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

Annotations already declare readOnly, idempotent, and non-destructive. The description goes well beyond that: it discloses the exact return structure (answer, evidence, confidence, source, fetched_at, refusal_reason), the refusal modes, the mechanism of extracting only from tool results, and the extra LLM call cost. This is rich behavioral context that annotations do not cover.

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 dense but every sentence serves a purpose: purpose, mechanism, return format, refusal conditions, usage guidance, and cost trade-off. It is front-loaded with the key differentiator (hallucination-resistant) and organized logically. No wasted words.

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?

For a complex tool with special grounding behavior, the description covers all necessary aspects: what it does, when to use, what it returns, failure modes, and cost implications. Even without an output schema, the return shape is explicitly described. Nothing an agent needs to call it correctly is missing.

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 description coverage is 100% – each parameter (all aliases of 'question') is described. The description adds no parameter-specific guidance beyond what the schema provides, and the schema already explains natural-language input and aliases. A baseline 3 is appropriate since the schema handles it.

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 it is a 'hallucination-resistant answer mode for high-stakes reads' that routes like ask_pipeworx but extracts the answer strictly from tool results. It names the sibling ask_pipeworx and distinguishes the grounded variant's purpose, so an agent knows exactly what this tool does and how it differs.

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 states when to use: 'whenever an answer will be quoted, cited, or acted on' and 'the agent must not invent facts.' It also gives the alternative: 'prefer ask_pipeworx for casual lookups,' and notes the cost trade-off. This is clear, actionable guidance for selecting between siblings.

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