BCB Payment Methods MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific data sets within the BCB payment methods domain, such as establishments, monthly/quarterly payment data, cardholders, fees, ATMs, and card transactions. No overlap exists; the descriptions precisely differentiate the scope of each query.
Naming Consistency5/5
All tool names follow a consistent 'consultar_' prefix with descriptive nouns in Portuguese, using snake_case uniformly. This pattern is predictable and enhances readability across the set.
Tool Count5/5
With 8 tools, the server is well-scoped for querying BCB payment methods data, covering key aspects like establishments, transactions, fees, and infrastructure. Each tool earns its place without being excessive or insufficient.
Completeness4/5
The tool set provides comprehensive query coverage for historical and statistical data on payment methods, including establishments, transactions, fees, and infrastructure. A minor gap exists in lacking tools for creating or updating data, but this is reasonable for a read-only query server focused on BCB data.
Average 3.1/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool queries data, implying a read-only operation, but does not mention potential side effects, rate limits, authentication needs, or response format. The description lacks details on what 'quantidade' entails (e.g., counts, aggregated data) or any constraints beyond the quarterly scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It directly states what the tool does ('Consulta quantidade...') and the key constraint ('por trimestre'), with zero wasted words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 parameters, no annotations, no output schema), the description is incomplete. It lacks information on behavioral traits (e.g., read-only nature, potential errors), output format, or usage context relative to siblings. While the schema covers parameters, the description does not address gaps in understanding how the tool behaves or what results to expect, making it inadequate for full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear documentation for all parameters (trimestre, top, ordenar_por, filtro). The description adds no additional parameter semantics beyond implying a quarterly focus for 'trimestre', which is already covered in the schema. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate with extra insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Consulta quantidade de estabelecimentos credenciados para aceitar meios de pagamento eletrônico por trimestre' (Query quantity of establishments accredited to accept electronic payment methods per quarter). It specifies the verb ('Consulta'), resource ('estabelecimentos credenciados'), and scope ('por trimestre'), but does not explicitly differentiate from sibling tools like 'consultar_meios_pagamento_trimestral', which might overlap in quarterly focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions 'por trimestre' (per quarter), but does not clarify if this is the only temporal scope available or how it differs from monthly tools like 'consultar_meios_pagamento_mensal'. There are no explicit when/when-not instructions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states it's a query operation ('Consulta'), implying read-only behavior, but doesn't disclose authentication needs, rate limits, pagination (beyond the 'top' parameter hint), error handling, or what the return data looks like (e.g., structure, fields). For a query tool with no annotation coverage, this is a significant gap in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence in Portuguese that front-loads the core purpose ('Consulta informações sobre portadores de cartões de pagamento por trimestre'). It has zero waste, with every word contributing to the tool's intent and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a query tool with three parameters, the description is incomplete. It lacks details on behavioral traits (e.g., safety, performance), output format, and usage context relative to siblings. While concise, it doesn't provide enough context for an agent to fully understand how and when to invoke this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for all three parameters (trimestre, top, filtro). The description adds no additional parameter semantics beyond what's in the schema, such as explaining the 'filtro' OData syntax or default behaviors. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Consulta' (query/consult) and the resource 'informações sobre portadores de cartões de pagamento' (information about payment card holders), specifying the temporal scope 'por trimestre' (by quarter). It distinguishes from some siblings like consultar_estabelecimentos_credenciados (query accredited establishments) but not from consultar_transacoes_cartoes (query card transactions), which might overlap in data domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. The description mentions 'por trimestre' (by quarter), which might imply usage for quarterly data, but it doesn't specify contexts, exclusions, or compare to siblings like consultar_meios_pagamento_trimestral (query quarterly payment methods) or consultar_transacoes_cartoes (query card transactions).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but provides minimal behavioral information. It states this is a query operation but doesn't disclose important details like whether it's read-only, what permissions might be needed, rate limits, pagination behavior (beyond the 'top' parameter), or what format the results will be in. For a tool with 3 parameters and no output schema, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point. Every word contributes to understanding the tool's purpose without any fluff or redundancy. It's appropriately sized for what it communicates.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a query tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, how results are structured, or provide context about the data source. While the schema covers parameters well, the overall tool behavior remains opaque to an AI agent trying to understand what to expect from using this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It doesn't explain how parameters interact or provide examples of typical parameter combinations. Baseline 3 is appropriate when the schema does the documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Consulta' - query/consult) and the resource ('taxas de desconto cobradas de estabelecimentos comerciais por operações com meios de pagamento' - discount rates charged to commercial establishments for payment operations). It distinguishes from most siblings which query different resources, though it doesn't explicitly differentiate from 'consultar_taxas_intercambio' which also deals with rates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention the sibling tools, explain what makes this tool unique, or specify use cases where this tool is preferred over others like 'consultar_taxas_intercambio' or the various payment method queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns data on quantity and value of card transactions, which is useful, but lacks critical details: it doesn't specify if this is a read-only operation (implied but not explicit), whether it requires authentication, any rate limits, pagination behavior (though 'top' parameter hints at it), or error conditions. For a query tool with 4 parameters, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, stating the core purpose in the first sentence and adding return details in the second. Both sentences earn their place by clarifying scope and output. However, it could be slightly more structured by explicitly separating purpose from behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema, no annotations), the description is incomplete. It covers the basic query purpose and return data but misses behavioral context (e.g., safety, performance), usage guidance relative to siblings, and deeper parameter insights. For a tool with no annotations or output schema, more comprehensive description is needed to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional parameter semantics beyond implying the query is filtered by quarter. It doesn't explain relationships between parameters (e.g., how 'filtro' interacts with 'trimestre') or provide examples beyond what's in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Consulta estoque e transações de cartões de pagamento por trimestre' (Query stock and transactions of payment cards by quarter). It specifies the resource (payment card stock/transactions) and verb (query/consult), though it doesn't explicitly differentiate from sibling tools like 'consultar_meios_pagamento_trimestral' which might have overlapping scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It mentions the quarterly timeframe but doesn't compare to monthly tools (e.g., 'consultar_meios_pagamento_mensal') or other related tools. There's no mention of prerequisites, exclusions, or typical use cases beyond the basic query scope.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a query/consult operation, implying it's read-only, but doesn't explicitly confirm this. It mentions the quarterly scope but doesn't describe what data is returned, potential limitations, authentication requirements, rate limits, or error conditions. For a tool with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without any wasted words. It's appropriately sized for a query tool and front-loads the essential information. Every word earns its place in defining what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, 1 required), 100% schema coverage, but no annotations and no output schema, the description is minimally adequate. It states what the tool does but doesn't provide enough context about when to use it, what data it returns, or behavioral characteristics. For a query tool with good schema documentation but no other structured information, this leaves room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description mentions 'por trimestre' (by quarter) which aligns with the 'trimestre' parameter, but adds no additional semantic context beyond what's in the schema. With complete schema coverage, the baseline score of 3 is appropriate since the description doesn't need to compensate for schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Consulta' - query/consult) and the resource ('taxas de intercâmbio praticadas no mercado de meios de pagamento por trimestre' - exchange rates in the payment methods market by quarter). It distinguishes from siblings by focusing specifically on exchange rates rather than establishments, payment methods, cardholders, discount rates, ATMs, or card transactions. However, it doesn't explicitly contrast with the similarly named 'consultar_taxas_desconto' (consult discount rates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention when this tool is appropriate versus 'consultar_taxas_desconto' (which deals with discount rates) or 'consultar_meios_pagamento_trimestral' (which deals with payment methods quarterly data). There's no indication of prerequisites, constraints, or typical use cases beyond the basic functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Consulta' implies a read-only operation, it doesn't specify whether this is a real-time query, historical data lookup, or if there are rate limits, authentication requirements, or data freshness considerations. The description lacks behavioral details beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that immediately communicates the core functionality. There's no wasted verbiage or unnecessary elaboration, making it optimally concise while still being informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a query tool with 3 parameters and no output schema, the description adequately covers the basic purpose but lacks information about return format, data structure, or error conditions. With no annotations and no output schema, the description should ideally provide more context about what statistics are returned and in what format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, so all parameters are documented in the schema itself. The description mentions 'por trimestre' which aligns with the required 'trimestre' parameter, but adds no additional semantic context beyond what's already in the schema descriptions. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Consulta' - query/consult) and the resource ('estatísticas sobre terminais de autoatendimento'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools that also query different types of financial data, though the ATM terminal focus is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 the sibling tools, nor does it mention any prerequisites or alternative scenarios. It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It describes a query operation ('Consulta') which implies read-only behavior, but doesn't explicitly state whether it's safe, whether it requires authentication, rate limits, or what happens with large datasets. The description mentions pagination parameters (top, skip) but doesn't explain pagination behavior or default values beyond what's in the schema. For a tool with 4 parameters and no annotation coverage, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured in two sentences: the first states the purpose and scope, the second provides crucial parameter formatting guidance. Every word earns its place, with no redundant information. It's appropriately sized for a query tool with good schema documentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters with 100% schema coverage but no annotations and no output schema, the description does an adequate but minimal job. It clarifies the monthly focus and parameter format, which helps contextualize the tool. However, for a data query tool with pagination and filtering capabilities, the description should ideally mention something about the return format, data volume considerations, or typical use cases to compensate for the lack of output schema and annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds value by providing a concrete example of the 'ano_mes' parameter format ('YYYYMM' with '202312' example), which clarifies the expected syntax beyond the schema's similar description. However, it doesn't add meaningful context about the other parameters (top, skip, filtro) beyond what's already in their schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Consulta' - query/consult) and the resource ('dados mensais sobre meios de pagamento' - monthly data about payment methods), with specific examples of what's included (boletos bancários, PIX, TED, DOC e outros). It distinguishes from sibling 'consultar_meios_pagamento_trimestral' by specifying 'mensais' (monthly) rather than quarterly, though doesn't explicitly contrast with other siblings like transaction or terminal queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the parameter format example (YYYYMM for monthly data) and by specifying it's for 'dados mensais' (monthly data), which suggests when to use this vs. the quarterly sibling. However, it doesn't provide explicit guidance on when to choose this tool over alternatives like 'consultar_transacoes_cartoes' or 'consultar_taxas_desconto', nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals this is a query/read operation (implied by 'consulta') and specifies the required parameter format, but doesn't disclose other important behavioral traits like whether this tool requires authentication, has rate limits, returns paginated results, or what the output structure looks like. The description adds some value but leaves significant behavioral aspects undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with just two sentences. The first sentence states the purpose, and the second provides crucial parameter format guidance with a clear example. Every word earns its place, and the information is front-loaded with the most important details first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a query tool with 4 parameters, 100% schema coverage, but no annotations and no output schema, the description is moderately complete. It covers the core purpose and critical parameter format, but lacks information about authentication requirements, rate limits, pagination behavior (though 'top' and 'skip' parameters suggest pagination), and output structure. The description should ideally address more of these behavioral aspects given the absence of annotations and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description adds specific format guidance for the 'trimestre' parameter ('Use o formato YYYYQ') and provides an example, which adds value beyond the schema. However, it doesn't provide additional semantic context for the other parameters beyond what's already in their schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Consulta dados trimestrais sobre operações com cartões de pagamento e transferências de crédito' (Query quarterly data about payment card operations and credit transfers). This specifies both the verb (query/consulta) and resource (quarterly payment card and credit transfer data). However, it doesn't explicitly differentiate from sibling tools like 'consultar_meios_pagamento_mensal' beyond the quarterly vs monthly distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context by specifying the required parameter format ('Use o formato YYYYQ para o parâmetro trimestre'), which implies this tool is specifically for quarterly data. However, it doesn't explicitly state when to use this tool versus alternatives like the monthly version or other payment-related tools, nor does it provide exclusion criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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