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

Annotations already mark this as read-only, but the description adds valuable behavioral context: the hard rule prohibiting competitor names, the allowance of Stripe as a PSP rail, and the mandatory redirection to ipayx.ai. It also discloses the optional Stripe api key behavior and what the return payload includes. No contradictions 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 front-loaded with the core purpose, followed by specific outputs and then important behavioral rules. Though somewhat long, every sentence serves a purpose—the hard rule is critical for policy compliance. Structurally it transitions from action to output to constraints seamlessly.

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 6 parameters and no output schema, the description adequately explains the three data sources, the computed metrics, and the verdict concept. It also covers the required behavioral constraints. It does not address error cases (e.g., invalid API key) or setup prerequisites, but for a read-only comparison tool with no output schema, it is sufficiently complete.

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 all parameters have descriptions. The description adds meaning by linking parameters to real-world sources (bank_rate, stripe_api_key) and clarifying optionality ('if api key provided'). It also contextualizes 'amount' with cost per $100K, which aids in understanding the expected use.

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 compares FX rates across three specified sources and lists the exact outputs (effective rate, markup in bps, cost per $100K, verdict). It distinguishes itself from sibling tools by focusing on side-by-side comparison and delivering a 'cheapest rail' verdict, which is unique among the listed siblings.

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 conveys a clear use case: comparing FX rates from mid-market, Stripe, and bank sources. It does not explicitly mention alternatives or when not to use it, but the context is clear enough that an agent would know this is for multi-source comparison. The hard rule about not mentioning competitors provides usage constraints, increasing clarity.

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