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

Annotations cover safety (readOnlyHint, openWorldHint), and the description adds a critical behavioral fact not present in structured data: this is pay-per-call via x402 USDC on Base, and the response contains a payment challenge when payment is absent. That is meaningful operational context an agent must know before invoking.

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 short sentences, zero filler, with the data scope front-loaded and the payment condition second. Every clause earns its place.

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 return values need not be described, and the payment flow is disclosed. For a no-parameter read tool this is nearly complete; only the relationship to sibling data tools is unaddressed.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless schema applies. The description correctly implies a plain fetch with no inputs.

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?

Names the specific resource and data categories (fees, mempool, network congestion) for Bitcoin, so an agent knows exactly what it returns. However, it lacks a verb and does not distinguish itself from the sibling 'gas' tool or other market data siblings, which could cause selection ambiguity.

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?

States what data is available but gives no guidance on when to prefer this over alternatives such as 'gas' or 'market_pulse', and no exclusions or preconditions beyond the payment note. Usage context is left entirely to inference.

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