ab-ibge-mcp-server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v2.2.0
Disambiguation2/5
Several tools overlap significantly: ibge_populacao_censo2022, ibge_populacao_municipio, and ibge_populacao_estados all provide census population data with different granularities; ibge_ipca duplicates part of ibge_indicador_economico. These overlaps create ambiguity about which tool to use for a given query.
Naming Consistency3/5
All tools share the ibge_ prefix, but naming conventions are mixed: some use verb_noun patterns (listar, buscar, obter, comparar) while others use bare noun phrases (populacao_censo2022, pib_estados, densidade_demografica). This inconsistency makes the API less predictable, though still readable.
Tool Count2/5
With 32 tools, the server is heavy and exceeds the typical well-scoped range. Many tools could be consolidated (e.g., population queries into one tool with a level parameter, IPCA into economic indicators), reducing redundancy without losing functionality.
Completeness4/5
The server covers a broad range of IBGE data: locations, SIDRA queries, population, PIB, CNAE, country indicators, names, and news. It provides list, search, detail, and comparison operations, with few obvious gaps for a read-only statistical data API.
Average 4.3/5 across 32 of 32 tools scored. Lowest: 3.4/5.
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
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behaviors, so the description has a lower burden. It adds context about TCU usage and annual updates, but doesn't disclose response format, default behavior when optional params are omitted, or error handling. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear first sentence and a bulleted parameter list. It is concise and front-loaded with purpose, though the final example sentence adds a bit of redundancy without much new information.
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?
The description covers purpose, scope, parameters, and usage guidance, but the schema contradiction regarding localidade creates a critical completeness gap. An agent cannot reliably invoke the tool based on this description, so it falls short of being complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds examples and explanation, but it explicitly states localidade can be an IBGE code while the input schema restricts it to an enum of 'BR' and 'estados'. This direct contradiction misleads the agent and will likely cause invalid calls, making the description worse than merely relying on the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries annual population estimates for inter-census years (2001-2024+), distinguishing it from sibling tools like the 2022 census. The TCU context and annual update cadence reinforce a specific, well-scoped purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use para dados mais recentes que o Censo 2022 ou para anos intermediários', providing clear context on when to choose this tool. It doesn't name alternative tools or exclusions, but the scope is defined well enough for an agent to make an informed selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds valuable behavioral context by specifying that the tool returns Censo data with frequency organized by decade, covers data since 1930, and clarifies the default for localidade. It does not mention potential edge cases or return format details, but for this tool the added context is sufficient.
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 well-structured with distinct sections for arguments, return value, and an example. It is concise, with no redundant or filler content. The action is front-loaded in the first sentence, and each subsequent detail earns its place by clarifying parameter meanings and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although there is no output schema, the description adequately describes the return value as Censo data with frequency by period (decade) and provides an example. It could be more explicit about the exact structure of the response (e.g., list of decades with counts), but for this straightforward tool, the provided information is sufficient for an agent to understand what the tool does and what it returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for all three parameters (100% coverage). The description adds value beyond the schema by including concrete examples for nome, stating the default for localidade ('BR'), and clarifying that sexo can be null to represent both genders, which is not apparent from the enum alone. This extra semantic detail helps the agent select and format parameter values correctly.
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 a specific action: returning the frequency of a given name in Brazil by decade since 1930. It also provides a concrete example question that the tool answers. However, it does not explicitly distinguish this tool from its sibling ibge_nomes_ranking, which likely serves a related but distinct purpose.
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 an example query ('Quantas pessoas se chamam João no Brasil?') that implies the intended use case, but it does not explicitly state when to use this tool over alternatives like ibge_nomes_ranking. There are no clear when-to-use or when-not-to-use guidelines, leaving the agent to infer appropriateness from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds context about the data sources (Censo 2022 and territorial area), the output fields (population, area, density), and sorting order, which goes beyond the annotations and helps set expectations.
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 very concise, consisting of one introductory sentence, a simple Args section, and a return statement. Every sentence provides necessary information without redundancy or filler, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 adequately explains what it returns (population, area, density, sorted by density) and the calculation basis. It lacks explicit output format details, but the tool's simplicity and the described return fields are sufficient for an agent to understand the result.
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 already describes uf_id as 'ID do estado. Omita para todos.' The description repeats this in slightly different words ('Omita para ranking completo') and notes the type is number, which is already in the schema. Since schema coverage is 100%, the description adds minimal extra meaning, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool calculates demographic density (hab/km²) by combining Censo 2022 and territorial area from IBGE. This is a specific verb+resource that distinguishes it from sibling population tools like ibge_populacao_censo2022 and ibge_populacao_estados, which only provide population counts.
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 for density calculations and notes that omitting uf_id gives a complete ranking, but it does not explicitly state when to use this tool over alternatives like ibge_populacao_censo2022 or ibge_area_territorial. Since siblings exist but no exclusions or alternatives are mentioned, usage context is only implied.
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that it returns a 'série histórica', but provides no further behavioral details such as output structure, limits, or error conditions. This meets the baseline but does not go beyond.
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 compact and well-organized: a single opening sentence, a clear list of arguments with valid values, and two practical examples. Every sentence earns its place, and the structure front-loads the main purpose before presenting details.
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?
The description thoroughly explains the input parameters and gives examples, but it does not describe the return format or any potential errors, which is a gap given there is no output schema. Additionally, it does not clarify the relationship to overlapping sibling tools like ibge_ipca, leaving some ambiguity about when to choose this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes 'periodos' only as a string, but the description fully documents the accepted formats ('ultimo', 'last', 'ultimos6', 'ultimos12', and intervals like '202401-202412') and provides concrete examples. Since schema description coverage is 0%, the description fully compensates and adds essential meaning beyond the enum values already present for 'indicador'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Busca indicadores econômicos e sociais com série histórica' (searches economic and social indicators with historical series), and lists the exact indicator values and period formats. This is a specific verb+resource that effectively distinguishes it from a generic search or listing tool.
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 includes two usage examples (e.g., 'Inflação 2024' and 'Desemprego atual') that imply when to use the tool. However, it does not explicitly state when to prefer this tool over overlapping sibling tools like ibge_ipca, nor does it give 'when-not' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety profile is covered. The description adds transparency about the return shape ('Retorna: Array com nome, códigos ISO-3166-1-ALPHA-2/3, região e sub-região') and data fields, which goes beyond annotations. The claim about filtering by region is not reflected in the schema, but this is more of a parameter/functionality mismatch than a behavioral transparency issue.
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 well-structured with bold labels ('Uso', 'Retorna') and is concise overall. It avoids unnecessary detail but does repeat 'Retorna' in two places, which is slightly redundant. Nevertheless, every section earns its place and information is front-loaded with the main purpose in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter) and rich annotations, the description covers the essential return values and data fields. It lacks pagination/limit info and the 'filtrar por região' claim is unsupported, but for a list endpoint, it is sufficiently complete. An output schema is absent, so the description's return details are valuable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single parameter `orderBy`, providing a clear description. However, the tool description introduces 'filtrar por região' which is not supported by any schema parameter, potentially misleading the agent to expect a region filter. This actively harms parameter semantics by suggesting functionality that does not exist, so a score below baseline is warranted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retorna lista de todos os países do mundo com informações básicas' specifying the verb and resource, and lists included data (name, ISO code, region). It distinguishes from sibling tools like ibge_listar_estados and ibge_listar_municipios by targeting countries specifically. A minor caveat is the unsupported 'filtrar por região' claim, but the core purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear 'Uso' section: 'Para obter lista completa de países ou filtrar por região.' This establishes a clear context for when to use the tool. However, it does not explicitly name alternatives for specific tasks (e.g., retrieving a single country), so it lacks explicit exclusions, which keeps it at a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds the exact data fields returned (area, geography, languages, capital, currency, history), which is useful behavioral context beyond annotations.
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 well-structured with clear sections for parameters and return values, and it front-loads the core functionality. Some repetition with the schema exists, but it is concise and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only lookup tool with one parameter, the description fully covers purpose, parameter, and return data. Annotations cover safety, schema covers parameter validation, and the description lists return fields since there is no 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 coverage is 100% for the single parameter, and the description repeats the schema info with examples and uppercase requirement. It does not add new semantics beyond what the schema already specifies, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves complete information about a specific country using an ISO-3166-1-ALPHA-2 code. It includes the verb (retorna), resource (país), and scope (informações completas, specific country), and implicitly distinguishes from siblings like 'buscar_pais' by emphasizing completeness.
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 implied usage is for obtaining detailed country data when the ISO code is known. However, it does not explicitly mention when to use this tool instead of alternatives like ibge_buscar_pais or ibge_listar_paises, so guidance is only implicit.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the return value ('Retorna: população residente total pelo Censo 2022'), but does not disclose potential error behavior, rate limits, or other behavioral nuances. This is a modest addition beyond annotations.
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 structured with a clear one-line purpose statement, a compact Args list, and a return value line. Every sentence and detail earns its place, with no redundant or extraneous text. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 params, 1 required, no output schema), the description is nearly complete. It explains all parameter options and the expected return value. It could be improved by mentioning error handling or behavior for invalid codes, but for a straightforward read-only query the coverage is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers all parameters (100% coverage), but the description goes further by explaining the semantic distinctions between 'nivel' values (e.g., 'BR'=Brasil, 'ESTADOS'=por estado) and specifying cross-parameter dependencies ('municipio' requer municipio_id). This adds meaningful value over the bare schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 de população do Censo Demográfico 2022' (queries population data from the 2022 Demographic Census). It uses a specific verb ('Consulta') and resource ('população do Censo Demográfico 2022'), and distinguishes itself from sibling tools by specifying the 2022 Census as the data source.
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 clear guidance on how to use the 'nivel' parameter, including when specific IDs are required (e.g., 'municipio' requires municipio_id, 'estado_municipios' requires estado_id). However, it does not mention when to prefer this tool over alternatives like ibge_populacao_estados or ibge_estimativas_populacionais, nor does it give any exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
As annotations já declaram readOnlyHint=true, idempotentHint=true e destructiveHint=false, cobrindo a segurança da operação. A descrição complementa ao especificar que exibe 'os valores mais recentes' e retorna 'ranking dos países', fornecendo contexto sobre o comportamento da saída sem contradizer as annotations. Não há menção a limites ou necessidade de autenticação, mas o bar é menor com annotations.
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?
A descrição é bem estruturada e concisa: uma frase de propósito, depois seções de parâmetros, retorno e exemplo. Cada parte é necessária e a informação essencial está na frente. O exemplo com a lista de países da América do Sul é instrutivo sem ser excessivo.
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?
Sem output schema, a descrição diz apenas que retorna um 'ranking dos países com o valor mais recente do indicador', o que é vago sobre a estrutura exata da resposta (ex: campos, ordenação, como são tratados dados ausentes). Para uma ferramenta com apenas 2 parâmetros e sem schema de saída, essa falta de detalhe sobre o formato de retorno prejudica a completude. O exemplo ajuda, mas não resolve a ambiguidade.
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?
A cobertura do schema é 100% e as descrições dos parâmetros no schema já explicam o formato (ex: 'separados por |') e dão exemplos ('BR|AR|US|PT'). A descrição repete essas informações e adiciona um exemplo com vários países e um ID específico, mas não traz semântica nova além do que o schema já oferece. O exemplo é útil, mas não eleva a nota acima do baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
A descrição é específica e clara: 'Compara um indicador específico entre vários países, mostrando os valores mais recentes' indica verbo, recurso e escopo, distinguindo-se de irmãos como ibge_indicadores_pais (focado em um país) e ibge_listar_indicadores_paises (lista de indicadores). O uso de 'entre vários países' e 'rankings internacionais' reforça a diferenciação.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
A frase 'Útil para análises comparativas e rankings internacionais' fornece contexto claro de quando usar a ferramenta, mas não menciona explicitamente alternativas ou casos de não-uso, como ferramentas para análise de um único país. Faltam exclusões ou comparações diretas com irmãos.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, reducing the burden on the description. The description adds the specific census year and reference IDs, but no additional behavioral details such as return format or error handling. No contradiction with annotations.
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 compact and front-loaded with the main purpose. The block of capital IDs is reference material that takes up significant space but is useful for quick validation. No redundant or vague sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with rich annotations and a complete schema, the description adequately explains what the tool does, the census source, and how to obtain the required ID. It does not describe the return value, but with no output schema and low complexity, this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage with a clear description of municipio_id. The description reinforces the 7-digit format and, more valuably, lists concrete example IDs for capitals, which helps the agent construct valid inputs without external lookup.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with the specific verb 'Consulta' and resource 'população de um município', clearly scoped to the Censo Demográfico 2022. This distinguishes it from sibling tools like ibge_populacao_estados (state-level) and ibge_populacao_censo2022 (general census query).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool (municipality population from 2022 Census) and provides a pointer to ibge_listar_municipios for obtaining the ID. It does not explicitly exclude alternatives like ibge_estimativas_populacionais, but the title and description make the intended use unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety. The description adds valuable behavioral context by enumerating all 21 sections and their letter codes, which helps the agent anticipate the returned data domain without needing to call the tool. It does not specify exact return format, but the annotation coverage lowers the bar, and this is a simple read-only list.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The first two sentences are concise and front-loaded, but the description then includes a long enumeration of all 21 sections with names. While informative, this duplicates what the tool likely returns and makes the description lengthy and less scannable. It could be shortened or moved to a more compact format, but it does provide quick reference value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should clarify return values. It states the tool returns the 21 sections with division counts and even lists the sections, giving a good sense of the data. However, it does not specify field names, structure, or whether pagination exists. For a simple read-only list tool, this is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 the input schema confirms no parameters exist. The description's mention of using the section letter to filter ibge_cnae_buscar indirectly explains that this tool outputs letters for use elsewhere, which is helpful but not necessary.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists the 21 CNAE sections with division counts, using a specific verb ('Lista') and resource ('seções da CNAE'). It also differentiates from sibling tools by explicitly mentioning that it can be used to discover the section letter for filtering ibge_cnae_buscar, making its purpose distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Use para ter uma visão geral da estrutura ou descobrir a letra de seção para filtrar ibge_cnae_buscar.' This indicates when to use the tool and how it relates to a sibling tool. It lacks explicit when-not-to-use instructions, but the context is clear enough for a simple list tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as a safe, idempotent read operation. The description adds useful behavioral context beyond annotations by stating that it returns a URL plus usage instructions, not the actual file. No contradictions with annotations.
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 well-organized with a clear summary, an 'Args' list, and concrete examples. Every sentence serves a purpose—no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since no output schema exists, the description appropriately explains the return type (URL + instructions). It covers use cases, parameters, and examples. It does not explicitly state that 'uf' is conditionally required for 'estado'/'municipios_de_estado', but the examples imply the relationship.
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% parameter coverage, so the baseline is 3. The description adds helpful examples relating 'tipo' to 'uf' and 'municipio_id', but it incorrectly states that 'svg' is the default formato while the schema declares default 'json'. This inconsistency undermines reliability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific action ('Retorna a URL para download') and a clear resource ('malha geográfica de estados ou municípios'). It distinguishes itself from sibling IBGE tools by focusing on geographic mesh URLs rather than listing codes or querying statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'criar mapas, calcular áreas, análise espacial, visualizações'. It does not explicitly name alternatives or when-not-to-use, but the purpose and scope are clear enough to guide selection among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safe read-only nature is covered. The description adds useful behavioral context by specifying the return fields (código IBGE, nome, UF, mesorregião) and scope ('todo o Brasil'), which are not available from annotations since there is no output schema.
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 concise and well-structured, leading with the main purpose followed by a short Args list and a Retorna line. Every sentence earns its place without unnecessary bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity, no output schema, and well-covered parameters, the description is complete: it explains the search behavior, parameters, and return values. The lack of pagination details is acceptable because 'todos os municípios encontrados' indicates exhaustive results.
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 both parameters. The description adds minor value by explicitly marking 'uf' as optional and stating it restricts the search, but it mostly repeats the schema information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Busca municípios em todo o Brasil pelo nome') with a clear resource (municípios) and scope (todo o Brasil). It differentiates from sibling tools like ibge_listar_municipios by emphasizing search-by-name rather than listing all municipalities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: search municipalities by name across all Brazil, optionally restricted by UF. However, it does not explicitly mention when to use an alternative tool or when not to use this one, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint and idempotentHint annotations, the description discloses that for classes/subclasses it returns 'as atividades incluídas' (included activities) and mentions the return of the complete hierarchy. This adds useful behavioral context without contradicting the annotations.
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 well-structured: a concise first sentence states the core purpose, followed by a clear 'Args:' section with examples and a 'Retorna:' section. Every sentence adds value, and the formatting is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential inputs and return elements, including the note about activities for classes/subclasses. However, with no output schema, it could be more explicit about the structure of the 'hierarquia completa' or error handling for invalid codes, but overall it is sufficient for a simple detail tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a description for 'codigo', but the tool description significantly enriches it by enumerating all accepted formats with examples (e.g., 'G', '47', '47.1', '4711-3', '4711-3/02'). This goes well beyond the schema's minimal description, clarifying exact string patterns and hierarchical levels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Retorna detalhes completos de um código CNAE' (returns complete details of a CNAE code), specifying the resource and scope. It distinguishes itself from siblings like ibge_cnae_buscar (search) and ibge_cnae_secoes (sections) by focusing on detailing any hierarchical level.
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 by stating it accepts section, division, group, class, or subclass codes, but it does not explicitly mention when to use this tool over alternatives or provide exclusions. No comparison with sibling tools is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds behavioral context by stating the output is 'séries temporais com valores anuais' and includes example indicator IDs with meanings, which helps the agent anticipate the response shape without an output schema.
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 well-organized with bold sections for parameters, return value, and examples. It is front-loaded with the main purpose and scannable bullets. Some redundancy exists between the initial 'Indicadores disponíveis' list and the later 'Exemplos de indicadores', but it remains focused.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only query tool with no output schema, the description adequately covers what is returned ('Séries temporais com valores anuais'), how to construct parameters, and where to find all indicator IDs. It does not cover error behavior or multi-country comparison scenarios, but those are not essential for this tool's core use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema documents both parameters; however, the description adds valuable examples ('BR', 'US') and a curated list of indicator IDs ('77823: PIB per capita', '77831: IDH') that go beyond the schema's descriptions and help select correct parameter values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Retorna séries históricas de um ou mais indicadores para um país específico', clearly stating the verb (retorna), resource (séries históricas de indicadores), and scope (país específico). This distinguishes it from sibling tools like ibge_listar_indicadores_paises and ibge_comparar_paises by focusing on fetching series for one country.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The final sentence explicitly directs users to ibge_listar_indicadores_paises for the full list of 34 indicators, providing an alternative for a related need. It also implicitly scopes usage to a single country via 'país específico', but does not explicitly mention when to use ibge_comparar_paises for multi-country comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by specifying the return fields (id, sigla, nome, região), the fixed set of 27 states, and the SIDRA-related use of the id, which goes beyond the structured metadata.
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 concise and well-structured: it opens with the primary purpose, then details the optional argument, and closes with the return format and downstream use. Every sentence contributes useful information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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 fully covers the behavior: it lists the exact states, the optional filter, and the returned fields. There is no missing context that would prevent correct invocation or interpretation of results.
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 already provides 100% coverage for regiao_id, including the same region mapping shown in the description. The description repeats the parameter details without adding new meaning, so it meets the baseline but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Lista todos os 27 estados do Brasil com códigos IBGE, siglas e regiões.' This clearly distinguishes it from sibling tools like ibge_listar_regioes and ibge_listar_municipios by stating the exact scope (27 states).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly establishes when to use the tool (to list Brazilian states) and includes an optional filter (regiao_id) with explicit region mappings. It does not explicitly name alternatives or exclusions, but the purpose and parameter guidance make the usage context unambiguous.
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?
Annotations already cover safety (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the description carries less burden. It adds the useful behavioral context that the tool returns IDs for downstream use, which is not in the annotations. However, it does not add deeper behavioral details like pagination or output format, so a score of 3 is appropriate.
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, focused sentence that immediately states the main function and purpose. It is front-loaded with the action 'Lista' and includes the essential detail about IDs and the consumer tool. No unnecessary words or repetition, making it highly concise and effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema, and straightforward listing behavior), the description is complete enough. It mentions the content (economic indicators), the deliverable (IDs), and the downstream usage. Annotations provide the safety profile. No significant information is missing for an agent to invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since this tool has zero parameters and the schema is empty (100% coverage), the description is not required to explain parameters. Per the baseline for 0-parameter tools, a score of 4 is given. The description adds context about the output (the IDs) which helps understand what the tool offers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists economic indicators available on this MCP server, with the specific verb 'lista' (lists) and resource 'indicadores econômicos'. It also explicitly differentiates from sibling listing tools by mentioning the IDs are for use in ibge_indicador_economico, which distinguishes it from other list tools like ibge_listar_estados.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context by stating the returned IDs are for use in ibge_indicador_economico, telling the agent when to invoke this tool. It does not explicitly mention when not to use it or alternatives, but the reference to the consumer tool gives an implicit usage guideline. This meets the 'clear context, no exclusions' level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds return fields (id, nome, microrregião) and the case-insensitive filter behavior, which are useful beyond the annotations. No contradictions found.
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 concise, well-structured with Args/Retorna, and front-loaded with the main purpose. Every sentence provides useful information without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool, the description covers the purpose, parameters, return value, and downstream usage. Since there is no output schema, explaining the returned fields (id, nome, microrregião) is essential and done well. No significant gaps for the intended use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters. The description adds value by specifying examples for uf ('SP', 'RJ', 'MG', 'BA') and clarifying that nome_filtro is case-insensitive, which goes beyond the schema's basic text description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it lists all municipalities of a state with 7-digit IBGE codes. The verb 'Lista' and resource 'municípios de um estado' make the function specific and distinguish it from siblings like ibge_buscar_municipio (search for one) and ibge_listar_estados (states).
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 gives a downstream usage hint ('Use o id em consultas SIDRA de municípios') and notes the optional filter, but it does not explicitly contrast with sibling tools such as ibge_buscar_municipio. Usage context is implied but not fully elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
As anotações já informam que a operação é somente leitura e idempotente, reduzindo a responsabilidade da descrição. A descrição agrega valor ao explicar que o retorno inclui a hierarquia completa Seção > Divisão > Grupo > Classe > Subclasse, mas não detalha a estrutura exata da resposta nem comportamento em casos sem correspondência.
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?
O texto é bem estruturado e front-loaded, com a frase principal no início, seguida de usos, parâmetros e lista de seções. A lista de 21 seções e os bullets tornam a descrição um pouco longa, mas cada elemento agrega informação prática; não há repetição desnecessária do schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A descrição cobre propósito, cenários de uso, parâmetros com exemplos, hierarquia de retorno e mapeamento de seções, o que é suficiente para uma ferramenta de busca sem output schema. Faltam detalhes como o formato exato do retorno, paginação ou comportamento com resultados vazios, mas o contexto geral está bem completo.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Embora o schema cubra 100% dos parâmetros, a descrição enriquece semanticamente ao fornecer exemplos no Args, como 'padaria', 'software' e 'construção civil', e um mapeamento completo das letras de seção (A=Agro, C=Indústria, J=TI etc.). Isso ajuda o agente a preencher termo e secao_id corretamente, indo muito além do que o schema isolado oferece.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
A descrição abre com verbo claro e específico: 'Busca atividades econômicas na CNAE' por palavra-chave, e acrescenta que retorna subclasses com hierarquia completa. Isso diferencia bem a ferramenta dos irmãos 'ibge_cnae_detalhar' e 'ibge_cnae_secoes', deixando claro que é um mecanismo de busca textual.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
A seção 'Use para' apresenta três cenários concretos com exemplos de perguntas, indicando claramente quando a ferramenta deve ser usada. Porém não menciona explicitamente quando não usar e não aponta alternativas como os irmãos de CNAE, o que evita o 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive behavior. The description adds valuable behavioral context beyond that, most notably the crucial caveat about 'ultimos_meses' for accumulated types returning only the N most recent periods, plus a description of the return series. This enhances transparency without contradicting annotations.
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 highly concise and well-structured: a clear opening sentence, a compact bullet list, and an important note. Every sentence earns its place, and the critical caveat is highlighted with 'IMPORTANTE', making it scannable and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no nested objects), the description is largely complete. It doesn't have an output schema, so it explains the return as a historical series with monthly percentage variation, which is adequate. Some detail about the exact response format is missing, but for a straightforward query tool this is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already documented. The description adds meaning by explaining the semantics of 'tipo' with examples and clarifying the non-obvious behavior of 'ultimos_meses' for accumulated types. This goes beyond the schema's basic descriptions and provides essential usage nuance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Consulta o IPCA' with a specific verb and resource, identifying it as the tool for Brazil's main inflation indicator. It stands apart from sibling IBGE tools that cover regions, population, or other economic indicators, making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
While no explicit alternatives or when-not-to-use guidance is given, the description provides clear context: this tool is for querying IPCA inflation data. The parameter explanations and the important note about accumulated types further clarify how to use it, but it doesn't explicitly compare with other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive hints. The description adds useful behavioral context: the default localidade is 'BR', returns ranking with name, frequency, and position, and clarifies that sexo can be null for both. No contradictions with annotations.
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 concise and well-structured: a one-sentence purpose, a bulleted list of parameters with defaults, a note on the return format, and a practical example. No redundant or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with three optional parameters and no output schema, the description is quite complete: it covers purpose, parameters, defaults, return shape, and an example. It could be improved by noting what happens with an invalid IBGE code or clarifying that ranking is across all names, but these are minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds extra meaning beyond the schema: it explains 'BR' as the default for localidade, clarifies that sexo null means both genders, and provides concrete decade examples (1990, 2000, 2010) that reinforce the schema's range.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the most popular names in Brazil or a specific location, with a specific verb ('Retorna') and resource ('nomes mais populares'). It distinguishes from the sibling 'ibge_nomes_frequencia' by focusing on ranking rather than individual name frequency, and even specifies the output includes position.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context through an example ('Quais os nomes mais comuns no Brasil?') and explains the optional parameters and defaults. However, it does not explicitly contrast with alternatives like 'ibge_nomes_frequencia' or state when not to use this tool, so it lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the annotations: it identifies the SIDRA table, discloses the default year ('mais recente'), and specifies the return units ('mil reais e PIB per capita'). Annotations already cover safety (readOnly, idempotent, non-destructive), so the description enhances transparency without over-explaining.
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 concise: two sentences plus a clean bulleted list of parameters. It is front-loaded with the main purpose, followed by parameter explanations and return format. Every sentence adds value, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description appropriately explains what is returned (GDP in thousands of reais and per capita). It also provides the SIDRA table reference, which aids traceability. It doesn't describe response structure in detail, but given the tool's simplicity and the annotations covering safety, this is sufficient but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full coverage (100%) with descriptions and examples. The description adds semantic context not present in the schema: estado_id returns all municipalities in the state, and 'ano' defaults to the most recent year. This goes beyond the schema's basic definitions, so it earns a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it queries the GDP of Brazilian municipalities using a specific verb ('Consulta') and resource ('PIB dos municípios brasileiros') with a reference to SIDRA table 5938. This distinguishes it from siblings like ibge_pib_estados (state-level GDP) and ibge_populacao_municipio (population).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains parameter combinations: municipio_id specifies one municipality, estado_id returns all municipalities in a state, and ano is optional with a default. While it doesn't explicitly name alternatives, the sibling context and the scope ('municípios') make the appropriate use case clear. It lacks explicit 'use this instead of X' guidance, hence a 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering safety and side effects. The description adds behavioral detail about the return format (ranking with % of national total) and optional parameter usage, which goes beyond the structured annotations. No contradictions found.
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 well-structured with a clear purpose statement, an Args section for the parameter, and a return summary. The UF mapping is lengthy but necessary as reference data. The main functionality is front-loaded, and every part serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, read-only, no output schema), the description is complete. It explains the query scope, parameter semantics, and return value format, covering all necessary information for correct invocation. No significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes uf_id with an example, but the description enriches it with a complete mapping of UF IDs (e.g., SP=35, RJ=33) and clearly states the parameter is optional. This adds value beyond the schema's minimal description, helping the agent select valid IDs without needing external knowledge.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 e compara a população de todos os estados ou de um estado específico.' This specifies the verb (consulta e compara), resource (população dos estados), and scope (todos ou um específico), distinguishing it from municipality-level or other population tools among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: omit the parameter for all states or provide a UF ID for a specific one. It also notes the output is a ranking with percentage of national total. However, it does not explicitly mention alternatives or exclusions, such as when to prefer ibge_populacao_municipio or ibge_estimativas_populacionais.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey read-only, idempotent, non-destructive. The description adds behavioral specifics: the default query returns 27 capitals when no state is given, top_n defaults to 20 with max 100, and ordering can be inverted. It also exposes the underlying IBGE table/variable identifiers, which helps understand data provenance.
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 concise: a one-line purpose, a tight parameter list, and three example queries. No redundant or filler sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the tool's output is straightforward (a ranked list of literacy rates), and the description covers all input dimensions, defaults, and edge cases. The examples provide sufficient guidance for typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all three parameters, but the description enriches them with practical examples ('35'=SP, '31'=MG) and clarifies the meaning of 'ordenar' as 'melhor taxa' vs 'pior taxa'. The special behavior of omitting estado_id is also described, which is not captured in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb-resource pair: 'Consulta a taxa de alfabetização (15 anos ou mais) por município com ranking.' It also specifies IBGE table 9543 and variable 2513, distinguishing it from other IBGE demographic tools like population or density.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage examples ('Mais alfabetizados em SP', 'Pior escolaridade na BA', 'Ranking das capitais') and explains when to omit estado_id (returns capitals). It doesn't name alternative sibling tools but gives enough contextual cues for an agent to choose this tool for literacy rate queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is well covered. The description adds valuable behavioral details beyond this: case-insensitive search, multilingual search (Portuguese, English, Spanish), and the return content (ISO codes and location). No contradiction with annotations.
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 concise, with a front-loaded purpose statement followed by clearly labeled sections (Parâmetros, Retorna, Exemplo). Every sentence adds value, and the structure makes it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read-only tool with no output schema, the description is complete. It explains the return format (list with ISO codes and location), provides an example, and clarifies search behavior. Combined with the strong annotations, the agent has everything needed to invoke and interpret the result correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing a baseline of 3. The description adds meaning beyond the schema by specifying that the search term works across three languages and that the search is case-insensitive, which are not present in the schema's parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Busca países cujo nome contenha o termo especificado' — a specific verb (search) and resource (countries) with a defined scope. It also differentiates from siblings by noting its utility for finding ISO codes before consulting detailed info, which is distinct from listing or obtaining country details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: 'Útil para encontrar código ISO de um país antes de consultar informações detalhadas.' This implies when to use it (for ISO lookup) but does not explicitly name alternatives or state when not to use it. That fits 'clear context, no exclusions.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by specifying the return fields (ID, nome, unidade) and that it returns the complete list, which is valuable beyond the annotations.
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 concise and well-structured: a clear primary sentence, a return-value detail, and a usage note. Every sentence adds value, and it stays within 3 short sentences with effective use of bold labels.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one optional parameter and strong annotations, the description is complete: it states the count (34), categories, return fields, and usage context. No output schema exists, but the description adequately covers what the agent needs to know.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (single 'categoria' parameter with enum and description). The description adds meaning by listing the categories (Economia, Indicadores Sociais, etc.), which helps users understand the parameter values even though it doesn't explicitly map them to the lowercase enum strings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the complete list of 34 indicators for countries, organized by category. It uses a specific verb ('Retorna') and resource ('lista completa dos 34 indicadores para países'), and the inclusion of 'para países' distinguishes it from sibling tools like ibge_listar_indicadores.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides an explicit use case ('Para descobrir quais indicadores estão disponíveis antes de consultar dados'), indicating when this tool should be used. It does not mention exclusions or alternatives, but the context makes the intended usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds useful context by defining the return format ('Lista de notícias com título, introdução, data de publicação e link') and the scope 'recentes' (recent). It also clarifies parameter constraints (quantidade 1-20, default 10), which supplements the schema.
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 well-structured and front-loaded: a single clear purpose sentence, followed by concise parameter details, return format, and examples. Every line adds value, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, but the description compensates by explicitly listing the return fields (title, introduction, date, link). It covers all optional parameters with examples, making it complete for an agent to decide when and how to invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for all three parameters, providing baseline. The description adds substantial value by giving concrete example values for each parameter (assunto: 'censo', 'pib', 'desemprego'; produto: 'PNAD', 'IPCA', 'Censo'), which helps an agent understand how to invoke filters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's specific function: 'Busca notícias, releases e publicações recentes do IBGE' (searches recent news, releases, and publications from IBGE). This distinguishes it from sibling tools that focus on structured data like regions, municipalities, tables, and indicators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context and practical usage examples mapping natural language queries to parameters (e.g., 'Notícias sobre o Censo 2022' → assunto='censo'). It does not explicitly mention alternatives or exclusions, but the focus on news vs. structured data is evident from the examples and the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral details such as returning a ranking with percentage share and the default behavior of per_capita, extending beyond what annotations offer. No contradictions.
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?
Well-structured with a clear introduction, argument list, return description, and examples. Every sentence is informative and earns its place, with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 parameters, no output schema), the description covers all necessary aspects: purpose, parameters, return format, and usage examples. It's complete for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description enhances it by providing examples (e.g., uf_id 35=SP), stating the default for per_capita, and explaining the return ranking, which adds practical meaning beyond the schema field descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it queries the Gross Domestic Product (PIB) of Brazilian states, using a specific verb ('Consulta') and resource ('PIB dos estados'). It distinguishes from sibling tools like ibge_pib_municipios by explicitly focusing on state-level data, and even provides example queries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context by stating it's for regional economic analysis of Brazilian states and provides example queries, making it evident when to use this tool. However, it doesn't explicitly mention alternatives or when not to use it, but the state-level scope implicitly differentiates it from municipal-level siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds behavioral context beyond these: it specifies a maximum of 50 results, lists return fields (id, nome, período, variáveis), and expands pesquisa_id codes with their meanings. It does not contradict the annotations, though it does not elaborate on search matching semantics.
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 concise and well-structured, with an Args list and a Retorna section. Every sentence contributes value: the core purpose, parameter details with examples, and return specifications contain no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two optional parameters, no output schema, and strong annotations, the description is complete. It explains the return format (id, nome, período, variáveis), the maximum result count, and the meaning of each parameter. It does not omit any critical context needed for an agent to decide to use it or interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers both parameters (100% coverage), but the description enriches them by expanding pesquisa_id codes to full survey names (CN=Censo, CA=Censo Agro, etc.) and providing concrete examples for nome_filtro (população, PIB, IPCA). This adds meaning beyond the schema, though the baseline is 3 due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Pesquisa tabelas (agregados) disponíveis no SIDRA por palavra-chave ou pesquisa.' It uses a specific verb (pesquisar), identifies the resource (tabelas do SIDRA), and details how search can be refined by keyword or survey. This distinguishes it from sibling tools like ibge_sidra_metadados_tabela and ibge_sidra_consultar_tabela, which operate on already-known tables.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for discovering tables: it explains the parameters and return values, making it clear this is a search/find operation. However, it does not explicitly state when not to use it or mention alternatives (e.g., if a table ID is already known, use metadata or consult tools instead). The context is clear but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly and idempotent behavior, and the description adds value by specifying the exact return structure (id, sigla, nome) and the meaning of each id (1=Norte, 2=Nordeste, etc.), fully disclosing the tool's output.
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 extremely concise: two sentences that clearly state the purpose and the return format. Every word earns its place, and the key information (the id mapping) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description is complete. It lists the five regions, explains the id codes, and states the fields returned, leaving no significant gaps for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema is empty (100% coverage). With no parameters to document, the description doesn't need to add parameter semantics, resulting in a baseline score of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('Lista') and resource ('as 5 grandes regiões do Brasil'), and it distinguishes itself from sibling tools like 'ibge_listar_estados' and 'ibge_listar_municipios' by its focus on regions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: this tool lists Brazil's major regions with their codes and acronyms. While it doesn't explicitly mention when not to use it, the distinct resource (regions) and the lack of ambiguity make the appropriate usage evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds behavioral context by specifying the return format (AAAA, AAAAMM, or trimestre), which is useful beyond the annotations. No contradiction with annotations.
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 concise and well-structured: a one-sentence purpose statement, a usage directive, a compact Args list, and a Returns line. Every sentence adds value, no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema, the description fully covers what the tool does, when to use it, and what it returns. It even explains the benefit of avoiding errors, making it self-contained for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% parameter coverage with examples. The description supplements this by tying specific example codes to well-known datasets ('1419' para IPCA, '9514' para Censo), adding real-world meaning to the parameter beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Retorna todos os períodos disponíveis para uma tabela SIDRA' with a specific verb and resource. It also distinguishes itself from the sibling tool ibge_sidra_consultar_tabela by noting this should be used beforehand.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly directs use 'ANTES de ibge_sidra_consultar_tabela' when needing to know available years/months, and cites the benefit of avoiding 'período não encontrado' errors. This provides clear when-to-use guidance and distinguishes it from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds context about the return content, specifically that it includes category IDs and ready-to-use values for the 'classificacao' parameter. It does not detail output structure, but provides meaningful value beyond annotations.
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 three sentences, front-loaded with the main purpose, followed by a clear usage directive and an args line with examples. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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 comprehensively lists what the metadata includes (variables, classifications, territorial levels, periods) and the exact use-case for querying. This is sufficient for an agent to decide when to call it and what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes tabela_id as 'Código da tabela SIDRA', and the description adds practical examples ('9514', '1419', etc.). This gives format guidance beyond the schema's minimal description, helping the agent construct correct input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Retorna metadados completos' and lists concrete outputs: variáveis, classificações com IDs, níveis territoriais, e períodos. It clearly distinguishes itself from the sibling ibge_sidra_consultar_tabela by focusing on metadata retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use the tool: 'Use SEMPRE antes de ibge_sidra_consultar_tabela quando não souber os IDs de variável ou classificação', naming the alternative tool and the exact scenario. It also notes that it returns the exact classificacao values ready for use, reinforcing its role as a preparatory step.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnly, idempotent, and openWorld. The description adds valuable behavioral context beyond these: it discloses potential HTTP 500 errors when fetching invalid periods, emphasizes the need to consult metadata first, and explains the behavior when parameters are omitted (e.g., 'Sem valor = todas'). This prepares the agent for failure modes and correct invocation.
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 moderately long but exceptionally well-structured with headers, a numbered workflow, and bullet-like parameter explanations. Every line adds value—examples, error warnings, and handy table IDs—without unnecessary fluff. It is front-loaded with the purpose and recommended flow, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 flexible parameters, no output schema) and the presence of sibling tools handling metadata and periods, the description provides comprehensive context: prerequisites, parameter syntax, workflow, and common-use table IDs. It covers everything an agent needs to select and invoke this tool correctly, including how to avoid errors.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 100%, the description enriches parameter understanding with concrete examples and formats: pipe-separated variables, localidade code patterns, special period values ('-6', '-12'), and classification syntax ('ID[all]'). It also explains default behaviors and common pitfalls, going well beyond the schema's basic descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 de uma tabela específica do SIDRA com séries históricas por localidade.' It uses a specific verb ('Consulta'), names the resource (tabela do SIDRA), and specifies the scope (séries históricas por localidade), making it distinct from sibling tools like metadata or period explorers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a detailed recommended workflow for unknown tables, explicitly naming sibling tools (ibge_sidra_metadados_tabela, ibge_periodos_tabela) and explaining when to use each. It also gives warnings to avoid HTTP 500 and advises never to invent classification IDs, giving clear when-to-use and how-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![ab-ibge-mcp-server MCP server](https://glama.ai/mcp/servers/ab-orbit/ab-ibge-mcp-server/badges/card.svg)](https://glama.ai/mcp/servers/ab-orbit/ab-ibge-mcp-server)

Score Badge

Copy to your README.md:

[![ab-ibge-mcp-server MCP server](https://glama.ai/mcp/servers/ab-orbit/ab-ibge-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/ab-orbit/ab-ibge-mcp-server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ab-orbit/ab-ibge-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server