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

Annotations already cover readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavior beyond that: the exact success contract {answer, evidence (verbatim quote), confidence, source, fetched_at} and the explicit refusal contract with the full reason enum (not_in_source, no_tool_match, tool_error, data_truncated, llm_error). It also discloses the extra-cost behavior. No contradiction with annotations found.

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?

Dense but efficient: front-loaded identity, then mechanism, return contract, usage, and cost trade-off in logical order. Slightly redundant in places ('Same routing as ask_pipeworx' elaborated by the parenthetical about picking tools), and the refusal-reason enum could arguably live in an output schema, but no sentence is wasted.

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?

With no output schema, the description carries the full burden of documenting return values — and it does so completely, covering both success and refusal shapes plus all refusal reasons. Combined with full schema parameter coverage and a complete safety annotation set, nothing an agent needs to call this tool 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% — the schema fully documents the question parameter and its five aliases (query, q, prompt, text, input). The description adds only incidental context ('fills arguments,' high-stakes domains) rather than parameter-level semantics, so the baseline 3 applies.

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?

Opens with a specific identity — 'Hallucination-resistant answer mode for high-stakes reads' — and describes the full mechanism: routes to the right tool, fills arguments, fetches data, then extracts the answer using ONLY what the tool result contains. It explicitly differentiates from the sibling ask_pipeworx ('Same routing as ask_pipeworx... prefer ask_pipeworx for casual lookups'), so an agent can tell them apart without inspecting 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?

Gives explicit when-to-use criteria ('whenever an answer will be quoted, cited, or acted on... must not invent facts') with concrete domains (financial verdicts, legal claims, medical lookups, public statements). Also states the exclusion condition and alternative: 'prefer ask_pipeworx for casual lookups,' including the cost reason (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.