Reclame Aqui

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

Annotations indicate idempotentHint=true and destructiveHint=false, which align with the description's non-destructive, repeatable nature. The description adds context about the token being non-expiring when added to config, and session-only when pasted, which is beyond the annotations. However, it doesn't explicitly mention that the tool initiates a browser login flow, which could be a side effect, but the description does say 'log in in the browser' so it's covered. 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 a single, dense paragraph that front-loads the purpose and then explains usage. It's concise but packs a lot of information into one sentence, which could be slightly restructured for readability. However, every sentence earns its place, and it's not overly verbose.

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 simplicity (1 optional param, no output schema), the description is fairly complete. It covers the two usage modes, the token parameter, and the no-args behavior. It doesn't mention what the response looks like, but since there's no output schema, that's a minor gap. The description is adequate for an agent to use the tool correctly.

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

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

The schema has one optional parameter 'token' with no description, and schema description coverage is 0%. The description compensates by explaining the token parameter: it should be a JWT pasted by the user for session-only login, and that calling with no args returns the login link. This adds meaning beyond the bare schema, though it could be more explicit about the token format.

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: authenticate a user for MCP.AI IDE agents by logging in via browser and obtaining an access token. It distinguishes itself from siblings by being the only authentication-related tool among the listed siblings, which are about connecting, marketplace, ReclameAqui operations, bug reporting, and version 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 provides explicit usage guidance: it explains two modes (permanent via config header vs session-only via pasting token), and instructs to call with no args to get the login link. It also mentions the best practice of adding the token to the server's config for a permanent connection, which helps the agent decide when to use this tool.

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

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

Annotations already cover safety (readOnly, idempotent, non-destructive). The description adds transparency about the return values under different conditions, which goes beyond annotations without contradicting them.

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 well-structured sentences. It states the general function and then details the two key cases without any superfluous information.

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

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

Given there is no output schema, the description adequately explains the return values for the most common scenarios (all connected vs. missing credentials). However, it does not cover intermediate states or error handling, leaving some ambiguity, but it is sufficient 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?

There are no parameters, so the description cannot add parameter meaning beyond the schema. According to the rubric, with 0 parameters, the baseline is 4, and the description does not need to explain anything extra.

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 also specifies two distinct outcome scenarios (all providers connected vs. missing credentials), making it distinct from the sibling 'authenticate' tool which likely performs authentication.

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 before authentication) but does not explicitly state when to use this tool versus alternatives like 'authenticate'. The behavior descriptions provide context, but the guidance is not spelled out.

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

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

The description goes well beyond the annotations: it discloses that invoke works for uninstalled MCPs, connects to credentials/checkout links, requires workspace owner/admin for writes, and flags installed_in_toolkit vs installed_in_workspace. These behavioral details add significant context without contradicting the annotation flags.

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 and dense, but it earns its length given 14 actions and 23 parameters. It front-loads the core marketplace flow, then covers edge-case behavior, permissions, and the prompt library. A more structured layout with headings or bullet lists would improve scannability, but every sentence adds substantive value.

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 complex multi-action tool with no output schema, the description is remarkably complete: it explains workflows, auth/payment fallbacks, permission requirements, and the prompt library. It does not explicitly describe return-value shapes or the 'resume' action, so it is not fully exhaustive, but it covers the primary decision paths an agent needs.

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?

With 0% schema coverage, the description compensates substantially by explaining the action enum (search, describe, invoke, install, list_tools, prompt actions) and contextualizing key params like mcp_id, tool_id, and arguments. However, several params such as limit, query, immediate, tier_slug, conversation, and request_name receive no explicit explanation, leaving some gaps.

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 identifies the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates the core flow (search → describe → invoke) and distinguishes related sub-actions, making the tool's purpose unmistakable and distinct from the sibling tools such as reclameaqui_* or report_bug.

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

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

The description gives explicit usage guidance: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also explains when to use list_tools, request_mcp, subscribe/cancel, and the prompt library functions, providing clear decision criteria and alternatives.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds meaningful behavioral context: it scopes results to 'sua empresa' (your company) and states the default ordering (most recent first). It does not, however, disclose behaviors like pagination limits or authentication requirements, but the annotations and description together provide reasonable transparency.

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, efficient sentence that front-loads the main action ('Lista as reclamações') and immediately provides essential details. There is no unnecessary verbiage or repetition; every word contributes to understanding the tool's purpose.

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?

With 5 optional parameters and no output schema, the description is incomplete. It lists output fields but does not explain parameter semantics (e.g., how to paginate with index/limit, how to filter by status, or what 'order' and 'order_type' mean). While the description covers default behavior, it leaves too many aspects undocumented for an agent to use the full parameter set effectively.

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

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

The description does not mention any of the 5 input schema parameters (index, limit, order, status, order_type). Schema description coverage is 0%, so the description carries no semantic weight for parameters. Since the schema itself has enums but no descriptions, the description fails to compensate for this gap.

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

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

The description clearly states the tool's function: 'Lista as reclamações da sua empresa no Reclame Aqui' (lists complaints of your company), specifies default ordering ('mais recentes primeiro') and enumerates returned fields (id, título, status, consumidor, cidade/UF, responded status, avaliação). This verb+resource combination distinguishes it from siblings like reclameaqui_responder (respond) and reclameaqui_reputacao (reputation).

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or exclusions. The description only states what the tool does, leaving the agent to infer usage from the name and sibling context.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by disclosing what data is returned and that a list of IDs is accepted, going beyond the annotation-only 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, front-loaded sentence that conveys purpose, input capability, and output content without redundant words or restating the tool name. Every element adds useful information.

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

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

With no output schema, the description helpfully names the main return elements (treatments, avaliação, score, status) and covers the ID-based input modes. It does not mention behavior for missing IDs or authentication prerequisites, but for a simple read-only lookup tool this is nearly complete.

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

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

Schema description coverage is 0%, so the description must compensate. It does so by explaining that the tool fetches 'uma ou mais reclamações por id' and 'Aceita lista de ids,' giving meaning to both the singular 'id' and plural 'ids' parameters. It does not fully specify constraints like mutual exclusivity or ID format, but it provides enough semantic context for basic invocation.

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

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

The description clearly states that the tool retrieves details of one or more complaints by ID ('Detalhe de uma ou mais reclamações por id') and enumerates the included information (conversa completa, avaliação, score, status). It also differentiates itself from sibling tools by emphasizing ID-based lookup rather than listing or reputation.

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

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

The description implies the appropriate context: use this tool when you already have complaint IDs and need full detail. It clarifies that it accepts a list of IDs, but it does not explicitly name alternatives or state when not to use it, so it stops short of full explicit guidance.

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about what the response contains (score/rating and main complaint topics), but does not disclose further behavioral details such as response shape, freshness of data, or whether any prior authentication is required.

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, focused sentence that conveys the tool's purpose with practical examples of the returned indicators. No wasted words or redundant material.

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 reputation tool, the description provides adequate context for an agent to decide when to invoke it. It does not detail the exact output structure, but no output schema exists and the tool's purpose is relatively straightforward.

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

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

The tool has zero parameters, so the baseline of 4 applies. There is no parameter meaning to add beyond the empty schema, and the description correctly identifies a parameterless reputation query.

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 identifies the resource ('Indicadores de reputação da sua empresa no Reclame Aqui') and specifies what will be returned (nota/rating and principais problemas reclamados). It distinguishes from sibling tools like reclameaqui_listar_reclamacoes and reclameaqui_responder by focusing on reputation indicators rather than listing complaints, inspecting a specific complaint, or responding.

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?

Usage context is implied: the agent can infer it should use this tool when needing company reputation indicators instead of individual complaints. However, the description does not explicitly state when to use this tool versus alternatives such as reclameaqui_listar_reclamacoes or provide exclusions.

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 indicate non-readOnly, non-destructive, non-idempotent, so the write nature is implied. The description adds critical context about public action and confirmation necessity, which goes beyond the annotations. Bulk support is also disclosed. 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.

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

The description is concise with three sentences: purpose, default and parameter guidance, and bulk support. The warning is embedded naturally. No fluff, front-loaded with the most important info.

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 four params and no output schema, the description covers the essential aspects: action, public/private distinction, and bulk execution. It doesn't specify return values, but that's not strictly necessary. The warning about public action is a nice touch for a write 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?

Schema description coverage is 0%, so the description must compensate. It explains the 'privada' parameter (default public, true for private) and the bulk capability via 'ids'. It does not elaborate on 'id' vs 'ids' relationship or the exact format of 'mensagem', but covers the key semantic elements.

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 verb 'Responde' and resource 'reclamação' with explicit scope ('da sua empresa'), and distinguishes from sibling tools like reclameaqui_listar_reclamacoes and reclameaqui_reclamacao. The 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.

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

Provides clear usage guidance: default is public response, privada=true for internal message, and warns about the public nature of the action ('confirme o texto antes de enviar'). It also mentions bulk support. While it doesn't explicitly say when not to use, the context is sufficiently directed.

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 indicate a non-destructive (destructiveHint: false), idempotent (idempotentHint: true) write operation. The description adds the practical requirement of including a conversation array for reproduction, which is useful. It does not contradict the annotations, but it does not detail side effects or post-report behavior. Given the annotations, the description provides adequate additional context.

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, two-sentence statement that is front-loaded with the purpose and includes a necessary instruction. No redundant words; every sentence contributes meaning.

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

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

For a simple tool with 3 parameters and no output schema, the description covers the core purpose and the key parameter (conversation). It falls short on explaining the 'context' parameter and does not mention the response format, but given the tool's simplicity and the annotations, it is nearly sufficient. A small gap remains.

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

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

Schema description coverage is 0%, so the description must compensate. It explicitly explains the 'conversation' parameter's purpose (include recent messages for reproduction) and 'message' is inferred from the purpose. However, the 'context' parameter is left unexplained. This adds some value beyond the schema but is incomplete.

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: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') and a resource (bug/feature/feedback), and it is distinct from sibling tools like authenticate, marketplace, and reclameaqui, which handle unrelated domains.

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

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

The description implies when to use the tool (for reporting issues) and provides specific guidance on including the conversation array for reproduction. However, it does not explicitly state when not to use it or mention alternatives, but the context is clear enough for an agent to decide.

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, covering the safety profile. The description adds the specific scope ('current' versions, 'platform and adapter'), which is useful context. No behavioral gaps or contradictions.

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, front-loaded sentence that conveys all necessary information without redundancy. It earns every word, making it an excellent example of conciseness.

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, parameterless read-only tool with no output schema, the description is sufficiently complete. It identifies the exact information returned (platform and adapter versions) and notes the 'current' state, which is all an agent needs to know. Could optionally mention the return format, but that is not critical given the tool's simplicity.

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

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

The tool has zero parameters, so the schema provides no information to enrich. The baseline for zero-parameter tools is 4; the description does not need to add parameter details since none exist.

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: showing the current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), making it unambiguous and distinguishing it from sibling tools that handle authentication, marketplace, or complaint operations.

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 its use as a version-inspection tool, which is clear in context. There are no direct alternatives for checking platform versions among siblings, so no explicit exclusions are needed. It could mention that it is safe to call at any time, but the annotations already convey that.

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 covered. The description adds value by specifying the content of the returned state (installed MCPs, statuses, accounts, catalog counts), which is useful behavioral context beyond the structured fields.

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, front-loaded sentence that starts with the action verb 'Returns' and lists four concrete data elements without any filler. Every word contributes meaningful information.

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

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

For a simple, zero-parameter, read-only state inspection tool, the description fully covers what an agent needs: what information is returned and the non-mutating behavior (confirmed by annotations). No output schema or parameters exist, so no additional return-type or parameter details are 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 an empty input schema with trivial 100% coverage. According to the baseline for parameterless tools, the description does not need to explain parameter usage, and it correctly omits any param details.

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

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

Description uses a specific verb ('Returns') and names a concrete resource ('current toolkit state'), then enumerates exactly which details are included: installed MCPs, connection status, connected accounts, and catalog tool counts. This makes the tool's purpose immediately clear and distinguishes it from siblings like show_version or connect.

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 when an agent needs an overview of installed/connected services, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. Since no sibling offers the same state-snapshot capability, the gap is minor but still present.

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