Comprot: Processo

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

The description adds meaningful behavior beyond the annotations: it reveals that no-args returns an authentication link, that pasted tokens are session-only, and that config tokens are permanent and non-expiring. This is valuable context for an idempotent, non-destructive auth tool. It does not contradict 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 compact yet information-dense. Both sentences earn their place: the first establishes context and the login flow, the second clearly lays out the two configuration/login options. The 'Best:' and 'Or' structure makes the alternatives easy to parse.

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

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

For a simple one-parameter authentication tool with no output schema, the description covers the core workflow: browser login, token acquisition, permanent config setup, session-only token usage, and no-args behavior. It could mention success/error responses or what happens after the session token is accepted, but it is largely 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?

With 0% schema description coverage, the description carries the semantic burden for the 'token' parameter. It clearly explains that token is an optional JWT and describes the two call patterns: with a token for session login, or with no args to receive a link. This is sufficient for the single optional parameter.

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's purpose: authenticating to MCP.AI for IDE agents, with concrete steps for logging in and obtaining a token. It does not explicitly differentiate itself from the sibling tool 'connect', though the focus on browser login and token acquisition makes the purpose reasonably distinct.

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 guidance on two usage modes: adding the token to server config for a permanent connection, or pasting a session-only token. It also explains when to pass a token versus call with no arguments. It does not mention when not to use this tool or compare it against 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 already declare readOnlyHint=true, openWorldHint=false, idempotentHint=true, destructiveHint=false. The description adds value by noting this is public data available to all citizens ('a mesma disponível ao cidadão, não é dado sigiloso'), clarifying the non-confidential nature, and handles LGPD compliance by stating the client is the data controller. It doesn't contradict annotations and provides reasonable disclosure beyond what annotations offer, though it could have gone deeper on privacy/data retention specifics.

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 paragraph of reasonable length (2-3 sentences), providing critical non-obvious information (government data source, LGPD considerations, prepaid consulting model, public nature of data). It's front-loaded with the core purpose. Slightly cryptically worded with the middle 'Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago' but concise overall.

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 5-parameter tool with no output schema and clear annotations, the description essentially covers the essentials: domain (official Brazilian sources), nature of the operation (consult), and legal compliance (controlador LGPD). However, it operates under the assumption that the agent understands how to combine the 5 parameters (width of a national database query), and it would have been strengthened by mentioning the completion or recommendation of the fields, especially since 3 parameters (cpf, cnpj, processo) appear mutually exclusive, and 2 data parameters 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?

Schema description coverage is 0%, so the description had the burden to compensate. It mentions the domain (processos, dados de fontes oficiais) and the distinction between person (cpf), company (cnpj), and process (processo) identifiers. However, it doesn't explicitly map parameters to their formats (CNPJ 14-digit, CPF 11-digit, date format for data_inicio/data_fim), the required field combination (data_inicio + data_fim), or clarify whether the combination is a filter versus standalone search criteria. This is a missed opportunity given the 0% 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 uses a clear verb-resource-scope structure: 'Consulta informação de fontes e órgãos oficiais brasileiros' (consult Brazilian official sources/agencies). It clearly identifies the tool as a read/query operation for processes and specifies the Brazilian public-domain context. However, since sibling descriptions aren't shown, specific sibling differentiation is only partially achievable, keeping it from a 5.

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 this is a consult/read operation and explains the revenue model ('pague por consulta com crédito pré-pago'), which tells users about associated costs. However, it doesn't explicitly state when to use this tool versus alternatives, nor does it provide explicit exclusions or alternative tool names. Usage is implied by context rather than explicitly stated.

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 discloses the two possible outcomes (all providers connected vs. missing credentials) and what each returns (authenticated:true with empty pending[], or connect_url for toolkit and per-install URLs). This provides good insight into behavior, though it could be more detailed about potential side effects (none expected given readOnly hint).

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, using two sentences to convey the core purpose and two main scenarios. No unnecessary fluff or redundancy. It is well-structured and to the point.

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

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

Given the simplicity of the tool (no parameters, no output schema), the description is complete. It explains what the tool does and the distinct outcomes, which is sufficient for an agent to determine when and how to use it. No further context is needed.

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 no parameters, and the schema coverage is complete (100%). There is nothing to explain; the description does not need to add parameter details. This is trivially sufficient.

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 clearly states the tool returns connection status and URLs, and distinguishes it from sibling tools like authenticate (which performs authentication) and toolkit_info (which provides general info). The two specific return cases further clarify its purpose.

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

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

The description implies the tool is for checking connection status, but does not explicitly state when to use it versus alternatives (e.g., when to call 'connect' vs 'authenticate' or 'toolkit_info'). It lacks explicit usage guidance, though the purpose is clear enough for a simple status check.

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=false and destructiveHint=false, but the description adds critical behavioral detail: invoke runs tools without installing them, install/uninstall/subscribe/cancel require workspace owner/admin, and invoke may trigger a one-off install behind the scenes. It also explains the return behavior (connect/checkout links). This exceeds what annotations provide.

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

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

The description is dense but not bloated; every sentence adds information about a different action or edge case. It is front-loaded with the core purpose and flow. However, it is a single wall-of-text paragraph without bullet points or structural aids, which hurts scannability for a 14-action tool.

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 params, no output schema), the description covers the main flows comprehensively: search→describe→invoke, install persistence, billing/auth recovery, prompt library, permission model, and sibling distinctions. Minor gaps exist (resume action, immediate parameter, cancel_reason semantics), but the overall context is sufficient for an agent to operate 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?

With 23 parameters and 0% schema description coverage, the description must compensate. It explains the action parameter's role and the relationship between describe (returns tool_id) and invoke (uses tool_id), and implies prompt_vars for get_prompt. However, many parameters (limit, immediate, tier_slug, conversation, request_name, prompt_* fields) are not described, leaving the agent to infer from names and defaults. This is a partial compensation, not full.

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 mcp.ai marketplace, a catalog and execution engine for MCPs/tools, and distinguishes it from sibling tools like authenticate/connect. It enumerates the core flow (search → describe → invoke) and secondary actions, so the agent understands the tool's sphere.

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 guidance on when to use invoke vs install ('prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT'), and explains list_tools, report_bug, request_mcp alternatives. It also gives conditional behavior for auth/billing (connect link, checkout link), making the decision tree actionable.

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 a non-readonly, idempotent mutation. The description adds the instruction to include the conversation array for reproduction, which is useful behavioral context. However, it doesn't disclose side effects or post-report behavior, so transparency is 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.

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

Two short sentences with the purpose front-loaded. Every phrase earns its place, and there is no redundant information.

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

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

For a simple bug-report tool with no output schema and good annotations, the description covers purpose and a key usage hint (conversation). Missing explanations for 'message' and 'context' are partially offset by the direct purpose statement, but the overall description is still sufficient.

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

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

Schema description coverage is 0%, so the description must compensate. It only clarifies the 'conversation' parameter ('Include the conversation array with recent messages for reproduction'). The required 'message' parameter and optional 'context' remain unexplained, leaving ambiguity about their intended contents.

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 a specific verb ('Report') and names concrete targets (bug, missing feature, feedback), clearly distinguishing it from sibling tools like authenticate, marketplace, or show_version.

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 states when to use this tool ('Report a bug, missing feature, or send feedback') and gives a clear context. It does not mention exclusions or alternatives, but none are needed given the unrelated 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?

The description says 'Show', which aligns perfectly with the annotations readOnlyHint=true and idempotentHint=true. There is no indication of side effects, destructive behavior, or open-world semantics. No contradictions or omitted behavioral caveats are present.

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, efficiently written sentence that conveys the tool's function without unnecessary verbosity. It is neither vague nor over-specified, striking the right balance for a simple version-inspection tool.

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?

While the tool has no output schema, the description indicates it returns 'current MCP platform and adapter versions'. This gives a general expectation of the response content. However, it doesn't specify the exact format (e.g., JSON structure, string representation), which could be useful. Still, for a version tool, the absence of output schema is acceptable given the clear intent.

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 (schema is empty with no properties). With 100% description coverage (the description explicitly mentions the information returned), there is nothing about parameters to be ambiguous or undocumented. The description succinctly identifies what the tool produces.

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 'Show the current MCP platform and adapter versions' is unambiguous and clearly states the tool's action ('Show') and its subject ('versions'). It directly maps to the tool name 'show_version', making the purpose immediately obvious even without the title.

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 tool takes no parametersache, so there are no prerequisites or invocation complexity. The description implies it can be called directly to retrieve versioning information, but it doesn't explicitly state when it's appropriate to use or if any setup is required. Still, for a version display utility, this is straightforward and requires no 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, idempotentHint=true, destructiveHint=false, covering safety expectations. The description adds behavioral context beyond annotations by detailing exactly what the tool reports (connected accounts, number of catalog tools per MCP), which is not present in the structured fields. It does not contradict annotations and provides useful operational insight about 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.

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

The description is a single sentence, extremely concise, and front-loaded with the verb 'Returns' followed by a clear list of what is returned. Every word earns its place, no filler or redundancy.

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

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

There is no output schema, so the description must cover what the tool returns, which it does explicitly: installed MCPs, connection status, accounts, and catalog tool counts. For a diagnostic tool with no parameters and strong annotations (readOnly, idempotent), this is complete enough. It doesn't over-specify structure, but the returned fields are sufficiently identified.

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

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

There are zero parameters erk going on, and schema description coverage is 100% (empty schema). With no parameters to document, the baseline is 4. The description correctly lists the returned fields, which indirectly indicates what parameters are not needed. No additional parameter explanation is 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 what the tool does: returns the toolkit state including installed MCPs, connection status, connected accounts, and catalog tool counts. It uses a specific verb ('Returns') and defines precise resource scope (current toolkit state), distinguishing it from sibling tools like show_version which focus on version. This is a specific, unambiguous purpose.

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 usage context: when you need to inspect the toolkit's current configuration and connections. It doesn't explicitly list alternatives or exclusions, but it's clear that this is the diagnostic/status tool. A slight improvement would be mentioning when to use it over similar tools like 'show_version', but the context is sufficiently clear without exclusions.

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