rag_query

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

No annotations present; description mentions LAZY-RAG cache and speedup but lacks details on side effects (e.g., cache writing), permissions, rate limits, or error behavior. Missing critical behavioral context for a query 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?

Two sentences: first states purpose, second adds a key technical detail. No fluff, front-loaded, efficiently communicates core function and a differentiator.

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?

No output schema exists, but description does not explain what the tool returns (e.g., answer text, references). For a simple query tool with one parameter, the lack of return description is a moderate gap.

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?

Single parameter 'question' with schema description 'Question to ask'. Schema coverage is 100%, so baseline 3 is appropriate. Description adds no extra semantic value beyond the 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?

Clearly states the verb 'ask' and resource 'question with RAG-enhanced context from xAI Collections'. Differentiates from siblings like rag_cache_clear and rag_cache_stats by specifying the core querying functionality. No ambiguity.

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?

Implies usage for question-answering with RAG, but no explicit guidance on when to use vs. alternatives (e.g., direct search or other faf tools). Does not provide when-not-to-use or prerequisites.

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