Analytics workspace, specifying the resource type (tables) and context (Log Analytics workspace). This distinguishes it from siblings like query_workspace (querying data) and describe_table (specific table details).

  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?

  Usage is implied: if you need to list or search tables, use this tool. However, there is no explicit guidance on when to use this versus alternatives like describe_table for table details or list_workspaces for workspace discovery. No exclusions or alternative suggestions are provided.

  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?

  Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds the constraint that only workspaces 'accessible' to the user are returned, which is useful context, but it does not describe pagination or return format.

  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 clear, front-loaded sentence with no wasted words. It states the action, resource, and scope efficiently.

  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 operation with one parameter and strong annotations, the description is mostly adequate. It lacks explicit details about return values or pagination, but the tool's simplicity and the openWorldHint annotation partially compensate. Slightly more detail 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?

  The schema has 100% coverage for the single parameter subscriptionId, describing it as 'Azure subscription ID'. The description adds no further parameter detail, but the schema already handles it, so baseline 3 is appropriate.

  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 uses a specific verb 'List' with a clear resource 'Azure Log Analytics workspaces' and scope 'in a subscription'. It clearly distinguishes from sibling tools like search_tables and query_workspace, which are for different operations.

  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 this tool: to enumerate accessible Log Analytics workspaces for a given subscription. It does not explicitly state alternatives or exclusions, but the context is clear and distinct from the sibling tools.

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

• query_azure_resourcesA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds contextual scope beyond the annotations by specifying the data domains (inventory, config, tags, policy, health) and the underlying mechanism (Azure Resource Graph). It does not add details like rate limits or pagination behavior, but the schema covers pagination via skipToken and maxResults, so the bar is appropriately lowered.

  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 exactly two sentences: the first front-loads the primary use cases and scope, and the second delivers a crisp exclusion with a sibling alternative. No filler or redundant content, every sentence earns its place.

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

  Completeness5/5

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

  Given the rich annotations, fully self-describing schema, and a description that clearly delineates scope and alternatives, the tool is fully contextualized. The tool is a read-only query tool, and the description covers what it queries and what it avoids. The lack of an output schema is acceptable per rules, as the return value is not a required explanatory element.

  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 includes comprehensive descriptions for all four parameters, achieving 100% coverage. The description does not add additional parameter-specific meaning beyond what the schema provides. Baseline 3 is appropriate when the schema does the 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 a specific verb and resource: 'Use for Azure resource inventory, configuration, tags, policy, health, and cross-subscription discovery through Azure Resource Graph.' It distinguishes from the sibling query_workspace by explicitly naming what it does NOT do and directing to the alternative.

  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?

  Explicit when-to-use and when-not-to-use guidance is provided: 'Do not use for telemetry, logs, events, or time-series analysis; use query_workspace for those.' This directly references the sibling tool as an alternative, making the usage boundaries unambiguous.

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

• query_workspaceA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful context: 'bounded' (requiring a result-limiting operator), 'against one workspace' (scope constraint), and the data types covered. This goes beyond what annotations provide, though it doesn't discuss return format or rate limits.

  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 primary use case and followed by an exclusion with an alternative. 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.

  Completeness5/5

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

  With rich annotations (readOnly, idempotent, non-destructive) and a clear description covering purpose, scope, and exclusions, the tool is well-specified for an agent. No output schema exists, but for a query tool the description sufficiently sets expectations without needing to explain return values.

  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 description coverage is 100%, with each parameter having a clear description. The tool description reinforces the query parameter as 'bounded, read-only KQL' and the workspaceId as 'one workspace', but does not add substantially new meaning beyond the schema. Baseline 3 applies.

  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 runs bounded, read-only KQL queries against a single Log Analytics workspace, specifically for telemetry, logs, events, metrics, and time-series data. This specific verb+resource+scope distinguishes it from sibling tools like query_azure_resources.

  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 states when to use (telemetry, logs, etc.) and when not to use (Azure resource inventory/config), with a direct pointer to the alternative tool query_azure_resources. This provides clear decision-making guidance.

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