process_search_query

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 technologies (GroundX and OpenAI) but doesn't explain what 'process' entails—whether it's a read-only search, requires API keys, has rate limits, or affects data. The description lacks critical behavioral context for a tool that likely involves external API calls.

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 well-structured and concise, with zero wasted words. It starts with the core purpose, then lists parameters and returns in a clear, bullet-like format. Every sentence adds value, making it easy for an agent to parse quickly.

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 the complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and parameters but lacks behavioral details, usage context, and output explanation. It's adequate as a baseline but has clear gaps, especially for a tool that likely involves external processing.

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?

The description adds meaningful semantics beyond the input schema. It explains that 'query' is a 'search query string' and 'config' is an 'Optional SearchConfig object for customization,' which clarifies their roles. Since schema description coverage is 0%, this compensates well, though it doesn't detail the SearchConfig properties like 'openai_api_key' or 'bucket_id'.

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 purpose: 'Process a search query using GroundX and OpenAI.' It specifies the verb ('process') and resource ('search query'), and mentions the technologies involved. However, it doesn't explicitly differentiate from sibling tools like 'search_doc_for_rag_context' or 'ingest_documents', which prevents a perfect score.

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 no guidance on when to use this tool versus alternatives. There's no mention of sibling tools, specific use cases, or prerequisites. The agent must infer usage from the tool name and description alone, which is insufficient for optimal tool selection.

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