Server Quality Checklist

Tool Scores

• get_issueA
  3.9/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden. It discloses that the tool returns the complete text with section headings preserved, which is useful. However, it does not mention what happens when both parameters are provided, when neither is provided, or the 'nearest issue' behavior that is only in the parameter description. The description adds some behavioral context but not a comprehensive picture.

  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 concise sentences, front-loaded with the action and resource. Every sentence contributes: the first states the purpose and parameters, the second describes the return value. No unnecessary words or repetition.

  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 simple with two optional parameters, and the output schema is absent, so the description helps by indicating the return format. However, it lacks important contextual details such as the requirement to provide at least one identifier and the conflict resolution if both are given. The description is adequate but has gaps.

  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 has 100% coverage for both parameters, so the baseline is 3. The description merely reiterates that the tool works by 'issue number or publication date', which adds no new meaning beyond the schema. It does not clarify that at least one parameter is needed, since none are required.

  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: 'Retrieve the full content of a specific Microsoft AI Roundup issue.' It specifies the resource ('Microsoft AI Roundup issue') and the action ('retrieve') along with the two lookup methods (issue number or publication date). It also distinguishes itself from sibling tools like search or list by focusing on full content of a single issue.

  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 for use: when you want a specific issue identified by number or date. It implies that you should have one of these identifiers. It does not mention alternatives like list_issues for finding issue numbers, but the context is clear enough without exclusions.

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

• list_issuesA
  4.2/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden for behavioral disclosure. It states the tool is for browsing (implying read-only) and returns a list with specified fields, but does not disclose pagination behavior, potential size limits, or ordering. It adds some context but not rich detail.

  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, and no unnecessary fluff. Every word 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?

  The description covers the return fields and positions itself against sibling tools. Since there is no output schema, it explains the return value (list with title, date, URL). However, it omits mention of pagination via offset/limit, which the schema supports, so it falls just short of being fully complete.

  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 100%, and each parameter already has a description. The description reinforces that year/month are for filtering, but adds no new information beyond the schema. Baseline 3 is appropriate since 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 the tool browses the Microsoft AI Roundup archive and returns a list of issues with title, date, and URL. It differentiates from siblings by explicitly mentioning use before get_issue or search_microsoft_ai_roundup, establishing its role as a discovery tool.

  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?

  Provides explicit guidance: 'Use this to discover what issues exist before using get_issue or search_microsoft_ai_roundup.' This clearly indicates when to use this tool versus the alternatives, and the mention of optional filtering adds context for parameter usage.

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

• find_tool_mentionsA
  4.3/5.0
  Behavior4/5

  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 discloses the return fields (tool names, descriptions, GitHub URLs, issue context) and the optional filter. It does not mention sorting or pagination, but for a read-oriented find tool, the description offers adequate behavioral detail.

  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 main action and scope. No redundant wording or unnecessary details.

  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?

  The tool is simple with two optional parameters, no output schema, and no annotations. The description covers what it does, what it returns, and how to filter. It is complete enough for an agent to determine if this tool fits the task.

  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% for both parameters (limit and query). The description only restates the query's search purpose ('find tools related to a specific technology or capability') without adding new meaning beyond the schema.

  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 with a specific verb 'Find' and explicit resources: community tools, GitHub projects, and Microsoft AI products/features mentioned in the Microsoft AI Roundup. This distinguishes it from siblings like get_issue and list_issues, which focus on issues.

  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 searches tool mentions within the Microsoft AI Roundup, with an optional keyword filter. However, it does not explicitly mention when to use an alternative like search_microsoft_ai_roundup, lacking direct exclusionary guidance.

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

• search_microsoft_ai_roundupA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden and does well. It discloses the hybrid semantic+keyword search, the OPENAI_API_KEY dependency for semantic mode, coverage from May 2026, and the return format. Minor gaps remain (e.g., no mention of result sorting or error handling), but it's transparent for a read-only search 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?

  The description is three sentences, front-loaded with the main action, and every sentence provides useful detail. No filler or repetition of schema fields.

  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?

  The tool is moderately complex with 3 parameters and no output schema. The description adequately explains the return format, coverage, and dependencies. It doesn't mention pagination or relevance ordering, but the limit parameter and search nature make this acceptable. Overall, it's complete enough 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.

  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 value by explaining that query can be natural language, and that semantic mode requires an API key, which is not in the schema. This enhances understanding of mode's behavior beyond the enum description.

  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: searching the full Microsoft AI Roundup archive with natural language or keywords. It distinguishes itself from siblings like get_issue and list_issues by focusing on cross-issue content search, and specifies the output (sourced excerpts with issue number, date, URL).

  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 for when to use this tool: when searching across the archive. It doesn't explicitly name alternatives or exclusions, but the search-focused wording implies differentiation from other sibling tools. A brief mention of when not to use it would elevate this further.

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