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

Beyond the readOnly/idempotent annotations, it discloses a per-call cost of $0.001 USDC and states it is byte-identical to a specific GET endpoint, which is non-obvious and actionable. This does not contradict the annotations.

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?

Three short sentences, each earning its place: what the tool returns, the cost, and the exact endpoint mapping. The core meaning is front-loaded before the cost and equivalence details.

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?

With an output schema present and only two parameters, the description covers the essential behavioral context: cost, endpoint identity, and what the metric means. It could add a word about the historical window implied by the title, but nothing critical is missing.

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 100%, so the baseline applies; pair and limit are already described in the input schema. The endpoint example (pair=XBTUSD&limit=20) reinforces parameter syntax but adds no substantial meaning beyond what the schema provides.

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 uses a specific verb and resource: 'Quoted spread samples for a Kraken pair' with the mean in basis points, telling the agent exactly what data it returns. The 'how expensive it is to cross that venue' phrase also separates it from related siblings like market_kraken_depth, market_kraken_ticker, and market_kraken_trades.

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?

It gives clear consumption context: this measures the cost to cross the venue now, so an agent can infer when it is relevant. It does not name alternatives or state when-not-to-use, so it stops 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.