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

No annotations are provided, so the description carries the full disclosure burden. It does add valuable behavioral context — the endpoint is paid, a free preview exists, and picks are historically settled — but it does not state access/auth mechanics, whether results are cached or time-sensitive, or how many picks are returned. Adequate but with clear gaps.

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?

Two sentences, front-loaded with the tool's identity and screening rule, then the preview/payment caveat. Dense but each clause contributes. Slightly compressed punctuation 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 and no parameters, the description must describe the return payload, and it does: model probability, ask, edge, and settled hit-rate. It also explains the qualifying threshold and the free-record preview, which is enough for an agent to call and interpret the result. Minor omissions around freshness and result volume keep it at 4.

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?

The tool takes zero parameters, so there is nothing to disambiguate at the input layer. The description correctly does not waste space inventing parameters, which meets the baseline for a no-param tool.

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 specific resource (today's football picks) and the precise qualifying criterion: a last-6-form Poisson model beating the live Polymarket moneyline by 10+ points. It also enumerates the returned fields (model probability, ask, edge, settled hit-rate). It does not, however, distinguish this from the many sibling akari_* tools such as akari_inplay_edge or akari_alpha_brief, so an agent must infer the boundary.

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 clear contextual guidance: check the free /x402/picks/preview settled record before paying, and 'never take a pick without it.' That tells the agent a prerequisite step, but it never says when to choose this tool over sibling analysis tools, nor does it name any alternative.

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