MPT CE: Certidão Negativa de Feitos

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

Beyond the annotations (idempotent, non-destructive), the description discloses the main behavioral trait: calling with no args returns a login link, while passing a JWT completes a session login. It does not mention error cases or exact side effects, but for this simple auth flow it provides meaningful behavioral context that annotations don't cover.

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 run-on block that mixes user instructions, configuration advice, and API call details. It contains all necessary information but is not tightly structured; it could be split into clearer sentences or bullets. It is not overly verbose, but it could be more 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?

For a tool with one optional parameter and no output schema, the description covers the main usage paths: no-args returns a link, token provides session login, and a config header provides permanent login. It omits explicit return value details and error handling, but the tool's low complexity means the description 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 schema coverage at 0% and a bare { token } property, the description compensates by explaining that token is an optional JWT and what happens if omitted. It explicitly shows the expected call shape { token: '<jwt>' }, giving the parameter semantic meaning 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 states a specific verb+resource: authenticate to MCP.AI for IDE agents, and clearly distinguishes the tool from siblings like 'connect' and 'report_bug'. It also explains the two usage modes (permanent via header config, session via token), making the purpose unmistakable.

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 when-to-use guidance: use it either with no args to get a login link, or with a token for session-only login. It recommends the config header approach as the 'best' permanent option. It lacks explicit exclusion of alternatives, but the usage context is clear and sufficient.

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 behavior. The description adds valuable conditional behavior: authenticated:true with empty pending[] when fully connected, and connect_url plus per-install URLs when credentials are missing. No 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?

Two tight sentences with the core purpose front-loaded. Every sentence adds meaningful behavioral detail; 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?

For a parameterless read-only status tool, the description is complete: it covers the happy path, the missing-credentials case, and the returned fields. With strong annotations and no output schema, this is sufficient guidance.

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 carries no parameter burden. Baseline is 4 for zero-parameter tools, and the description appropriately focuses on output semantics rather than inputs.

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 the resource ('connection status and URLs'). It also distinguishes itself from sibling tools like 'authenticate' by focusing on status inspection rather than performing 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: call this to check connection status and obtain URLs. However, it does not explicitly state when to prefer this over alternatives like 'authenticate' or 'toolkit_info', nor does it mention 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?

Adds rich behavioral context beyond the sparse annotations: explains one-off execution without installation, generation of connect and checkout links, workspace owner/admin requirements for writes, and installed_in_toolkit vs workspace flags. No contradiction with annotations; this is a model of 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?

Extremely dense and front-loaded with the core flow, but presented as a single unbroken block of text. Every sentence adds value, though a more structured layout (bullet points, sections) would aid scanability. Slight deduction for the wall-of-text presentation.

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 tool with 23 parameters, 14 actions, no output schema, and minimal annotations, the description is exceptionally complete. It covers main flows, side effects, permission requirements, billing/auth edge cases, and even the prompt library subset, giving an agent nearly everything needed to use the tool 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?

Despite 0% direct parameter documentation, the description significantly clarifies the meaning and usage of core parameters (action values, tool_id, arguments, prompt_* fields) through the core-flow narrative. However, several parameters (e.g., tier_slug, conversation, immediate) remain unexplained, slightly reducing compensation for the coverage 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 defines the marketplace as the official MCP catalog and execution engine, with a specific core flow (search → describe → invoke). It explicitly distinguishes sub-operations and differentiates from sibling tools (e.g., invoke vs install vs list_tools), achieving high 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?

Provides explicit guidance on when to use install vs invoke ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use'), and when to use report_bug, request_mcp, and list_tools. It clearly states context 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 readOnly, idempotent, and non-destructive behavior. The description adds valuable context beyond those: hosting, prepaid credit cost, lack of platform credential requirements, public data source, and LGPD data-controller responsibilities. No contradiction with annotations is 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 front-loaded with the primary purpose, followed by operational, financial, and legal context. Each sentence delivers distinct information, and there is no filler or redundancy. It is appropriately compact given the multiple caveats involved.

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 hosting, payment, source, and legal obligations well. However, with no output schema and no parameter guidance, the agent lacks a complete picture of what inputs to provide and what the response will look like. The context is sufficient for understanding the tool's place but not fully actionable.

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 lists cpf and cnpj as string parameters with zero description coverage. The tool description does not explain their format, whether both/one must be provided, or their relationship to the certificate query. With 0% schema coverage, the description was expected to compensate but does not address the parameters at all.

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: consulting an official 'Certidão Negativa de Feitos' from MPT CE. The verb 'consulta' and the specific resource distinguish it from sibling tools like authenticate, marketplace, and report_bug. The acronym MPT CE is not expanded, but the core action and subject are 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 conveys operational context: no platform credentials, prepaid credit required, official Brazilian source, and LGPD responsibilities for the client. However, it does not explicitly state when to use this tool versus alternatives, nor does it indicate whether CPF or CNPJ should be supplied exclusively or optionally. Usage is implied rather than clearly guided.

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 readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description does not contradict these and adds a behavioral note about including the conversation array for reproduction. It does not describe side effects (e.g., where the bug report goes), rate limits, or auth requirements, but with annotations covering the safety profile and idempotency, the description adds sufficient context beyond the structured data.

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 front-loaded with the primary purpose. The first sentence states the core functionality, and the second adds a critical usage detail. No filler or redundant information is present; every sentence 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?

The tool is simple (3 parameters, no output schema, no nested objects). The description covers the main purpose and one important parameter (conversation), but it lacks explanation of the 'message' parameter (required) and 'context', and it does not describe what the tool returns or potential error conditions. For a feedback tool, this might be sufficient, but it leaves gaps in comprehension for an AI agent.

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 for parameter explanations. It mentions the 'conversation' parameter explicitly, advising to include recent messages for reproduction. However, it does not explain the required 'message' parameter or the 'context' parameter. The description adds meaning only to one of the three parameters and leaves the others undefined, which is inadequate given zero 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 states the tool's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('report') and identifies the resource (bug/feature/feedback). None of the sibling tools (authenticate, connect, marketplace, etc.) overlap with this purpose, so it is well differentiated.

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 a concrete usage instruction: 'Include the conversation array with recent messages for reproduction.' However, it does not explicitly state when to use this tool versus alternatives, though no obvious alternatives exist among the siblings. The guidance is implied rather than explicit, and no exclusions or conditions are given.

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, which fully cover behavioral expectations. The description's 'Show' aligns with these annotations and adds no further side-effect details. Since the annotation bar is high and the description is consistent, it is transparent, though it does not add extra context 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 a single, clear sentence with no unnecessary words. It is front-loaded with the main action and object, adhering to concise and structured communication.

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 is simple with no output schema or complex behaviors. The description sufficiently conveys the purpose and result without needing to explain return values or edge cases. Given the low complexity, the description is 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?

The tool has zero parameters, so the input schema is trivially 100% covered. There is no parameter semantics to describe, and the description correctly omits any parameter details. This is an ideal scenario for this dimension.

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 explicitly states the tool shows the current MCP platform and adapter versions. This is a specific verb ('show') and resource ('versions'), clearly distinguishing it from sibling tools like authenticate, connect, or marketplace, 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 does not explicitly state when to use this tool or provide alternatives. However, given that no sibling tool serves a version-query purpose, the intended usage is implied. Still, the lack of explicit guidance (e.g., 'Use to check compatibility or debug version issues') keeps it at an adequate but not excellent level.

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 expands on the readOnlyHint annotation by detailing what 'state' includes: installed MCPs, connection status, connected accounts, and catalog tool counts. This adds meaningful context about the response content and read-only behavior without contradicting any 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 verb and object. Every word contributes meaning, and there is no redundancy or filler. It perfectly balances brevity with necessary detail.

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 and no output schema, the description fully covers what the agent needs to know: the tool returns a snapshot of toolkit state with specific fields. There is no ambiguity about input or side effects, and the behavior is fully disclosed without being verbose.

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 there are no semantics to explain. Per the rubric, a baseline of 4 is appropriate for no-parameter tools. The description does not need to add parameter info 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 begins with the verb 'Returns' and specifies the exact resource: 'the current toolkit state'. It lists concrete details (installed MCPs, connection status, accounts, catalog tool counts) that clearly distinguish it from sibling tools like authenticate or connect. This leaves no ambiguity about the tool's function.

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 querying toolkit state. While it doesn't explicitly contrast with siblings, the action and resource are specific enough that an agent can infer when to invoke it. No exclusions or alternatives are mentioned, but none are strictly needed given the tool's self-contained nature.

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