IBGE: Área territorial brasileira

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

Annotations already declare idempotent, non-destructive, and non-read-only. The description adds context on the two authentication modes (permanent vs session) and the no-arg behavior, which supplements the annotations without contradiction. It clarifies that the token is for session login, aligning with 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise given the multiple usage modes, starting with a clear purpose and then detailing the permanent and session options. The structure is logical: context, recommendation, alternative, and specific call examples. Each sentence serves a purpose, though it could be tightened.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema, the description covers the essential usage scenarios: permanent config, session token, and link retrieval. It does not describe return values, but given the auth flow and annotations, this is adequate. The description provides enough to know how to invoke the tool correctly for both modes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema only lists a token string with 0% description coverage, so the description must explain it. It does: indicates the token is a JWT for session login ('{ token: "<jwt>" }') and that omitting it retrieves a link. This adds meaning beyond the schema, though it doesn't specify token format requirements beyond 'jwt'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states this is an authentication tool for MCP.AI on IDE agents, with specific actions: logging in, copying access tokens, configuring permanent tokens, and session-only login. It identifies the resource (access token/connection) and the verb (authenticate), and distinguishes from siblings like 'connect' by focusing on token handling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage modes: adding a header for permanent access or pasting a token for session-only login, and explains calling with no args to get the link. It gives context on when to use each method, though it does not explicitly compare to alternative tools like 'connect'.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds meaningful behavioral context beyond annotations: it explains the response shape (authenticated flag, pending array, connect_url) and conditional states, enriching the agent's understanding of what to expect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the primary action and concise. It efficiently conveys the core behavior and conditional outcomes without any wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no parameters, the description fully explains the tool's two possible outcomes and covers the main behavioral aspects. Combined with annotations (readOnly/idempotent), it provides complete context for a status-check tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and schema coverage is 100%, so the description has no parameter burden. Per the baseline for 0 params, a score of 4 is appropriate; the description correctly does not attempt to describe nonexistent parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: it returns connection status and URLs. It uses specific verbs ('Returns') and explains its behavior under two conditions, distinguishing it from siblings like 'authenticate' (which likely initiates auth) and 'toolkit_info'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage (checking connection status) but does not explicitly state when to use this tool versus alternatives. It mentions conditional outcomes (all providers connected vs. missing credentials) but does not provide guidance like 'use authenticate when credentials are missing' or exclude cases.

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

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

The description adds meaningful behavioral context beyond the annotations: no credentials needed, prepaid per-query billing, data is public/non-confidential, and the customer is the data controller under LGPD. It also aligns with the readOnlyHint, idempotentHint, and destructiveHint annotations, with no contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is reasonably concise, front-loads the core purpose, and includes important operational details (credentials, cost, LGPD) in a compact form. It could be slightly tighter by separating legal disclaimers from the main functionality, but it remains efficient and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple query tool with good annotations, the description covers operational context well (cost, credentials, data nature, legal responsibility), but it omits critical query details: no parameter format guidance, no example values, and no description of the return value since no output schema exists. An agent would likely need additional information to invoke it correctly with real-world inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the two parameters (codigo_estado, nome_municipio), but it does not explain expected formats (e.g., whether codigo_estado is a UF abbreviation or numeric IBGE code) or how the parameters relate to the returned area. The parameter names are self-explanatory at a basic level, but no value is added beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'IBGE: Área territorial brasileira, consulta em fonte oficial', which clearly identifies the tool as querying Brazilian territorial area information from the official IBGE source. It distinguishes itself from the sibling tools (auth, marketplace, report_bug, etc.), though it does not explicitly state that the output is the area value for the given municipality/state.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides practical usage context: the tool requires no platform credentials, is billed per query with prepaid credit, and queries only public official data. It does not explicitly state when not to use the tool or name alternatives, but the context is clear enough for selecting it over non-query sibling tools.

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

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

Annotations provide readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false, but the description adds substantial context beyond these: it discloses that invoke runs tools without installation, returns auth/checkout links when credentials or payment are needed, and that writes require workspace owner/admin. It also notes the distinction between installed_in_toolkit and installed_in_workspace. 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but densely packed with essential information for a complex, multi-action tool. It is structured around the core flow and covers permissions, edge cases, and the prompt library. Every sentence contributes to understanding. However, it is a wall of text without explicit paragraph breaks or bullet points, which slightly reduces readability, though it remains efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity—14 actions, 23 parameters, no output schema—the description provides significant context. It explains the relationship between actions, the lifecycle of MCPs (one-off vs permanent), credential/payment handling, permission requirements, and the prompt library. It does not describe return values or output formats, but that is somewhat acceptable without an output schema. It is fairly complete, though per-parameter behavior is not covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 23 parameters with 0% description coverage, so the description must compensate. While it explains the actions and the general flow, it does not provide per-parameter semantics for most fields (e.g., limit, query, message, arguments, etc.). It gives some guidance indirectly through the action descriptions (e.g., invoke needs tool_id and arguments), but leaves many parameters unexplained. It is not a 2 because it does offer meaningful context about the main actions, but it falls short of fully compensating for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool is the official mcp.ai marketplace, covering both discovery and execution of MCPs, plus a prompt library. It uses specific verbs like search, describe, invoke, install, and lists the capabilities. It distinguishes itself from siblings by its broad scope and unique functionality (e.g., invoke without install), which no sibling tool offers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides usage guidance: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and explains the core flow (search → describe → invoke). It also differentiates actions like list_tools, subscribe/cancel, and request_mcp, and notes when to use the prompt library. It gives clear 'when to use' and even 'when not to use' (e.g., avoid install for one-off uses).

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

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

Annotations already indicate readOnly=false, idempotentHint=true, and destructive=false. The description adds that the conversation array is used for reproduction, which provides some contextual value. However, it does not disclose what happens after reporting (e.g., ticket creation, data transmission), leaving some behavioral ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, consisting of two short sentences that front-load the purpose and then provide a direct usage tip. Every word earns its place without unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with three string parameters and no nested objects, the description is adequate but not thorough. It addresses the conversation parameter explicitly but leaves the other two parameters unexplained, which could lead to misuse. The level of detail is minimal for the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only mentions the 'conversation' parameter, clarifying its purpose for reproduction. It does not explain 'message' or 'context', which are essential for correct invocation. The description fails to compensate for the lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reports a bug, missing feature, or sends feedback, using specific verbs and resources. It distinguishes itself from sibling tools like 'connect' or 'authenticate' which are about different actions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It implies usage by instructing the user to include the conversation array for reproduction, but it does not explicitly state when to use this tool over alternatives or provide exclusions. The guidance is present but not fully developed.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well-established. The description adds no additional behavioral context beyond the core purpose, but this is acceptable given the strong annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single declarative sentence that conveys the tool's function without redundancy or repetition of structured data. It is appropriately front-loaded and minimal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a parameterless, read-only version tool with comprehensive annotations, the description is fully sufficient. There is no output schema, but showing version strings is self-explanatory, and the tool's simplicity means no additional context is required.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema is empty (100% coverage). With no parameters, the description need not add parameter details; the baseline of 4 applies because the description correctly avoids attempting to explain nonexistent inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Show' and names exact resources ('MCP platform and adapter versions'), clearly distinguishing it from sibling tools like authenticate or connect. This is a specific and unambiguous statement of the tool's function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies the tool is for retrieving version information when needed, providing clear context for usage. However, it does not explicitly state when not to use it or mention alternatives, though for a version info tool this is likely unnecessary.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds value by detailing the returned content (installed MCPs, connections, accounts, tool counts). No contradiction, and it enriches the safety profile with concrete output information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the action ('Returns') and immediately specifies the output components. No unnecessary words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lists all the specific pieces of state returned, which is sufficient for a read-only tool without an output schema. It doesn't mention response format or potential variations, but for a status tool with no parameters, this feels complete enough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

As there are zero parameters, the description doesn't need to explain parameter usage. The baseline of 4 is appropriate since no parameter semantics are required.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns the current toolkit state, enumerating specific aspects (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes itself from sibling actions (authenticate, connect) as a read-only status query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for checking toolkit status, but does not explicitly state when to use it versus alternatives, nor provide exclusions or prerequisites. For a simple read tool, this is acceptable but not fully explicit.

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