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

With no annotations, the description carries the full burden and does well: it discloses the price ($0.01 USDC per call) and the return composition, and the schema pairs it with the x402 payment and free-trial mechanics. It still omits latency, error/refund behavior, and whether the three models are distinct providers, so it is not fully transparent.

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?

Three tightly packed sentences: capability first, then the use case that selects it, then the price. No filler, and the most routing-relevant information 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?

With no output schema, the description usefully enumerates what comes back (verdict, confidence, agreements, dissent, what would change the answer), which an agent needs to interpret results. The payment path is left mostly to the schema's field descriptions, and sibling differentiation is absent, keeping it short of complete.

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%, so q, x_payment, and free_trial are already fully documented. The description's only extra contribution is the phrase 'quick tier only' for the free trial, hinting at a tier structure the schema does not spell out; otherwise it stays at the baseline.

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 concrete verb and resource ('Put one question to 3 DIFFERENT AI models and get a single verdict back') and enumerates the shape of the result (confidence, agreement, dissent, counterfactual). It does not, however, distinguish itself from its siblings council_deep and council_grounded, so an agent cannot tell from the text which council variant to pick.

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 framing with example decision questions ('is this safe, is it worth it, which option'), which is exactly the context an agent needs to route a judgement call here. It stops short of naming when NOT to use it or pointing to the deep/grounded siblings as alternatives.

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