semantic_search

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

Annotations provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that results are ranked by relevance and include citable source fields. No contradiction. Description adds value beyond annotations by explaining return structure.

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?

Description is somewhat long but well-organized: purpose first, then examples, then parameter details, then siblings. Every sentence adds value. Could trim some redundancy but effective overall.

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?

Given no output schema, description explains return format with cite fields. It covers usage, parameters, examples, and relationships to siblings. Contextually complete for a retrieval tool.

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 100% gives baseline 3. Description adds meaning: explains 'q' as natural-language query, 'corpus' as optional CSV with defaults, 'k' range 1-15 default 8. Includes examples demonstrating parameter use. Adds value beyond schema.

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?

Description clearly states the tool is for conceptual/fuzzy questions using semantic meaning-based retrieval. It provides specific verb 'semantic_search' and distinguishes from exact-filter siblings like get_news, list_transactions, search_facilities. Examples illustrate usage.

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?

Explicitly says when to use: 'Use for CONCEPTUAL / fuzzy questions where keyword filters fall short.' It contrasts with exact-filter tools and directs to get_market_context for full briefing. No confusion about alternatives.

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