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

No annotations provided, so description carries full burden. It accurately describes the read-only behavior, the information returned, and the fallback for unset wallets. No contradictions or hidden side effects noted.

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, each providing essential info: purpose, return details, and fallback. No redundancy, perfectly front-loaded.

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?

For a simple balance check tool with no output schema, description covers all needed aspects: what it does, what it returns, and what happens if setup is missing. Context is fully 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?

Zero parameters and schema coverage 100%. Description reiterates no parameters are required, which adds no new info but is consistent. Baseline 4 is appropriate for zero-parameter 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 specifies the tool checks the AgentCash USDC wallet balance on Base, detailing what is returned (balance and approximate call count). It clearly distinguishes itself from siblings like x402_call (which likely makes payments) and x402_discover.

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 states no parameters are needed and mentions setup instructions if missing. It implicitly conveys when to use (when you need balance info), but does not explicitly discuss when not to use or provide 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?

Despite no annotations, the description fully discloses the 3-step payment flow, requirements for AgentCash wallet, and retry logic. No contradictions or hidden behaviors.

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?

Well-structured with clear sections, bullet-point steps, and examples. Every sentence adds value; no 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 no output schema, the description lacks explicit return value details, but examples imply endpoint data. Overall, it covers purpose, flow, requirements, and usage adequately.

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 covers the 'url' parameter with 100% coverage, and description adds examples and explains it accepts full URLs with query parameters, adding 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?

Description clearly states it calls x402 paid APIs with automatic USDC payment. It distinguishes from siblings (x402_balance, x402_discover, x402_research) which handle different aspects of the x402 protocol.

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 when-to-use context with examples and mentions integration with x402_discover. Lacks explicit when-not-to-use or alternative tools, but context is sufficient.

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?

No annotations are provided, so the description carries the full burden. It describes the tool as a read-only search across the ecosystem, mentions the fallback mechanism, and lists categories. No destructive behavior is indicated, and no contradictions are present.

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 well-structured with bullet points and examples, front-loading the core purpose. While somewhat lengthy, every sentence adds value and the structure aids readability.

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 lacks explicit details about the output format (e.g., what fields are returned). Given no output schema, this is a notable gap. However, the mention of x402_call for calling endpoints implies the tool returns endpoint details, and the examples suggest a list.

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 single parameter 'query' has a clear description in the schema, and the tool description adds valuable examples and context (e.g., 'domain security' → finds Domain Shield). Schema coverage is 100%, so the description complements the schema well.

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 searches for x402 paid API endpoints, specifies the source (Decixa with local fallback), and distinguishes it from siblings like x402_call. Examples illustrate specific queries and expected results.

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 tells when to use this tool (for discovery) and explicitly links to x402_call for calling endpoints. It provides query examples but does not explicitly state 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?

No annotations are provided, so the description carries the full burden. It discloses parallel calling, automatic payment, and cost control via max_cost. However, it omits details like authentication requirements, error handling, rate limits, and potential side effects.

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 well-structured with a clear main sentence, followed by bullet points and examples. It is concise yet informative, with no redundant sentences. Every part contributes to understanding the tool's functionality.

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 or annotations, the description covers the essential aspects: input processing, parallel execution, and cost management. It lacks details on return format and error scenarios, but these are mitigated by the tool's simplicity and the combined results description.

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. The description significantly adds value by explaining the subject parameter's auto-detection behavior and providing concrete examples. For max_cost, it clarifies that cheapest endpoints are called first, which is not evident from the schema alone.

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: running comprehensive research by calling multiple x402 endpoints in parallel. It specifies the input types (domain, IP, address, drug, sport) and the workflow (auto-detection, endpoint selection, parallel calls). This distinguishes it from siblings like x402_call, which likely calls a single endpoint.

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 usage context, including when to use (fastest way to get intelligence) and examples for each input type. However, it does not explicitly mention when not to use or compare with sibling tools like x402_call or x402_discover.

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