CARF: Processo

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

Explains behavioral traits beyond annotations: permanent vs session-based login, the use of Authorization header, JWT token format, and no-arg behavior to retrieve a link. This adds significant value beyond the basic flags (readOnlyHint=false, idempotentHint=true) 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?

Two sentences, but dense and slightly rambling. Covers all key points without waste, though could benefit from bullet points or clearer separation of the three usage modes. Still efficient for the information conveyed.

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?

Adequate for a simple authentication tool with one parameter. Describes both input modes and the permanent configuration path. Doesn't mention response format, but no output schema is present, and an agent can infer the tool returns a link or confirmation. Missing error handling or timeout details, but not essential for basic use.

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 only defines 'token' as an optional string with no description. The description fills this gap by explaining it expects a JWT pasted by the user, and that omitting it retrieves a login link. Fully compensates for the 0% schema 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 ties to authentication ('log in', 'access token') and specifies the resource (MCP.AI for IDE agents). It distinguishes from siblings by focusing on authentication, though the phrasing 'MCP.AI for IDE agents...' is slightly indirect and could be crisper.

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 when-to-use guidance through three scenarios (permanent config, session token, no-arg) and practical instructions for each. It doesn't explicitly contrast with alternatives but offers enough context for an agent to know when to call 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 declare readOnlyHint=true and destructiveHint=false. The description adds valuable context: payment required (prepaid credit), no platform credentials needed, data is non-confidential (same as citizen-accessible), and LGPD compliance responsibilities. This goes beyond the annotations and informs the agent about cost and data sensitivity.

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 sentence with multiple clauses covering payment, credentials, data source, and legal compliance. It's not overly long but not well structured. It is front-loaded with the core purpose ('Processo, consulta') but then dives into legal and commercial disclaimers, which could be separated. It earns a mid score because it's efficient but a bit jumbled.

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 schemacustom, and the description does not mention what the response contains (e.g., process details, status, dates). With 5 parameters and zero schema coverage, the description should compensate by explaining expected inputs and outputs, but it only gives high-level context about data source and legal responsibility. Missing parameter explanations and pagination/result format info make it incomplete.

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 5 parameters and schema description coverage is 0%. The description does not explain any parameter semantics (e.g., what 'cpf', 'cnpj', 'data_fim' mean, or how they relate to the query). Since the schema has no descriptionscommunication, the description completely fails to compensate. The only hint is the word 'processo' but it doesn't clarify the combination logic.

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 performs a query ('consulta') for CARF process information from official sources. It identifies the resource (CARF processes) and the action (consult), though it doesn't explicitly distinguish from direct siblings since the sibling list is generic tools like authenticate and connect, so this is acceptable.

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 context on how to use it: hosted by the platform, no credentials needed, pay per query, and that it consults official sources. However, it doesn't explicitly state when to use it versus alternatives or when not to use it. It implies usage for looking up CARF process info but lacks clear exclusion 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, idempotentHint, and destructiveHint false. The description adds meaningful behavioral detail beyond those annotations by explaining conditional return states and the presence of connect_url and per-install URLs. No contradiction exists.

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

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

The description is two sentences, front-loaded with the primary purpose, and contains no filler. Every sentence adds useful information about return states and URL behavior.

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 zero-parameter, read-only, idempotent status tool with no output schema, the description fully covers the main return scenarios and the meaningful fields returned. It gives enough detail for an agent 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.

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, so parameter semantics are effectively not applicable. The description correctly omits parameter details, and the baseline score of 4 applies.

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 'Returns connection status and URLs,' which clearly states the verb and resource. It also distinguishes itself from the sibling 'authenticate' tool by focusing on status/URL retrieval rather than authentication 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?

The description provides useful context through conditionals ('When all providers are connected...' and 'When credentials are missing...'), making the tool's behavior clear. However, it does not explicitly name alternatives or state when to use this tool instead of 'authenticate,' so exclusion guidance is implied rather than explicit.

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?

Beyond the sparse annotations, the description discloses critical behaviors: invoke runs tools without installing them, missing credentials return a connect link, empty wallet returns a checkout/top-up link, installs make tools permanent, and writes require owner/admin permissions. This is far more behavioral detail than the annotations alone provide, 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 long but well-organized around a core flow: search → describe → invoke, then install vs invoke, then auxiliary actions, then the prompt library. It is front-loaded with the most important behavior. Some redundancy exists, such as 'without adding the MCP to the toolkit and without bloating the tool list,' and the resume action is omitted, so it is not perfectly concise.

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, 23 params, no output schema, and sparse annotations, the description is remarkably complete: it covers discovery, execution, one-off vs permanent installation, auth, billing, permissions, auxiliary actions, and the prompt library. It misses a few less-central details like the resume action and detailed semantics for many optional parameters, but it is sufficient for the primary use cases.

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 heavily. It does add meaning for core params like action, tool_id, arguments, and prompt_vars, but many params remain unexplained: limit, query, immediate, resume, cancel_reason, cancel_comment, report_context, request_details, and several prompt fields. The description covers the primary workflow but leaves significant ambiguity for less-common actions.

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 catalog and execution layer, with a specific flow: search MCPs by intent, describe profiles, and invoke tools. It distinguishes itself from the sibling tools by explaining its role as the in-platform way to discover and run MCPs, and even differentiates internal sub-actions like search_prompts vs search.

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 invoke for one-off execution, install only to make an MCP permanent, prefer invoke when the MCP is not installed, subscribe/cancel for billing, report_bug for feedback, and request_mcp for new tooling. It also states that writes require workspace owner/admin, which is important when deciding whether to attempt an action.

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 idempotentHint=true (calling repeatedly yields same result) and destructiveHint=false (non-destructive). The description does not elaborate on these aspects; it simply states the action. Without annotations, the description carries the burden, but here it adds no extra behavioral context beyond repetition of the purpose, so transparency is minimal.

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

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

The description is two sentences, concise and to the point. It front-loads the purpose and then adds a key detail about the conversation array. No unnecessary 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 it's a simple reporting tool with 3 parameters and a good annotation set, the description covers the core purpose and one parameter, but missing explicit guidance on the 'context' parameter and detailed expectations for the message. Complete enough for a straightforward action, but could be slightly richer given the zero schema coverage.

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 clarify parameters. The description mentions 'message' and 'conversation' but the schema includes also 'context' with a default. The description does not explain the 'context' parameter at all, and only partially explains 'conversation'. It adds some value by indicating that the conversation array aids reproduction, but it fails to cover all params.

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: to report bugs, missing features, or send feedback, which distinguishes it from sibling tools like 'marketplace' or 'show_version'. It also mentions including a conversation array for reproduction, adding specificity.

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 implicitly communicates when to use this tool (for reporting issues or feedback) but does not explicitly contrast with alternatives or provide exclusions. It mentions including conversation data, but could better clarify prerequisites or alternative reporting channels.

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 safety profile is covered. The description adds no additional behavioral details (e.g., what exactly is returned, potential errors). Given annotations, a 3 is appropriate – it doesn't contradict, but adds minimal extra value.

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?

Single sentence, perfectly concise and front-loaded. Every word earns its place.

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 version query with no parameters and no output schema, the description fully captures the purpose. No additional 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?

No parameters exist, so schema coverage is 100% and there is nothing to explain. Baseline 4 for zero 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 shows the current MCP platform and adapter versions, using a specific verb ('Show') and resource. It is unambiguous and distinguishes itself from sibling tools, which are all action-oriented (authenticate, report_bug, etc.). No ambiguity or tautology.

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 purpose is self-evident for a version query tool; the description implies usage (check versions) but doesn't explicitly state when to use vs alternatives. However, no real alternatives exist among siblings, so the basic context is clear.

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, covering safety. The description adds behavioral context by specifying what the return value will contain (state details), which goes beyond the annotations. It doesn't contradict 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 a single, well-structured sentence that front-loads the purpose ('Returns the current toolkit state') and then lists the specific data categories. It is concise with no 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?

For a no-parameter, read-only query tool, the description fully explains what the user can expect from the output (state components). With no output schema, it adequately covers the needed information. It doesn't address error cases, but those are minor for a state query. Given the simplicity, it's 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?

There are zero parameters, so the description cannot add parameter semantics. Per the rubric, 0 params gives a baseline of 4. The description doesn't need to explain parameters and adds nothing beyond what's absent.

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 'current toolkit state' and enumerates specific elements (installed MCPs, connection status, connected accounts, catalog tool counts). This distinguishes it from sibling tools like authenticate or connect, which are actions rather than state inquiries.

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 state but does not explicitly state when to use it over alternatives or mention any exclusions. Given the sibling tools, it's obvious it's for informational purposes, but the description doesn't provide explicit guidance on when to call it or when not to.

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