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

Annotations already cover read-only/idempotent safety, but the description adds substantial behavioral detail: the exact success return shape {answer, evidence, confidence, source, fetched_at, refusal_reason:null}, the enumerated refusal reasons, and the 'using ONLY what the tool result contains' guarantee. This goes far beyond what annotations declare.

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 logically sequenced: purpose, mechanism, return contract, usage guidance, and cost trade-off. It is longer than strictly minimal, but every clause contributes useful signal and the main purpose is front-loaded.

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?

There is no output schema, so the description properly documents both the success return object and the refusal failure modes. It also explains the routing behavior, the hallucination-resistance guarantee, and when to prefer the cheaper alternative. For a read-only tool with one required parameter, nothing essential 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 coverage is 100% — the schema fully describes the `question` parameter and its aliases. The description adds no parameter-level formatting or constraints beyond the schema, so the baseline 3 applies rather than additional credit.

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 opens with a specific verb and resource: 'Hallucination-resistant answer mode for high-stakes reads', and then explains exactly how it differs from ask_pipeworx by extracting answers only from tool results. It clearly identifies this as the grounded/evidence-based variant, making it distinguishable from siblings without opening schemas.

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?

Explicit when-to-use guidance is given: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts', followed by concrete domains (financial verdicts, legal claims, medical lookups, public statements). It also names the alternative ('prefer ask_pipeworx for casual lookups') and the cost trade-off ('Costs one extra LLM call').

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