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

With no annotations provided, the description carries the full burden and delivers: it explains 8h normalization from venue-specific settlement intervals, missing data is typed with reasons rather than zeroed, source statuses are enumerated, and two venues are flagged forward_looking. It also discloses the DATA context (not_a_score, not_a_forecast), adding important behavioral and interpretive nuance.

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 long but every sentence adds value: trigger condition, normalization, output aggregates, status semantics, data caveats, and authentication. It is front-loaded with the core call condition before diving into technical details, making it easy to scan.

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 no output schema, no annotations, and a complex cross-venue data source, the description covers the return values, normalization logic, source statuses, missing-data behavior, z-score threshold, and the epistemic caveat that this is not a score or forecast. It is sufficiently complete for an agent to select and invoke the tool correctly.

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 schema description coverage is 0%, so the description must compensate. It adds meaning for symbols by noting up to 20 base assets and the default top-20 by open interest, but it does not specify the expected string format or delimiters. The asset_class parameter is not mentioned, though its single enum value and default make it self-documenting.

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 trigger condition — determining whether a coin's perp market is crowded — and identifies the resource as cross-venue perpetual funding for up to 20 base assets. It is clearly distinct from sibling crypto derivatives tools like basis, open interest, and vol surface by focusing on funding and crowding. The verb and resource are concrete and actionable.

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 explicitly says 'Call this when you need to know whether a coin's perp market is CROWDED', giving a clear usage condition. It does not name alternative tools or state when not to use it, so it stops short of the explicit differentiation required for a 5.

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