Dados B3

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

With no annotations, the description carries the full burden of behavioral disclosure. It discloses that the output is in JSON ('em JSON'), that it is free ('Gratuito'), and provides important methodological nuances (e.g., different profit bases for margins and ROE). This adds valuable context beyond a simple definition, though it does not explicitly state whether the tool is read-only or describe all return contents.

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 and every phrase earns its place: the first sentence defines the tool's content, and the second provides a critical practical caveat for correct usage. It is well-structured, front-loaded, and free of redundant 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 that the tool is a parameterless reference dictionary, the description provides sufficient context: it explains what the JSON contains, mentions a key caveat for correct use, and notes the cost. It does not enumerate all indicators, but that is not essential for this type of tool, and the description is complete enough for an agent to understand its purpose.

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 tool has zero parameters, and schema coverage is 100% vacuously. The baseline for 0 parameters is 4, and the description does not need to explain parameter behavior. It provides no parameter-related information, which is appropriate for a parameterless reference tool.

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 that the tool provides indicator methodology in JSON format, including formula, CVM accounts, and the profit base for each indicator. It gives a specific example (margem_liquida vs roe) to illustrate its purpose, though it does not explicitly distinguish itself from the sibling tool 'metodologia'.

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 the tool is useful for correctly comparing indicators ('IMPORTANTE para comparar corretamente'), but it does not explicitly state when to use this tool versus alternatives like 'metodologia' or other sibling tools. There is no clear when-to-use or when-not-to-use guidance.

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, and the description adds behavioral context by noting that WEGE3 is free while other tickers require chave_api. It lists the response contents but does not disclose whether the operation is read-only, rate limits, or error behavior. This is adequate for a simple read endpoint but lacks broader behavioral detail.

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: the first lists the tool's purpose and key output fields, the second covers the free/API-key distinction. No filler or redundant content.

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 annotations and output schema, the description covers the main purpose, output fields, and a key authentication requirement. It does not mention pagination, historical depth, or error handling, but for a straightforward data retrieval tool this is reasonably 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?

Schema description coverage is 0%, but the description explains the chave_api parameter by stating that only WEGE3 does not require it, and that a free or Pro key is used. The ticker parameter is self-evident from the name and is used in the example 'WEGE3', though its format is not formalized.

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 'Histórico de proventos em dinheiro (dividendos e JCP) de uma empresa da B3' which clearly identifies the tool as returning a history of cash dividends and JCP for a single Brazilian company. It lists specific fields (valor por ação, data de aprovação, data-com, preço) and adds metrics (resumo anual, dividend yield), distinguishing it from siblings like 'multiplos' or 'indicadores_anuais'.

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 usage condition: 'WEGE3 é gratuita; demais tickers exigem chave_api' – indicating when the API key is needed. However, it does not explicitly compare this tool to sibling tools or state when to prefer it over 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 carries the full burden. It discloses the auditable nature, source accounts, temporal options, and the free ticker, but omits details like authentication (chave_api), rate limits, or error behavior. The 'Q1-Q3 isolado' is a useful nuance.

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 succinct sentences, front-loaded with core content and no filler. Every phrase adds meaning.

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 tool has no output schema and no annotations, so the description should explain return format and all parameters. It covers the main data content and temporal options but leaves chave_api and response structure unclear. Adequate but with gaps.

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 0%, so the description must compensate. It clarifies ticker via WEGE3 and trimestral via 'Anual ou trimestral', but the chave_api parameter is completely unexplained. Overall, partial compensation only.

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 provides standardized financial accounts (revenue, EBIT, profit, etc.) with source CVM account references, making the purpose clear. It also notes annual/quarterly availability and a free ticker, but does not explicitly differentiate from sibling tools like indicadores_anuais or multiplos.

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?

No explicit when-to-use guidance or alternative comparisons. The mention of 'Anual ou trimestral' and 'WEGE3 gratuita' gives some usage context, but not enough to guide tool selection among 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?

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal an authentication requirement (chave_api for most tickers) and notes a free tier for WEGE3, which is useful context. However, it does not explicitly state that the operation is read-only, nor does it describe response format, potential errors, or data update frequency, leaving room for ambiguity.

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 highly concise, consisting of two sentences that pack essential information: the data series, indicators, date range, and access tiers. Every word contributes, with no fluff or repetition, and the most important details are 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?

Given the lack of output schema and annotations, the description covers the basic purpose, metrics, and time range, but omits return structure, quality flag details, and error handling. It is adequate for a straightforward data retrieval tool, but falls short of fully preparing the agent for invocation without needing additional assumptions.

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 schema provides no descriptions, and the description partially compensates by explaining the role of chave_api (required for non-WEGE3 tickers) and implying that ticker is the stock code. It does not elaborate on ticker format or constraints, but the essential condition for the API key is clearly communicated, adding value beyond the bare 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 that the tool provides an annual series of specific financial indicators (ROIC, ROE, margins, growth, net debt/EBITDA) for a B3-listed company, which distinguishes it from sibling tools like 'multiplos' or 'saude'. However, it lacks an explicit verb like 'returns' or 'lists', using the noun phrase 'Série anual' instead, which makes it slightly less direct but still 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 gives access conditions (WEGE3 free, others require chave_api) but does not provide any guidance on when to use this tool over its siblings or when it would be inappropriate. No alternatives or exclusion criteria are mentioned, so the agent is left without context on tool selection.

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 the full burden. It discloses that the tool is free, requires no key, and notes that tickers are included only when resolved. This adds useful behavioral context beyond a mere verb, though it does not mention other traits like sorting or rate limits.

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 a single concise sentence that front-loads the main action and includes essential details (count, fields, free/no-key) without any unnecessary words. Every word 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?

For a zero-parameter, no-annotation, no-output-schema tool, the description is complete. It states what is returned (name, CNPJ, ticker), the scope (402 companies), and the access condition (free, no key). There is no additional complexity that would require more 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?

The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and it appropriately focuses on what the tool returns rather than input details.

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 action: listing Brazilian publicly traded companies, with specific output fields (name, CNPJ, ticker) and a scope (402 companies). It distinguishes itself from sibling tools, which focus on financial metrics and dictionaries, by being the only listing operation.

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 when to use the tool (to get the list of available companies) and provides context that it is free and requires no API key, but it does not explicitly state when to use it vs alternatives or any exclusion criteria. There is no mention of 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 the full burden. It discloses that the tool is free, lists pages without an argument, and returns full text with a name. This covers the main behavioral aspects, though it does not mention error handling or the exact return format.

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 tool's purpose. Every word earns its place, making it efficient and easy to parse.

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 tool with one optional parameter and no output schema, the description covers both usage modes and states the return type (text). It is complete enough for an agent to invoke correctly, though it omits minor details like invalid name 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 0% for the 'nome' parameter, but the description compensates by explaining that the parameter takes a name (e.g., 'roic') and returns the full text. This gives clear semantic meaning beyond the raw 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 function: it provides public methodology for indicators. It specifies two modes: listing pages without arguments and returning full text when a name is given (e.g., 'roic'). This distinguishes it from sibling tools that likely provide data values rather than methodology.

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 how to use the tool (with and without the 'nome' argument) but does not explicitly mention when to use it instead of alternatives or exclusions. It implies usage for methodology text, but no direct comparison to siblings is made.

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 provided, the description carries the full burden. It discloses a key behavioral trait: the price is taken from the first trading session after the actual balance sheet publication, preventing look-ahead bias. It also mentions WEGE3 being free, implying a pricing model for other tickers. This adds useful context beyond the schema, though it omits details like error handling or response structure.

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 a single, information-dense sentence. It front-loads the core purpose (point-in-time multiples), lists specific multiples, and adds methodology and pricing notes without wasted words. Excellent structure.

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 tool has no output schema and no annotations, so the description needs to cover return values and usage context. It explains the types of multiples and the point-in-time methodology, but it does not describe the output format, the meaning of chave_api, or any limitations beyond the free ticker. It is adequate but leaves gaps for a tool with this complexity.

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 0%, so the description must compensate. It only implies that 'ticker' is a stock code via the WEGE3 example, but it leaves 'chave_api' completely unexplained. The description adds minimal semantic value for parameters, especially the API key, which remains ambiguous.

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 provides point-in-time multiples (P/L, P/VP, EV/EBITDA annual; P/L TTM quarterly) and specifies the unique methodology (price after actual balance sheet publication, no future information leakage). This distinguishes it from sibling tools like indicadores_anuais or screener, which may offer current or unfiltered data.

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 when to use this tool: when point-in-time multiples without look-ahead bias are needed. It also notes WEGE3 is free, giving a pricing condition. However, it does not explicitly exclude alternatives or state when to prefer sibling tools, so it falls short of a 5.

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 provided, the description carries the full burden of behavioral disclosure. It implies a read-only status check but does not explicitly state that, nor does it mention any side effects, authentication, or rate limits. The information given is accurate but minimal.

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 short sentences, front-loading the core purpose and adding the 'free' note. Every word earns its place, 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?

For a simple no-parameter, no-output-schema tool, the description covers the basic functionality but lacks details about the return format or what 'contagens' refers to specifically. It is adequate for a status check but not fully complete for an agent to predict the output structure.

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 schema has zero parameters, so schema description coverage is 100%. Per rubric, a baseline of 4 is applied for 0-parameter tools. The description adds nothing about parameters because none exist, which is acceptable.

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 provides current database coverage counts and last ingestion timestamp. It identifies a specific resource (database health) and is distinct from sibling tools focused on financial data. However, it lacks an explicit verb like 'get' or 'list', so it doesn't fully meet the 5-level criterion.

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. It does not mention alternatives, prerequisites, or typical use cases. The only additional note is that it is 'free', which is not a usage guideline.

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 the full behavioral burden. It discloses important traits: default year behavior ('Sem ano usa o último de cada empresa'), data qualification ('Só valores SEM flag entram'), and authentication requirement ('Requer chave_api'). It also explains the indicator suffix convention. However, it does not describe output format or potential errors, but these are not strictly required for a filter 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?

The description is reasonably concise but packs a lot of information into a single sentence plus embedded notes. It front-loads the main action and uses an example to clarify the filter format. It is not overly verbose, but the long list of indicators and suffix rules makes it denser than necessary. Still, it earns a 4 for clarity within its length.

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 the core filtering logic, parameter semantics, and authentication, but it omits the output format (no output schema is provided). Users are not told what the tool returns (e.g., a list with which fields), which is a notable gap for a screening tool. Given the moderate complexity and lack of output schema, a score of 3 is appropriate.

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?

Despite 0% schema description coverage, the description compensates by explaining the `filtros` dict with an example, listing valid indicator keys, defining the _min/_max suffix convention, and clarifying the behavior of `ano`. It also mentions `chave_api` as a requirement. This provides substantial meaning beyond the bare schema. It falls short of a 5 only because it does not detail value formats or edge cases for each indicator.

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 function: 'Filtra as 402 empresas por faixas de indicadores' (Filters the 402 companies by indicator ranges). It specifies the resource (companies), action (filter), and scope (402 companies, indicator ranges). However, it does not explicitly differentiate from sibling tools, which lowers the score.

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 usage conditions (e.g., 'Sem ano usa o último de cada empresa', 'Só valores SEM flag entram', 'Requer chave_api') but does not state when to prefer this tool over sibling tools. No alternatives or exclusion criteria are mentioned. Thus, there is no guidance for tool selection.

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