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

With no annotations, the description carries the full burden and does substantial work: it discloses the HTTP verb (GET, i.e. read-only), the payment/auth requirement ($0.04 via x402), the ranking methodology (absolute probability change over the window), and that output includes volume surge ratios. Missing rate limits and error behavior, but this is well above average for an unannotated tool.

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 core definition, then the differentiating sentence, then a compact bracket with endpoint, price, and docs link. Every element earns its place; the bracket is dense but operationally useful rather than 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 4-param, no-output-schema, no-annotation tool, the description covers purpose, ranking semantics, and payment model, but leaves the meaning of limit and category, default behavior, and response field shape unaddressed. Adequate but with visible gaps.

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 only 25% (only min_liquidity is documented), so the description must compensate. It adds meaning for window ('1h/6h/24h' and 'absolute probability change over your chosen window'), but says nothing about limit or the category parameter — which is especially notable since a category filter on a Fed-pre-filtered tool is non-obvious.

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 verb+resource+scope: 'Biggest Federal Reserve probability moves (1h/6h/24h)'. This cleanly separates it from the generic probability_movers (all markets) and from level-oriented siblings like probability_board_fed, without needing the schema opened.

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 fastest way to see where news is landing in Federal Reserve' implies a use case (news-driven change detection), and 'Same shape as /v1/movers, pre-filtered to Federal Reserve markets' points at the parent tool. But there is no explicit when-to-use-vs-when-not guidance against probability_board_fed or probability_movers, so the agent must infer.

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