veradata-api

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

No annotations are provided, so the description must disclose behavioral traits. It mentions cost ($0.10 USDC via x402) and the general nature, but lacks details on idempotency, rate limits, or authentication needs.

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 extremely concise with two sentences, no wasted words, and front-loads 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?

With 4 parameters, no output schema, and no annotations, the description is too sparse. It omits the query and x_payment parameters, and does not describe the return format, making it incomplete for reliable agent use.

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 50%, requiring the description to explain parameters. It only mentions sector and country, ignoring query and x_payment. It adds marginal meaning but insufficiently compensates for undocumented parameters.

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 states it provides 'AI-powered LATAM market context' with sector and country inputs producing market_size, key_players, regulations, growth signals. It clearly distinguishes from siblings like vera_entity, vera_rates, vera_sanctions.

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 for LATAM market context and lists sibling tools, but does not explicitly state when not to use this tool 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?

No annotations are provided, so the description carries the full burden. It discloses the cost ($0.03 USDC via x402) and the registries accessed, but does not explicitly state that the operation is read-only, idempotent, or what happens on errors or missing entities. The behavioral disclosure is adequate but not rich.

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 long, front-loading the core purpose. Every phrase adds value: registries, output fields, cost, and payment method. No extraneous words, making it highly efficient.

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 absence of an output schema, the description covers the essential return fields (NIT/CNPJ, status, representative, industry). It also mentions the payment requirement. Missing are details on error handling, number of results, or any side effects. For a simple enrichment tool, this is reasonably complete, but lacks some edge-case context.

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 50% (name and identifier have descriptions; country and x_payment do not). The description adds context by mapping country values to registries (RUES CO, CNPJ BR, RFC MX) and explaining identifier types (NIT, CNPJ, RFC). However, it does not explain the x_payment parameter's format or purpose beyond the cost mention, leaving some ambiguity.

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 company enrichment from specific LATAM public registries (RUES CO, CNPJ BR, RFC MX) and lists the returned fields (NIT/CNPJ, status, representative, industry). It distinguishes itself from siblings by specifying the registries and output, making its purpose unambiguous.

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 no guidance on when to use this tool versus alternatives (e.g., vera_context, vera_sanctions). It does not state prerequisites, limitations, or conditions where another tool would be more appropriate. The usage context is implied but not explicitly compared to siblings.

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?

Description discloses real-time nature, returned data types, and a cost ($0.02 USDC via x402), but with no annotations, it fails to mention safety (read-only?), error handling, or rate limits. Adequate but not comprehensive.

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, front-loaded with purpose, then outputs and cost. No wasted words. Highly efficient.

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, description lists return types (FX, benchmark, inflation) and cost. Lacks detailed structure or pagination info, but sufficient for basic selection and use.

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?

All three parameters are documented in the schema (100% coverage), so description adds minimal value beyond confirming country codes and optional signals. Baseline 3 is appropriate.

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 the tool returns real-time LATAM central bank rates for specific countries (CO, MX, BR, CL, PE) and lists output types (FX, benchmark, inflation). However, it lacks an action verb like 'get' or 'retrieve', slightly reducing clarity.

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?

Usage context is implied by the description (LATAM rates) and sibling tools (context, entity, sanctions) suggest distinct purposes. But no explicit guidance on when to use this tool versus alternatives or when not to use it.

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 carries full burden. It discloses the cost ($0.05 USDC via x402) and the return values (risk_score, audit hash), which are important behavioral traits. However, it does not explicitly state whether the tool is read-only or if it has 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 extremely concise (two sentences) and front-loaded with the core purpose. Every piece of information (scope, lists, output, cost) is relevant and earned 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's moderate complexity (four parameters), no output schema, and no annotations, the description provides sufficient context about purpose, output, and cost. It lacks details on error handling or edge cases, but overall it is fairly 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 50% description coverage (name and country have descriptions). The description adds no additional parameter-specific information beyond what is in the schema, so it meets the baseline for this coverage level.

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 is for global sanctions screening with a focus on LATAM operations, lists specific sanction bodies (OFAC, UN, EU, UK) and entry count, and mentions the output format (risk_score, audit hash). It distinguishes itself from siblings like vera_entity and vera_rates.

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 for sanctions screening in LATAM but does not explicitly state when to use versus alternatives or provide any exclusions. No comparison with sibling tools is given.

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