Dados B3

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

No annotations are provided, so the description carries the full behavioral burden — and it excels: it discloses that the sampling is deterministic and reproducible ('a mesma semente devolve sempre os mesmos casos, então seu resultado é reproduzível por terceiros'), that the sample is randomly drawn, and that the tool is free with no API key ('Gratuito, sem chave'). These are exactly the behavioral traits an agent needs to know and could not infer from the schema or annotations.

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 dense (roughly 350 words) but well-structured and front-loaded — the core purpose comes first, followed by methodology, case contents, verification steps, and reporting rules. Every block earns its place, especially the audit-integrity rules that constrain agent behavior. It is slightly long in the operational verification section (the dfp_cia_aberta_<EXERCICIO>.zip download and filtering details), which borders on over-specification, but it is scannable and purposeful.

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 2-parameter tool with no annotations and no output schema, the description is remarkably complete. It effectively supplies a de facto return contract by enumerating what each case contains (empresa, CD_CVM, exercício, indicador, valor publicado, fórmula, conta CVM), explains the required parameter, gives verification workflow, sets behavioral rules, and even points to the issue tracker for bugs. Nothing an agent needs to invoke it correctly is left to guesswork.

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 thoroughly explains the required parameter 'semente' — what it is (any integer), the security constraint (don't accept suggestions), and its behavioral implication (determinism). The optional 'n' (sample size, default 25) receives no explicit explanation, but it is a simple integer with a sensible default visible in the schema, and the text implicitly references sample sizes ('7 divergências em 100'). Strong compensation for the hard parameter, slightly light on 'n'.

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 leads with a specific verb and resource scope: 'AUDITE ESTA BASE. Sorteia casos e devolve o que você precisa para refazer cada número contra o arquivo ORIGINAL da CVM'. This makes crystal clear it is a sampling-audit tool that cross-checks against original CVM filings, not a fetch/query tool. It is also self-evidently distinct from all 13 siblings (dividendos, fatos_contabeis, fii, etc.), which are data-retrieval tools, so an agent cannot confuse them.

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 strong contextual guidance on the intended scenario ('AUDITE ESTA BASE') and rich methodological rules — choose your own seed, never accept someone else's suggestion, publish the denominator and not just '7 divergências', and show the account when claiming an error. However, it stops short of explicitly naming sibling alternatives or stating when NOT to use this tool versus the regular data tools; the distinction is implied rather than spelled out.

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 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?

No annotations are provided, so the description carries the full burden. It discloses data-source behavior (DFP annual vs ITR quarterly granularity with overlapping history), scope limitations (stocks only; FII not supported in this format), and authentication requirements (chave_api needed except for WEGE3). It does not cover error behavior, invalid-key handling, or output structure, but the core behavioral traits an agent needs are disclosed.

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 compact paragraphs, each with a distinct job: core functionality and granularity, scope/exclusion with sibling routing, and access requirements. The key purpose is front-loaded and every sentence carries information — no filler or repetition of schema fields.

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 3-parameter tool with no annotations and no output schema, the description covers what data is returned, source traceability, granularity semantics, scope restrictions, and authentication conditions. Minor gaps remain — exact return format and error behavior — but nothing that would prevent correct selection and invocation.

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 for the schema. It fully explains `trimestral` with the concrete outcome of each value (annual DFP vs isolated ITR Q1-Q3) and explains when `chave_api` is required (all tickers except WEGE3). `ticker` is only implied as a stock code rather than explicitly described, so the compensation is strong but not complete.

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 identifies a specific resource and output: standardized accounting accounts for a stock (receita, EBIT, lucro, PL, dívida, caixa) with the originating CVM account for each figure, making the data auditable end-to-end. It also distinguishes itself from siblings by stating 'Só ações' and explicitly routing FII queries to the `fii` tool. The verb is implied rather than explicit ('returns/provides'), but the intent is 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?

Gives explicit when-to-use guidance: stocks only, with FII explicitly excluded and routed to the sibling `fii` tool ('o que existe é o informe mensal, exposto por `fii`'). It also explains the `trimestral` choice as a granularity decision (False → annual DFP, True → ITR Q1-Q3, both covering the same history) and the access condition (WEGE3 free, others require chave_api). Nothing is left to inference.

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 transparency burden. It discloses the data included and the authentication requirement (chave_api for non-MXRF11 funds). It does not mention rate limits or explicitly state read-only behavior, but the listed content and key requirement provide substantial transparency for a data-retrieval 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 concise and well-structured: two sentences that start with a clear purpose and then list specific data items, followed by a crucial access note. Every clause adds value with 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 the tool has only two parameters, no output schema, and no annotations, the description provides a solid overview: purpose, data contents, and access conditions. It lacks explicit error handling or output format details, and does not distinguish itself from overlapping sibling tools, leaving some gaps, 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?

Schema coverage is 0%, so the description must compensate. It does so by explaining that the tool requires a ticker (implicitly via MXRF11 example) and that chave_api is required for funds other than MXRF11. This gives meaningful context to both parameters 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 the tool provides details of a real estate fund (FII) and enumerates specific data points (cadastro, último informe, historical P/VP series, current 12m DY, and last dividends paid). This makes the purpose specific and valuable, but it does not explicitly differentiate from sibling tools like fiis_ranking or dividendos.

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 by indicating it is for individual FII details and explains that only MXRF11 is open for free testing while others require an API key. However, it does not provide explicit when-to-use or when-not-to-use guidance compared to alternatives, such as directing users to fiis_ranking for rankings or dividendos for broader dividend queries.

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 adds useful context beyond basic ranking: data sources ('informe mensal da CVM + COTAHIST'), data filtering ('só valores limpos (sem flag) e fundos líquidos'), authentication requirement ('Requer chave_api'), and a note about free access to a specific ticker ('MXRF11 é aberto para degustação'). This gives the agent meaningful insight into how the tool behaves.

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 and front-loaded with the core purpose (ranking FIIs). Each clause adds distinct information: criteria, data sources, quality filters, and authentication. There is no redundant filler, though some domain abbreviations (P/VP, DY) may be less accessible to general audiences.

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 simplicity of the tool (one param, no output schema) and lack of annotations, the description provides a solid overview of what the tool returns (rankings and medians) and its data provenance. However, it omits practical details such as result limits, default sorting, output format, or whether all FIIs are included, leaving some ambiguities for the agent.

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 only shows a parameter named 'chave_api' with no description (schema coverage 0%). The description compensates by explaining that this is an API key, mentions free and Pro tiers, and states it is required ('Requer chave_api'). This adds essential meaning beyond the raw schema definition.

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 with a specific verb and resource: 'Ranking dos fundos imobiliários (FIIs)' and details the ranking criteria (most discounted by P/VP, highest yield by DY 12m, and medians per segment). It distinguishes itself from siblings like 'screener_fiis' by focusing on rankings and aggregate statistics rather than screening.

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 intended use is implied through the description (it provides rankings for FIIs), but there is no explicit guidance on when to choose this tool over alternatives like 'screener_fiis' or 'fii'. No exclusions or alternative recommendations are provided, though the context is clear enough for an agent to infer basic usage.

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 behavioral disclosure burden and handles it well: it discloses the data scope (2010–today), the indicator set, the FII exclusion behavior, the bank/insurer limitation (no ROIC/EBITDA due to their chart of accounts), and the API-key requirement. It stops short of describing the return format or what 'flags de qualidade' mean, but the core behavioral traits are transparent.

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 short paragraphs, each with a distinct job: what the tool returns, exclusions and alternative routing, and auth/pricing. Every sentence earns its place and the core purpose is front-loaded in the first sentence. No filler or repetition.

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 2-parameter tool with no annotations and no output schema, the description is nearly complete: it covers purpose, valid inputs, exclusions, alternatives, and auth requirements. The only minor gaps are the undefined 'flags de qualidade' and the lack of a return-structure sketch, though the enumerated metric list already gives an agent a solid expectation of the response.

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 fully compensates: it defines the valid `ticker` space (B3 stocks only, not FIIs ending in 11, banks/insurers allowed with caveats) and specifies when `chave_api` is required (all tickers except WEGE3) and which tiers work (free or Pro). This is exactly the parameter-level meaning the schema fails to provide.

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 a specific verb-resource relationship: it provides an annual series (2010–today) of ROIC, ROE, margins, growth, and net debt/EBITDA for a single B3 stock, with quality flags. It distinguishes itself from siblings by explicitly excluding FII tickers and routing them to `fii`, and by noting banks/insurers are included with limitations.

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 explicit when-to-use/when-not-to-use guidance: FII tickers ending in 11 (e.g., MXRF11) must NOT be queried here and should use `fii` instead, with the rationale that FIIs have P/VP, DY, and vacancy rather than ROIC/EBITDA. It also states the prerequisite that WEGE3 is free while all other tickers require chave_api.

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 meaningful behavior beyond the basic function: the count is returned in the response rather than hardcoded, tickers appear only when resolved, FIIs are excluded, and no authentication key is needed. This is strong behavioral context for a zero-parameter 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 main action and scope are front-loaded, and the exclusion note is efficient. The meta-explanation about why the count is not written in the description is slightly verbose, but it does serve a purpose for AI clients reading the description.

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 parameterless listing tool with no output schema, the description is complete: it covers scope, returned fields, response count behavior, exclusions, sibling alternatives, and access requirements. Nothing essential for correct invocation 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?

There are zero parameters, so the baseline is 4. The description adds useful output-field semantics (nome, CNPJ, ticker) but there are no parameters for it to document.

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?

States a specific verb and resource: 'Lista as companhias abertas brasileiras (AÇÕES)', with the returned fields named (nome, CNPJ, ticker). It explicitly separates this tool from FII tools, so an agent can distinguish it from fiis_ranking and fii without opening schemas.

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?

Gives explicit when-to-use guidance: only stocks, and explicitly excludes real estate funds. It names the alternatives for FII use: fiis_ranking for the list and fii for a single fund. It also states access requirements upfront: 'Gratuito, sem chave'.

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, the description carries the full burden of behavioral disclosure. It discloses the key methodology (no look-ahead bias, price after actual publication) and the API key requirement. However, it does not describe the response format or behavior on errors, which is a minor gap given no output schema exists.

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 three sentences with no wasted words. It front-loads the core purpose and methodology, then adds usage nuance about scope and pricing. The line 'Só ações' ('only stocks') slightly repeats the initial 'de uma AÇÃO', but it reinforces the exclusion and fits naturally.

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 multiples provided, the pricing rule, the restriction to stocks, the alternative tool, and the API key condition. Since there is no output schema, it could be more explicit about the return format, but for an agent deciding whether and how to call the tool, the information is sufficient.

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 only `ticker` and `chave_api` with 0% coverage, so the description must compensate. It adds meaning by giving a concrete example (WEGE3) and explaining that `chave_api` is required for all tickers except WEGE3, which clarifies the role of both parameters beyond the bare schema fields.

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 explicitly defines the tool's function: it provides point-in-time multiples (P/L, P/VP, EV/EBITDA annual; P/L TTM quarterly) for stocks, with a precise pricing rule based on the first trading session after the actual earnings release. It also clearly distinguishes itself from the sibling `fii` tool for real estate funds, making the resource and scope 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?

It explicitly states 'Só ações' (only stocks) and directs users to the `fii` sibling for real estate fund P/VP, providing a clear alternative. It also gives a concrete usage condition: WEGE3 is free while all other tickers require an API key, helping an agent decide when to invoke this tool.

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 burden and does well: it explains the side-by-side display, the fact that restatements are recorded rather than silently corrected, and gives a free-use example. It does not cover error handling or return format, but the core behavior is transparent.

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 compact, front-loaded two-sentence summary. Every part adds value: purpose, output details, differentiator, and an example. No redundant or filler 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?

Even without an output schema, the description gives a good sense of what the result contains (ano, conta, valores, variação). It lacks information on possible empty results or authentication nuances, but for a simple tool with one required parameter, it is largely adequate.

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 description clarifies that the tool works for a company ('de uma empresa') and provides WEGE3 as an example ticker, which helps for the required 'ticker' parameter. However, the optional 'chave_api' parameter is not mentioned at all, and schema coverage is 0%, so the description only partially compensates.

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: it shows republished balance sheets with side-by-side comparisons of original and restated values. It includes specific fields (year, account, old vs new, variation) and a concrete example (WEGE3), making it distinct from siblings like fatos_contabeis.

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 a specific company's restatements but does not explicitly state when to use this tool over alternatives. The 'differential' line hints at a unique benefit, but no direct comparison or exclusion is provided.

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?

No annotations are provided, so the description must fully disclose behavior. It does mention that banks do not have Piotroski scores and that WEGE3 is free, which is useful context. However, it does not clarify return format, authentication requirements, any side effects, or what happens if the account is not open. The 'com a conta aberta' prerequisite is vague and unexplained.

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 concise at three sentences and front-loads the main purpose. Some details like 'cada um dos 9 critérios auditável' are useful but could be trimmed; overall it is well-organized and avoids 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?

The tool has no output schema and only two parameters, so the description is the main source of context. It explains the two scoring methodologies and includes exceptions, which is helpful. However, it lacks parameter semantics, auth details, and explicit usage guidance, leaving noticeable gaps for an agent to invoke it correctly.

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, but it only implicitly mentions the ticker by giving 'WEGE3' as an example. It does not explain the format or meaning of the 'ticker' parameter, nor does it mention the 'chave_api' parameter at all. This leaves the agent with insufficient information to correctly populate both arguments.

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 fundamental scores (Piotroski F-Score and Graham's criterion), mentioning specific details like the 0-9 range and the P/L × P/VP ≤ 22.5 threshold. It distinguishes itself from sibling tools by naming these specific scoring methodologies, though it lacks an explicit verb like 'calculates' or 'returns'.

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 guidance is given on when to use this tool versus alternatives. The phrase 'com a conta aberta' implies a prerequisite (open account) but does not explain it, and there is no mention of situations to avoid or sibling comparisons. The only concrete usage hint is that WEGE3 is free, but that does not help an agent decide when to invoke this tool.

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?

There are no annotations, so the description carries the full burden. It discloses several non-obvious behaviors: only unflagged values enter, missing `ano` falls back to the latest per company, and an API key is required. It stops short of describing output shape or error/rate-limit behavior, so it is strong but not exhaustive.

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 dense and front-loaded with no filler; every clause adds useful information. However, it is a long run-on sentence with many clauses and semicolons, which slightly hurts scanability.

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 and no annotations, the description covers purpose, filter syntax, accepted indicators, default year behavior, flag filtering, and authentication. It does not describe the return shape or failure modes, which would make it fully complete for an agent planning to consume the result.

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 property descriptions and `filtros` is a free-form object, so the description compensates fully. It gives a concrete dict example, enumerates all supported indicator names, explains the `_min/_max` suffixes, and clarifies the `chave_api` requirement, giving meaningful guidance for all three 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 a specific verb and resource: 'Filtra as AÇÕES do universo por faixas de indicadores'. It explicitly differentiates from the sibling `screener_fiis` by noting this is 'só ações' and that real estate funds should use the other tool, so an agent can distinguish them immediately.

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?

It gives explicit when-to-use guidance with an alternative: use this for stocks, use `screener_fiis` for real estate funds, whose filters are different. It also clarifies the behavior when `ano` is omitted and that only unflagged values are included, leaving little ambiguity about when the tool applies.

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 responsibility and covers key behaviors: inclusive bounds, exact/case-insensitive segment matching, a liquidity floor, exclusion of flagged values, ascending P/VP sorting, a 100-record cap, and API-key authorization. This is rich behavioral disclosure.

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 tight paragraph where every sentence earns its place: it gives a mini-example, enumerates valid filters, notes data-quality constraints, ordering, limit, and auth. No filler or repetition.

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 having no output schema, the description explains filtering criteria, sorting, maximum returned records, data-quality filtering, and required key, which is enough to understand the tool's behavior. The nested filtros object is fully demystified, so nothing critical 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?

Schema coverage is 0% and the only parameter property is an unconstrained object with additionalProperties true. The description compensates by listing valid keys (pvp_min, pvp_max, dy_min, dy_max, segmento, cotistas_min) and their semantics, including inclusivity and matching rules, plus the chave_api requirement.

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 opens with 'Filtra os FIIs por faixas,' using a specific verb and resource, and immediately distinguishes this from the stock-screener sibling by scoping to FIIs. It further specifies ordering and output cap, making the tool's role unmistakable.

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 clearly establishes this tool is for filtering FIIs by range-based criteria ('por faixas') and gives the exact accepted keys. It does not explicitly name alternatives or exclusion scenarios, but the FII-specific scope provides clear enough context.

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