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 that results are ranked by divergence with direction, that confidence derives from ensemble spread, that liquidity is included, that parse_coverage reports catalog coverage, and that signals only emit for classes passing a public calibration gate. It also exposes the transport (HTTP GET) and cost ($0.15 x402), which is useful behavioral context.

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 core purpose is front-loaded in the first sentence, followed by supporting detail, with transport metadata bracketed at the end. It is dense but every sentence carries information; no filler.

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 tool with no output schema and no annotations, the description is reasonably complete: it explains what is returned (divergence, direction, confidence, liquidity, parse_coverage) and the gating condition. The remaining gaps are the undocumented parameters and the absence of alternative-tool routing.

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 only 50%, so the description should compensate for undocumented parameters, but it adds no meaning for limit, min_divergence, or region beyond the schema. Only hazard carries a schema-level description. The ranking-by-divergence phrasing loosely touches min_divergence but never defines it.

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 states a precise verb and resource: it compares the model's event probability against the market-implied probability for weather-linked prediction markets, ranked by divergence. An agent immediately knows the deliverable (divergence signals). It does not, however, explicitly differentiate itself from close siblings like edge_weather-markets-delayed, leaving the real-time-vs-delayed distinction to inference.

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?

There is no explicit when-to-use guidance, no statement of when NOT to use it, and no named alternative. The calibration-gate sentence describes an emission condition rather than helping an agent choose this tool over edge_calibration, edge_detail, or edge_weather-markets-delayed.

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