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

Annotations already declare readOnly/idempotent/openWorld, so safety is covered; the description adds substantive behavior beyond that: the exact success return shape ({answer, evidence, confidence, source, fetched_at, refusal_reason}), the enumerated refusal modes, and the extra-LLM-cost/latency penalty versus ask_pipeworx. With no output schema present, this disclosure carries real weight.

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?

It is dense and runs long, but the mode definition, return contract, and usage routing are front-loaded and each sentence carries distinct information. Slightly verbose for a single-parameter tool, but nothing 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?

For a routing-and-extraction tool with no output schema, the description fully covers the return contract, the failure modes, and the routing/cost tradeoff. An agent has everything it needs to select and call this correctly.

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%, and the schema itself documents the aliases and the 'question' field. The description adds no syntax, format, or constraint detail beyond what the schema provides, 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?

States a specific verb (extract a grounded answer) and resource (routed pipeline query), and explicitly distinguishes itself from the sibling ask_pipeworx ('same routing as ask_pipeworx... then EXTRACTS the answer using ONLY what the tool result contains'). An agent can tell it apart from ask_pipeworx and ask_pipeworx_beta without opening a schema.

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?

Names exactly when to use it ('whenever an answer will be quoted, cited, or acted on... financial verdicts, legal claims, medical lookups, public statements') and when not to ('prefer ask_pipeworx for casual lookups'), including the cost tradeoff of one extra LLM call. Nothing is left to inference.

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