dns-of-money

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

With no annotations, the description carries full burden. It discloses that the tool returns only agent capabilities and NO payment credentials, making the read-only nature clear. It does not mention auth or rate limits, but for a simple lookup this is adequate.

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 sentences and an example example. Every word adds value with no redundancy or fluff.

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 a single required parameter and no output schema, the description fully explains the tool's purpose, usage context, input format, and output scope. No information is missing.

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?

Parameter coverage is 100% via schema description. The description adds an example call ('discover_agent('pay:acme.user')') and explains the alias_uri format, providing 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: 'Get the AP2/A2A agent-commerce block for a pay: address'. It distinguishes from siblings like 'get_payment_requirements' and 'resolve_alias' by specifying it is for agent discovery before a mandate flow, and it returns capabilities not credentials.

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 explicitly says 'Use this during agent discovery before initiating a mandate flow' and clarifies what it returns and does not return. It lacks explicit alternatives or when-not-to-use, but the context with sibling tool names implies usage boundaries.

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?

With no annotations, the description discloses read-only behavior, lists returned data (credential requirements, rate limit), and describes the tool's role in the registration flow. It could mention error cases or data format, but overall transparent for a simple info tool.

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 efficient sentences plus an example. Every sentence adds value; no wasted words. Front-loaded with the core purpose.

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 no output schema, the description adequately covers key return items (endpoint, credential requirements, rate limit, anchor-proof endpoint). It could mention return format but is sufficient for understanding.

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?

No parameters exist, and the schema coverage is 100%. The description adds value by explaining what the tool returns, though it does not detail output structure (no output schema). Baseline 4 for 0-param tools.

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 returns registration info (endpoint, credential requirements, rate limit, anchor-proof endpoint) and distinguishes itself from siblings like discover_agent or get_payment_requirements by focusing on self-registration alias setup.

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 explains the tool is read-only and directs that the actual registration is a separate POST, giving clear context. However, it does not explicitly state when not to use it versus alternatives.

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?

With no annotations, the description fully discloses that the tool is deterministic, read-only ('never moves money'), and explains the settlement rails per currency. It does not mention error cases or auth requirements, but for a read-only query tool, coverage is adequate.

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 maximally concise: one sentence states the purpose, two sentences detail currency-specific behavior, and one line gives a concrete example. No filler words, every sentence 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?

Given the tool has 3 parameters, no output schema, and no annotations, the description covers the return structure, parameter details, and behavioral traits well. It could be further improved by mentioning whether the call requires authentication or listing possible error responses, but the current completeness is strong.

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%, but the description adds significant meaning: explains amount format ('decimal string in the asset's display unit'), clarifies when amount can be omitted, and details the implications of currency selection. The example further aids understanding.

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 starts with a clear verb-object phrase 'Get x402 PaymentRequirements for paying a pay: alias.' It specifies the exact return structure (the 402 accepts block). It is easily distinguished from siblings like discover_agent or resolve_alias, which serve different purposes.

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 explains when the tool is used ('for paying a pay: alias') and explicitly states what it does not do ('this tool never moves money'). It provides context for currency parameter choices ('XRP settles on XRPL, USDC on Algorand'). However, it does not explicitly mention when not to use it or alternatives.

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?

Discloses return fields (preferred rail, fallback endpoints, ISO 20022 hint, compliance signal) and tier-based visibility. Being a read-only resolution, it is safe. No annotations provided, so description covers well.

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?

Three sentences with no filler. Front-loaded purpose, then usage and output, ends with example. Every sentence adds essential information.

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 no output schema, description explains output fields. Covers usage, parameters, and edge cases (tier visibility). No gaps for a tool with 4 params and simple behavior.

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%, baseline 3. Description adds meaning: amount refines rail scoring, preferred_rail is advisory, alias_uri format with example. Adds clarity beyond 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?

Description clearly states it resolves a pay: address to payment metadata, with specific verb and resource. Distinguishes itself from siblings by explicitly stating its role in payment initiation.

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?

Explicitly advises to call before initiating a payment to a pay: address. Mentions API-key tier visibility. Does not explicitly differentiate from siblings, but context signals provide sibling names.

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