search_microsoft_ai_roundup

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.

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.

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.

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.

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.

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.