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

Goes well beyond the readOnly/idempotent/openWorld annotations: it enumerates the success payload shape (answer, evidence, confidence, source, fetched_at), every refusal_reason value, the refusal_cause sub-field for llm_error ('wall' vs 'route'|'threw'|'unparseable'|'wall_after_failure'), and the latency/cost profile. This is exactly the extra context the annotations cannot carry.

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?

Front-loaded with the core differentiator and the routing-to-extraction pipeline before the return contract and refusal taxonomy. It is dense and long, but nearly every clause carries operative information; only the detailed refusal_cause parenthetical is heavier than an agent strictly needs at selection time.

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, yet the description fully specifies the return contract, all failure modes, and when to prefer the cheaper sibling. For a 1-required-param router tool with no output schema, nothing an agent needs to call or interpret it 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% and the schema documents all aliases plus prefer_tool, so the baseline is 3. The description adds nothing about parameter behavior itself — notably it never mentions the seven alias spellings or the prefer_tool override, both of which live only in 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?

States a specific verb+resource ('grounded, hallucination-resistant answer mode') and the exact mechanism: routes to a tool, fills arguments, fetches data, then extracts the answer using only the tool result. It explicitly contrasts with the sibling ask_pipeworx, so an agent can distinguish the two 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?

Gives an explicit when-to-use rule ('whenever an answer will be quoted, cited, or acted on' with concrete domains: financial, legal, medical, public statements) and an explicit when-not rule ('prefer ask_pipeworx for casual lookups'), including the cost tradeoff of one extra LLM call that drives that choice.

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