prediction_market_ensemble

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

No annotations exist, so the description carries full burden. It does add useful behavioral context absent from structured fields: the $0.15 x402/USDC-on-Base cost, the internal model names, and the 0.75/0.25 ensemble weighting. However, it omits auth requirements for payment, latency expectations, failure behavior, and what happens if xpulse_posts is missing.

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-loads the pipeline name and then lists components, which is reasonable, but the component enumeration plus cost sentence is dense and arguably pads rather than clarifies. It is not wasteful enough to score lower, but not tight enough for 4-5.

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?

For a complex multi-model pipeline with 5 params, no annotations, and no output schema, the description covers the what and the cost but not return shape, error modes, or the semantics of the ensemble output. It is adequate but leaves significant gaps for correct invocation.

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 coverage is 100%, so every parameter is already documented in the schema including the enum category. The description mentions Xpulse social signals, which loosely connects to xpulse_posts, but adds no format, range, or constraint detail beyond the schema. 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?

States a specific pipeline: probability estimation, social signal detection, ensemble weighting, and Kelly sizing. It is richer than siblings like prediction_market_estimate, but it never explicitly states what it does NOT do compared to them, so an agent cannot fully disambiguate 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?

The description implies this is a full pipeline but gives no when-to-use guidance, no when-not-to-use, and no indication of when the cheaper single-purpose siblings (estimate, size, scan, info) should be preferred.

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