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

Annotations already declare the tool as read-only, open-world, idempotent, and non-destructive. The description adds valuable context about the tool's return structure (budget decision, tool-stack recommendation, fallback plan) and references a payment URL/cost, which is relevant for understanding the execution workflow. No contradiction with 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?

The description is two sentences, front-loaded with the primary purpose, followed by the return summary and payment linkage. It is concise and efficient, with no filler or redundant information that duplicates structured data.

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 presence of an output schema, the description does not need to detail return values. It covers the use case, output summary, and cost/payment angle. The main gap is the lack of parameter explanation, but the schema provides parameter names and some descriptions. Overall, the description is sufficiently complete for a quoting tool with annotations.

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 50%, with four parameters (needs_code, needs_onchain, needs_contacts, needs_current_web) lacking descriptions. The tool description does not compensate by explaining what these parameters mean or how they affect the quote. It relies solely on parameter names, which are not self-explanatory for all cases. The description adds no semantic value beyond the schema.

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 clearly states the tool's purpose with a specific verb ('Estimate') and resource ('cheapest sensible agent execution lane'), and enumerates the output types: budget decision, tool-stack recommendation, and fallback plan. It distinguishes itself from sibling tools like compare_market_tool_options and score_defi_token_risk by focusing on pre-purchase routing and cost estimation.

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 provides clear context for when to use the tool: 'before buying model calls or xpay tools'. This implies it is for pre-purchase planning. It does not explicitly enumerate when not to use it or name alternative tools, but the context is unambiguous enough to guide selection among siblings.

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