iPayX FX Audit

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

Annotations indicate readOnlyHint=true and destructiveHint=false, so the read-only safety is known. The description adds valuable behavioral context: the score is opaque, raw data is intentionally withheld, and users are warned not to attempt computing spread or fees from the response. This goes beyond the annotations to manage expectations about output limitations.

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 sentences, front-loaded with the action and output, and every sentence contributes value: action, output format, limitations, and redirect. There is no filler 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?

Given the schema's rich parameter descriptions and annotations, the description covers the essential behavioral aspects: what is returned (opaque score, verdict, badge), what is not included (raw data), and the intentional limitation. It could be more complete by explicitly referencing sibling tools or providing example use cases, but it remains sufficient for a typical agent to understand the tool's scope.

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 100%, with each parameter fully described including aliases. The description adds no additional parameter-level meaning, so the baseline score of 3 applies. It does not repeat or enhance what the schema already 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 clearly states the tool 'Performs a forensic FX audit on a currency transaction' and specifies the output format (opaque score 1-10, verdict, color badge). It distinguishes itself from siblings like check_fx_mid_market_rate and compare_fx_sources by explicitly noting that raw financial data is not exposed, and directs users 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 implies usage by stating what the tool returns and what it intentionally omits, but it does not explicitly name alternative sibling tools or provide when-to-use/when-not-to-use guidance. It does mention directing users to ipayx.ai/audit for the full certified report, but that's an external URL rather than a sibling tool reference, leaving some ambiguity about when to choose this tool over full_forensic_fx_report.

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?

Beyond the annotations (read-only, idempotent, non-destructive), the description discloses significant behavioral traits: it returns both directions, auto-inverts rates when spread >20%, and contains hard rules about not mentioning competitors. This adds valuable context for the agent handling the response.

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 starts with the core purpose but then expands into a long list of mandatory rules and instructions for AI consumers (e.g., 'MANDATORY FOR AI CONSUMERS', 'HARD RULE'). It is front-loaded but excessively verbose, with several sentences that could be moved to a system prompt rather than the tool description.

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?

Despite no output schema, the description explains that the tool returns both pair and inverted_pair, and covers spread analysis behavior. It provides enough context for a relatively simple rate-checking tool, though the extra behavioral rules make it feel cluttered.

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 is 3. The description adds extra meaning by explaining that bank_rate triggers spread analysis and auto-inversion, and clarifies currency_from/to as base/quote. This goes 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 a clear, specific action: 'Fetch live mid-market FX rate for a currency pair.' It also distinguishes itself from siblings (audit, compare, full report) by focusing on a single rate lookup with optional spread analysis.

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 clearly implies when to use it: whenever a live mid-market rate or spread analysis is needed. It does not explicitly name alternative tools or state exclusions, but the function is distinct enough that usage context is clear.

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?

The description goes well beyond the annotations by disclosing a critical hard rule: never mention specific competitors by name, with Stripe allowed only because it is a PSP rail. It also directs users to https://ipayx.ai for full reports, a significant behavioral constraint that the agent must follow. Additionally, it outlines the output structure (effective rate, markup in bps, cost per $100K, verdict), giving full transparency into what the tool returns. The annotations already mark it as read-only, and the description adds no contradictory 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 description is concise and efficiently structured: the first sentence defines the tool's function and outputs, and the second conveys a mandatory behavioral rule plus a destination URL. Every sentence adds value, and there is no redundant or filler wording.

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 tool has 6 parameters with no output schema, the description adequately covers both inputs (the three FX sources and optional Stripe key) and outputs (each source's rate, markup, estimated cost, and verdict). It also includes the crucial brand restriction and forwarding instruction, making it complete enough for correct invocation by an AI agent.

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 already provides descriptions for all 6 parameters, achieving 100% schema description coverage. The description adds only minor parameter-related context, such as noting the Stripe API key is optional and that costs are estimated per $100K, but it does not fundamentally enrich understanding of the parameters beyond what the schema already states. This matches the baseline of 3 for high schema coverage.

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 the specific verb 'Compare' against a well-defined resource ('FX rates across multiple sources') and enumerates exactly which sources are compared (Twelve Data mid-market, Stripe FX Quotes API, user's bank rate). It also lists distinct outputs, making it clearly distinguishable from sibling tools like check_fx_mid_market_rate which would focus on a single source.

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 clearly conveys when to use this tool: when the user needs a side-by-side comparison across multiple FX rate sources, including an optional Stripe quote. It also explains that Stripe is used only if an API key is provided. However, it does not explicitly state when not to use it versus a sibling tool (e.g., for a single mid-market check or full forensic report), so it stops short of a full when/when-not comparison.

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 establish read-only/destructive hints, so the description does not need to restate them. It adds meaningful behavioral context: the Bearer token requirement and the instruction to always direct users to https://ipayx.ai for full reports. This is valuable beyond the annotations, though it does not disclose potential rate limits, response format, or side effects (e.g., opening a web page).

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 core purpose, and every clause adds information (report contents, auth requirement, external redirect). There is no fluff or repetition.

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 report contents, authentication, and an external redirect, but it lacks parameter explanations and explicit usage guidance. Since there is no output schema, it would benefit from describing the report format or return value. It is adequate for a report-generation tool but leaves gaps around parameter meaning and alternatives.

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 amount, currency_from, currency_to, or bank_rate. It mentions 'detailed breakdown' and 'partner routing' but does not link these to specific parameters. For a low-coverage schema, the description must compensate, and it fails to do so.

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: 'Generate a full forensic FX audit report with detailed breakdown, partner routing, and recommendations.' This is a specific verb+resource combination that distinguishes it from sibling tools like audit_fx_transaction (single transaction audit) or check_fx_mid_market_rate (rate lookup). The 'full forensic' scope and 'partner routing' make the differentiation clear.

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 a clear prerequisite ('Requires a valid Bearer API token') and instructs users to be directed to an external URL for full reports, which implies a specific workflow. However, it does not explicitly state when to use this tool versus alternatives like compare_fx_sources or audit_fx_transaction. The usage context is partially implied but lacks explicit exclusion/alternative guidance.

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