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

With no annotations provided, the description carries the full burden and fully discloses the exact scoring rubric, the three analysis dimensions, and the returned fields (0-100 score, first-trade timestamp, total notional, methodology). This gives an agent an accurate behavioral model of the tool's computation and output.

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 three dense sentences, front-loaded with purpose followed by a numbered breakdown of the scoring logic and return values. Every sentence contributes necessary information, and the detail about point thresholds is essential for understanding the tool's behavior.

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?

Given the absence of an output schema, the description compensates by explicitly listing return fields and methodology, making the tool actionable. It does not explain how to choose between the optional id and slug parameters or how malformed wallet addresses are handled, but these are minor gaps given the schema and dense functional description.

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 input schema already documents all three parameters with 100% coverage, so the schema carries the burden. The description adds only general context ('single wallet', 'specific market') and does not provide new parameter-level meaning beyond what the schema already states, meriting the baseline score.

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 opens with a specific function: 'Statistical timing analysis of a single wallet's position on a specific market' and enumerates three concrete checks with scoring values. It also mentions pairing with pg_information_advantage_score, which distinguishes this tool's analytic niche from sibling tools.

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 clearly scopes usage to a single wallet's position on a specific market and explicitly recommends pairing with pg_information_advantage_score for a full assessment, giving practical usage context. It does not provide explicit exclusions or a full list of alternatives, so it falls short of a 5.

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