IBAMA Débitos

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

Beyond the annotations (idempotent, not destructive, not read-only), the description discloses important behavioral traits: a config token is permanent and non-expiring, while a pasted token is session-only. It also reveals that calling with no args returns the login link. This adds meaningful context about session vs. permanent authentication and side effects, though it could further clarify what happens after login (e.g., connection state).

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 cohesive paragraph that front-loads the purpose and then explains two usage modes. Every sentence contributes useful information, and it avoids unnecessary filler. It is slightly long but appropriate for the auth flow it describes.

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 auth tool with one optional parameter and no output schema, the description covers the full workflow: obtaining the token via browser, configuring it in the server config for permanence, or passing it as a session token. It also explains no-arg behavior. It is complete enough for an agent to understand the tool's purpose and invocation.

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 an optional 'token' string with no description. The description compensates by explaining the token parameter: it should be a JWT pasted by the user, and the tool can also be called with no arguments to get the link. This gives clear semantics for the parameter and the no-arg invocation, well beyond the schema.

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

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

The description clearly states the tool's purpose: to authenticate IDE agents to MCP.AI by either generating a login link or accepting a pasted token. It uses specific verbs like 'log in' and 'copy the access token,' and explains the resource (MCP.AI server). However, it does not explicitly contrast with sibling tools like 'connect,' so it lacks direct sibling differentiation.

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 clear context for usage: it targets IDE agents (Cursor, etc.) and gives two usage paths—config-based permanent token or session-only token via this tool. It explains when to call with no args (to get the link) versus with a token (to complete login). It does not explicitly state when not to use this tool or mention alternatives, but the guidance is actionable and context-rich.

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 clear. The description adds behavioral context by specifying the two return states (authenticated:true with empty pending[] vs connect_url with per-install URLs), which goes beyond the annotations and helps set expectations.

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 main purpose, and contains no redundant information. Every sentence adds value by explaining the two possible outcomes.

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 status tool with no output schema, the description adequately covers the two main scenarios (all connected vs credentials missing). It does not mention a partial-connection state, which could be a minor gap, but overall it is complete enough for its complexity.

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

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

There are zero parameters, so the baseline for parameter semantics is 4. The description correctly avoids adding parameter details since none exist, and the schema coverage is trivially 100%.

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 connection status and URLs, and differentiates from siblings like authenticate by focusing on status rather than initiating authentication. It also describes the two distinct output states, making the purpose specific and 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 the tool is used to check connection status and retrieve URLs when credentials are missing, providing clear context for when to invoke it. It does not explicitly name alternatives or when not to use it, but the behavior described is sufficient guidance for standard use cases.

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

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

Beyond annotations (readOnly, idempotent, non-destructive), the description adds practical details: payment model, public access, and legal compliance (LGPD). It does not mention response format or rate limits, but adds useful operational 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?

Four sentences, each adding distinct information: purpose, payment/hosting, public access, and LGPD. Slightly wordy on the legal disclaimer, but the core action is front-loaded and no sentence is pure filler.

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 lookup tool with 3 params and no output schema, it covers the essential aspects: what it does, access, payment, and legal framing. Missing is a description of the 'completo' parameter and the response structure, but the overall context is 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 coverage is 0%, so the description must compensate. It explains 'CPF ou CNPJ' and their mapping to pessoa/empresa, but leaves the optional 'completo' parameter completely undefined, creating an ambiguity. Partial parameter semantics.

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 'Emite a certidão negativa de débitos ambientais do IBAMA' using CPF/CNPJ, with a specific verb and resource. It is easily distinguished from unrelated siblings like authenticate, marketplace, and 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 provides clear context: hosted platform, no credentials, pay-per-consultation with prepaid credit, and public data access with LGPD responsibility. It doesn't name alternatives explicitly, but the tool is unique, making the intended use evident.

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

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

The description adds rich behavioral context beyond the annotations: invoke runs tools even when not installed, one-off without bloat; returns connect/checkout links under credential/payment conditions; and search/describe flag installation state. These details significantly exceed the minimal hints provided by annotations and disclose important edge-case behaviors.

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 organized, using 'Core flow:' and 'KEY:' markers to highlight essential guidance. It is longer than ideal for a single paragraph, but every sentence carries useful information, making it efficient despite lacking bullet points.

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 all major action branches—search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library—with context on when to use each. It omits the 'resume' action and does not describe return value structures, but for a tool with 23 parameters and no output schema, it is quite comprehensive.

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 compensates by explaining the main action values (search, describe, invoke, install) and linking them to parameters like query, mcp_id, tool_id, and arguments. However, it does not explain many secondary parameters (immediate, tier_slug, cancel_reason, etc.), though some are self-explanatory or have enums.

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 defines the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It specifies the core search→describe→invoke flow, distinguishing it from sibling tools like authenticate or ibama_debitos_consultar, which are unrelated to marketplace 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 explicitly contrasts invoke vs. install: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also differentiates list_tools as listing only callable tools and notes that writes require workspace owner/admin, providing clear when-to-use and when-not-to-use 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 cover safety traits (idempotent, non-destructive, not read-only). The description adds that the conversation array is used for reproduction, but it does not detail side effects, response behavior, or rate limits, which is acceptable given 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?

Two concise sentences, front-loaded with purpose, no unnecessary details. Efficient and easy to scan.

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 is adequate for a simple feedback tool but lacks details on required message content, expected response, or how the report is processed. Given no output schema, more context would help but is not critical.

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 no schema descriptions, the description must compensate. It explains the 'conversation' parameter's role but leaves 'message' (required) and 'context' unexplained. It also calls conversation an 'array' while the schema types it as a string, which may cause confusion.

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: reporting a bug, missing feature, or feedback. It uses a specific verb ('report') and resource types, distinguishing it from sibling tools like authenticate or marketplace.

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 reporting issues and provides guidance to include the conversation array for reproduction. However, it does not explicitly mention alternatives or exclusions, though none are needed given the distinct 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, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds the specific subject (MCP platform and adapter versions), which is consistent with the annotations and completes the behavioral picture.

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 that fully states the tool's action and target. No filler or 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?

Given the tool has no parameters, no output schema, and a simple read-only function, the description sufficiently covers all relevant aspects. No additional details are needed for an agent to invoke it 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 input schema has zero parameters, so schema coverage is trivially 100%. The baseline for a no-parameter tool is 4, and the description adds no unnecessary param details, which is appropriate.

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 ('Show') and clearly identifies the resource ('current MCP platform and adapter versions'). This unambiguously distinguishes it from sibling tools like authenticate, connect, and toolkit_info.

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

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

The intended use is clear: call this tool to inspect the current MCP platform and adapter versions. It doesn't name alternatives or exclusions, but given the tool's simplicity and unique purpose, no further guidance is necessary.

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 data scope (installed MCPs, connection status, accounts, tool counts), which clarifies the behavioral output but doesn't disclose additional traits like rate limits or error behavior.

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 that efficiently lists the return contents without redundant phrasing. It front-loads the action ('Returns') and then itemizes the data.

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 read-only status tool with no parameters and no output schema, the description provides sufficient detail about the return value, covering the main categories. It doesn't need additional context given the annotations and simple complexity.

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

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

The tool has zero parameters, so the schema is trivially 100% covered. The baseline for 0-parameter tools is 4; the description doesn't need to add parameter semantics.

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 'Returns' and clearly identifies the resource ('current toolkit state'), enumerating the exact components returned (installed MCPs, connection status, accounts, 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 for checking toolkit status, but it doesn't explicitly state when to use it vs alternatives such as show_version or connect. It provides clear context (returning status info) but no exclusions or alternative directions.

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