IBAMA Regularidade

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

Annotations indicate idempotent and non-destructive behavior. The description adds context about the two modes (permanent via config header, session-only via token) and explains that no args yields a login link. It also reveals the token is a JWT, going beyond the schema.

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

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

The description is slightly verbose with a run-on second sentence, but it is front-loaded with the target audience and purpose. All sentences add value, though the structure 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?

Given the tool's simplicity (one optional param, no output schema), the description covers the authentication flow, permanent vs session modes, and how to obtain the token. It is complete enough for an agent to invoke correctly, though it doesn't detail post-auth behavior.

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 coverage is 0% yet the description fully explains the only parameter 'token': it is a JWT passed in the call for session login, and with no arguments the tool returns a link. This compensates completely for the lack of schema description.

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 authenticates IDE agents via browser login and provides an access token. It distinguishes itself from sibling tools by focusing on authentication flow and token management, with specific verbs like 'log in' and 'copy the access token'.

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 provides clear usage guidance: recommend adding the token to server config for a permanent connection, or pasting it for session-only login. It also explains when to call with or without arguments, though it does not explicitly contrast with 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 readOnly, idempotent, and non-destructive traits. The description adds value by specifying the two behavioral states: returns authenticated:true with empty pending[] when connected, or connect_url when credentials are missing. This goes beyond the annotations, though it does not cover partial connection states or potential errors.

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 long, front-loads the main purpose, and every sentence adds specific behavioral detail. 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?

The tool has no parameters and no output schema, so the description carries full responsibility for conveying expected returns. It adequately explains the two outcome states, making it complete for the tool's simple scope. The presence of sibling tools does not add complexity that would require more detail.

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, and the baseline for a no-parameter tool is 4. The description does not need to explain parameter semantics since there is no input schema beyond an empty object.

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 'Returns connection status and URLs' with a specific verb and resource, and distinguishes from siblings like 'authenticate' by focusing on status/URLs rather than performing authentication. It also details conditional behavior, which makes its purpose 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?

The description implies when to use the tool by explaining conditional outcomes (all providers connected vs. credentials missing), which helps the agent decide based on the state. It does not explicitly exclude alternatives like 'authenticate', but the context makes the tool's role 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?

Beyond the readOnly/idempotent annotations, the description adds meaningful behavioral context: no credentials needed, prepaid credit per consultation, public-access nature of the data, and the client's role as data controller under LGPD. These details help the agent set user expectations and understand compliance implications.

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 and well-structured: first sentence states the core purpose, the second covers payment/hosting, and the third addresses public access and legal responsibility. Every sentence earns its place with no filler 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 covers purpose, cost, access class, and legal context well, which is strong for a simple public lookup. However, with no output schema, the description should provide more about the expected return ('completo' behavior, response format, or certificate details), and the CPF/CNPJ requirement mismatch further harms completeness.

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 coverage is 0%, so the description must compensate, but it only partially does. It clarifies that Cpf and Cnpj are person/company identifiers, yet it says 'ou' (or) while the schema lists both as required. The optional 'completo' parameter is not explained at all, leaving a semantic gap and a potential contradiction.

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 specific action ('Emite') and resource ('certificado de regularidade ambiental') plus the target audience (pessoa ou empresa a partir do CPF ou CNPJ). This distinguishes the tool from the unrelated sibling tools and makes the purpose immediately obvious.

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 selection context: it is hosted by the platform, requires no credentials, is paid per query, and consults only public official data. It explicitly excludes private or confidential data and mentions LGPD responsibility. It does not name alternative tools, but no direct sibling competitor exists, so the guidance is adequate.

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 are minimal (readOnlyHint false, destructiveHint false, openWorldHint true), so the description carries the full burden. It discloses that invoke works even on non-installed MCPs, returns connect/checkout links in specific scenarios, and that writes require workspace owner/admin. It also explains toolkit vs workspace installed flags, going well beyond the annotations.

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

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

The description is long but densely packed with unique information, with no redundant sentences. It front-loads the primary flow and then covers edge cases, permissions, and the prompt library. A more structured layout (e.g., bullet points) might improve scannability, but the content is concise relative to the tool's 14-action surface.

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 high complexity, the description covers all major behaviors: search/describe returns profiles, invoke returns links, list_tools enumerates callable tools, and the prompt library actions are described. It also addresses permissions, installed status flags, and the one-off vs permanent distinction, making it sufficient for safe and correct 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?

With 23 parameters and 0% description coverage, the description must compensate. It does a strong job by explaining core parameters (action, tool_id, mcp_id, arguments, prompt_* variables) through the workflow examples. However, several parameters like immediate, tier_slug, request_details, and cancel_reason are never explicitly mentioned, so the agent must infer their meaning from names and enums alone.

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 immediately 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 lists all action variants, clearly distinguishing marketplace from siblings like report_bug or connect. The purpose is unmistakable and highly specific.

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 when-to-use guidance for each action: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and it explains the core flow step-by-step. It also contrasts with list_tools and covers billing, reporting, and request actions, providing alternatives and 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 already indicate idempotentHint=true, readOnlyHint=false, destructiveHint=false. The description adds context that the conversation is needed 'for reproduction,' which gives some behavioral insight, but it doesn't disclose any side effects or expected outcomes beyond what annotations imply. It does not 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?

Two concise sentences. The first states the purpose, the second provides an actionable guideline. Every word earns its place; no fluff 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?

For a simple 3-parameter tool with no output schema, the description sufficiently covers what the tool does and what to include. The main gap is the lack of detail on the 'message' format, but overall it is adequate for an agent to use 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?

Schema description coverage is 0%, so the description must compensate. It clarifies that 'conversation' should contain recent messages as an array (though schema defines it as string, likely JSON). It does not explain the required 'message' or optional 'context' fields. Partial compensation, but with a potential type ambiguity.

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 resource ('bug, missing feature, or feedback'), clearly distinguishing the tool's purpose from siblings which are unrelated (authenticate, marketplace, etc.). It fully states what the tool does without ambiguity.

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?

Explicitly states when to use the tool ('Report a bug, missing feature, or send feedback') and provides a concrete instruction ('Include the conversation array with recent messages for reproduction'). No competing alternatives exist, so no exclusions are needed.

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 known. The description adds the specific outputs (platform and adapter versions) but no additional behavioral context beyond that, which is acceptable but not exceptional.

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?

A single, direct sentence conveys the entire purpose without any filler or unnecessary details.

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-check tool with no parameters and comprehensive annotations, the description is fully sufficient. It states exactly what is returned and leaves no ambiguity.

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 input schema is trivially complete. The description doesn't need to add parameter details, and the baseline for zero-parameter tools is 4.

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 'show' and names the exact resources ('current MCP platform and adapter versions'). This is clearly distinct from sibling tools like authenticate, connect, 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 makes the use case obvious: check platform and adapter versions. No explicit alternatives are needed for such a simple query, and the context is clear enough.

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, establishing a safe read operation. The description adds valuable context about what the returned toolkit state includes (installed MCPs, connection status, accounts, catalog tool counts), going beyond the annotations to clarify the nature and granularity of the 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, well-structured sentence that immediately states the verb ('Returns') and resource, followed by a clear list of the state components. Every word contributes value, with no redundancy or unnecessary details.

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 info tool with no output schema, the description fully captures what the tool returns and its scope. It covers the key aspects of toolkit state that an agent would need to decide whether to call it, and no additional context is necessary 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 input schema has zero parameters, making parameter semantics trivially covered. Per the rubric, 0 params earns a baseline score of 4, and the description appropriately omits any parameter explanations since there are none.

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 with a specific verb ('Returns') and a detailed resource ('current toolkit state'), enumerating the exact contents: installed MCPs, connection status, accounts, and catalog tool counts. This distinguishes it from sibling tools like authenticate or show_version, which serve different purposes.

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 by describing what info is returned, but it does not explicitly state when to use this tool versus alternatives like show_version or ibama_regularidade_consultar. No exclusion criteria or alternative references are given, so the agent must infer the appropriate context.

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