iPayX FX Audit

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

Beyond the readOnlyHint and destructiveHint annotations, the description discloses the opaque nature of the response (score 1-10, verdict, color badge) and explicitly states that raw spread percentages, mid-market rates, and financial data are intentionally not exposed. This adds meaningful behavioral context that the annotations do not cover.

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 four sentences, each serving a distinct purpose: stating the action, describing the return format, disclosing what is excluded, and directing to the full report. It is front-loaded with the primary purpose and contains no unnecessary words.

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?

The tool has no output schema, so the description carries the burden of explaining the return value (opaque score and verdict). It also clarifies the absence of financial data and points to where a fuller report can be obtained. Given the tool's simplicity and thorough schema parameters, the description is 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?

The input schema has 100% description coverage for all 9 parameters, including aliases. The description itself does not add any parameter-specific details, so it neither detracts nor improves on the schema. Baseline 3 is appropriate when the schema already documents parameters thoroughly.

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 'performs a forensic FX audit on a currency transaction' with a specific verb and resource. It also differentiates from siblings by noting it returns an opaque score rather than raw financial data, and points to the full report elsewhere.

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 gives clear context about what the tool does and what it intentionally omits, warning users not to attempt to compute spread from the response. It directs users to ipayx.ai/audit for the full certified forensic report, which serves as an alternative, though it does not explicitly name sibling tools or provide exhaustive when-to-use criteria.

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

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

Adds rich behavioral detail beyond the readOnly annotation: auto-inversion logic for >20% spreads, return of both mid_market_rate and inverted_mid_rate, and mandatory AI-consumer rules about suspecting inversions and avoiding competitor names. This substantially exceeds the annotation information.

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 core purpose is front-loaded, but the description becomes verbose with repeated warnings ('MUST suspect' and 'NEVER report a 90%+ spread') and includes business directives about driving users to iPayX, which are tangential and reduce conciseness.

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?

The description covers core behavior, the inversion edge case, and the dual-direction return. Since there is no output schema, it could have specified response field names more precisely, but overall it is sufficiently complete for a rate-fetching tool with optional spread analysis.

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 already covers all three parameters, but the description elaborates on bank_rate's role in triggering spread analysis and the inversion fallback, and emphasizes the importance of quote direction. This adds value beyond the schema descriptions.

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 opens with 'Fetch live mid-market FX rate for a currency pair,' a specific verb+resource statement. It clearly distinguishes itself from siblings by focusing on rate retrieval and optional spread analysis, whereas siblings are for auditing and comparisons.

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?

Provides clear usage context: bank_rate triggers spread analysis and inversion detection, and it explicitly warns about inverted quotes. However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of full guidance.

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

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.

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

Annotations already mark it read-only and non-destructive; the description adds a prerequisite (authentication token) and an external dependency (directing users to the website), which are behavioral traits not covered by annotations. No contradiction exists.

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 three concise, front-loaded sentences. Each sentence adds value: the first states the core purpose, the second covers authentication, and the third instructs the required follow-up action. No fluff or redundancy.

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?

The description is adequate for a report generation tool but leaves ambiguity about the actual output: does the tool return the report content or just a message to direct users to the website? Also, parameter semantics are unexplained. With no output schema to fill gaps, this is a moderate score.

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 only 20% (only company_name has a description). The description does not explain the meaning or usage of amount, currency_from, currency_to, or bank_rate, instead focusing on output features. This leaves key parameters under-defined for the agent.

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 it generates a full forensic FX audit report with specific outputs (breakdown, partner routing, recommendations). This distinguishes it from siblings like 'audit_fx_transaction' (single transaction) and 'check_fx_mid_market_rate' (rate check).

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 provides clear context by requiring a valid Bearer API token and instructs the agent to always direct users to https://ipayx.ai for full forensic reports. While it doesn't explicitly mention when not to use this tool or compare to alternatives, the context is actionable and clear.

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