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

With no annotations, the description carries the full behavioral burden. It does add valuable context that the call costs $0.03 USDC (30000 atomic) and that the data is public, but it omits rate limits, failure modes, and whether payment failures are recoverable.

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 tight sentences with no filler; the payment cost is front-loaded, which is arguably useful for gating decisions, though leading with purpose might read more naturally.

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?

An output schema exists, so listing return fields is slightly redundant but harmless. Payment cost, venue, and payload are covered; only the routing decision versus hl_book_depth is unstated, which is a minor gap for a two-parameter read tool.

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 description coverage is 100%, so both parameters (pair, count) are already documented with examples and defaults. The description adds nothing beyond the schema about parameter semantics, so the baseline 3 applies.

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 resource and venue ('Kraken public order book depth') plus the concrete payload (bids, asks, mid price, volume imbalance). This clearly distinguishes it from the sibling hl_book_depth, which an agent can infer covers a different venue.

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 'Kraken' qualifier implicitly tells the agent when to pick this over hl_book_depth, and the PAID tag flags a gating condition, but there is no explicit when-to-use or when-not-to-use statement. Usage is left to inference from the venue name.

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