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

With no annotations, the description carries the behavioral burden. It discloses the $0.05 x402 payment requirement, the z-score methodology, and the baseline caveat. It does not detail return shape or error/payment failure behavior, but it clearly communicates the core behavior.

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 description is compact, front-loaded with cost, and every sentence contributes: purpose, use case, exclusions, cautions, and parameter default. No filler or redundancy.

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?

The description is strong on use-case and behavioral context but incomplete for a 4-parameter tool with no output schema and no annotations: dataset and field are not specified, payment_header semantics are absent, and the return structure is only implied. It would be fully complete with a sentence on parameter semantics.

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 0%, so the description must compensate. It only explains z_threshold's default and role; dataset, field, and payment_header are required or relevant but not defined. The phrase 'keys whose latest move' hints that field is a numeric measurement, but this is not sufficient for correct invocation.

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?

Description opens by stating the tool returns statistical outliers, specifically keys whose latest move breaks their own historical baseline, with z-scores. It also distinguishes this from anansi_movers by warning not to use it to rank raw speed.

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?

Explicitly says to use it to separate genuine abnormal moves from ordinary volatility and gives a concrete alternative/exclusion: do not use it for raw speed ranking, which belongs to anansi_movers. It also cautions about young datasets inflating z-scores.

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