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

Richly discloses behavior beyond the readOnlyHint=true and destructiveHint=false annotations: the exact success return shape ({answer, evidence, confidence, source, fetched_at, refusal_reason:null}), the full refusal contract with enumerated refusal_reason values, the 'ONLY what the tool result contains' extraction rule, and the extra LLM call cost. This gives the agent a precise mental model of grounding and refusal semantics that annotations alone cannot.

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 longer than average but information-dense — every sentence carries a distinct fact: purpose, routing mechanism, return shape, refusal behavior, usage guidance, cost tradeoff. It is front-loaded with the core purpose before the implementation detail. Minor redundancy ('Same routing as ask_pipeworx' is stated once and the cost comparison later reinforces it) keeps it from a 5.

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 fully carries the burden of explaining return values — which it does, covering both success and refusal paths with the exact JSON shape and refusal enum. Combined with full parameter documentation in the schema and safety annotations, an agent has everything needed to invoke this tool correctly, including cost awareness to avoid over-use.

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 already documents the question parameter and its five aliases (q, text, input, query, prompt). The description adds context that the question will be routed across many tools and that arguments get filled automatically, which slightly enriches understanding, but it does not add specific parameter format or scoping detail. Baseline 3 is appropriate.

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, functional label — 'Hallucination-resistant answer mode for high-stakes reads' — then states the mechanism: routes a question across 5,908 tools / 1,540 sources, fetches data, and extracts the answer only from the tool result. It names the sibling it parallels ('Same routing as ask_pipeworx') while making its distinguishing trait (grounded extraction) explicit. An agent can immediately tell this apart from ask_pipeworx, ask_pipeworx_beta, and validate_claim.

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?

Provides explicit when-to-use criteria: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts,' with concrete domains (financial verdicts, legal claims, medical lookups, public statements). It also gives the exclusion: 'prefer ask_pipeworx for casual lookups,' and justifies it with the cost tradeoff. No inference is required.

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