Prefeitura MG Uberaba: Certidão Negativa de Débitos

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

The description discloses behavioral aspects: it returns a link when called with no args, accepts a token for session login, and mentions config-based permanent connection. However, annotations already indicate idempotentHint=true and destructiveHint=false, but the description adds practical context about the two modes (session vs permanent). It does not contradict annotations. Slightly less than 5 because it doesn't detail what happens after successful auth (e.g., validation, response).

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 paragraph. It is somewhat long but each sentence adds critical info about the two authentication methods. It is front-loaded with the main purpose and then covers alternatives. Slightly verbose but not wasteful; could be split into bullet points for clarity, but it's acceptable.

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 (authentication flow with two modes) and that there is no output schema, the description covers the essentials: how to initiate, what to do with the token, and the permanent config option. It lacks details about potential error cases or what happens after successful token submission, but for a tool with a single optional parameter, it is fairly complete. Siblings like 'connect' and 'marketplace' are distinct, so no confusion.

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% (no description in schema), but the description thoroughly explains the single parameter 'token': it is a JWT to paste for session-only login, and optional (call with no args to get the link). This fully compensates for the lack of schema description. Score 4 because it provides clear semantics beyond the schema's bare 'type: string'.

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: authentication for MCP.AI in IDE agents, providing a browser login link and accepting a token. It distinguishes itself from siblings like 'connect' and 'marketplace' by focusing specifically on authentication flow.

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: for logging in via browser and copying the access token. It also gives alternatives: adding the token to config for permanent connection vs. pasting it here for session-only login. Clearly states when to call with or without args.

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, and the description aligns with those by purely reporting state. The description adds useful behavioral detail beyond annotations: exact return conditions such as authenticated:true, empty pending[], and connect_url for toolkit/install-level URLs.

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 core purpose, and each sentence adds meaningful detail on the two possible connection states. There is no redundancy with the annotations or schema.

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 no-parameter, read-only status tool, the description covers the main outcome fields and two relevant scenarios. It does not explicitly describe a partial-credential state or name every return field, but the given conditions ('all providers connected' and 'credentials missing') provide sufficient operational context.

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 the schema coverage is 100%, so there is no parameter info the description needs to add. The baseline of 4 applies because no parameters exist and the description correctly focuses on behavior rather than inventing param details.

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 and object ('Returns connection status and URLs') and clarifies the tool's role as a status/read-only endpoint. It also distinguishes behavior by credential state, making it easy to tell apart from sibling tools like 'authenticate', which presumably initiates the auth flow.

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 clear context: users should call it to check whether providers are connected and to obtain connect URLs when credentials are missing. It does not explicitly say 'do not use this to authenticate' or name alternative tools, so it lacks a full exclusion/alternative statement.

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?

Discloses that invoke runs tools even if not installed (one-off), may return connect or checkout links, and that writes require workspace owner/admin—beyond what the annotations (readOnlyHint:false) indicate. It also explains the distinction between installed_in_toolkit vs installed_in_workspace and the prompt library's behavior, all without contradicting 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 lengthy but dense; every sentence adds value for a complex, multi-action tool. It is a single block without bullet points, which hurts scannability, but the flow is logical and there is no redundant or filler content. Given the tool's scope, the length is justified, though better structure would improve clarity.

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 large parameter set, no output schema, and many action branches, the description covers the essential workflows: discovery, invocation, installation, billing, and the prompt library. It explains edge cases like credential/auth requirements, wallet top-up, and owner/admin restrictions—sufficient for an agent to understand what to expect and how to proceed.

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 coverage, the description carries the burden of explaining the key action-driven parameters (action, mcp_id, tool_id, arguments, prompt fields) and how they fit the workflows. It does not document every parameter individually, but it explains the core ones and the defaults (e.g., action default 'search') through the narrative. This is adequate but not exhaustive, so a small deduction.

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 it is the official mcp.ai marketplace and explains its core functions—discovering, describing, and invoking MCP tools—while also covering the prompt library. It distinguishes itself from sibling tools by explicitly naming its actions and the flow (search → describe → invoke) that sets it apart from simpler tools like authenticate 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?

Provides explicit guidance on when to use invoke vs. install (permanent vs. one-off), when to use search/describe for discovery, and how to handle connect/checkout flows. It also mentions alternatives like list_tools and subscribe, and distinguishes between marketplace actions and prompt-library actions, so an agent knows exactly when to choose this tool over others.

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 and idempotent annotations, the description discloses meaningful behavioral details: it is a paid consultation using prepaid credit, requires no platform credentials, accesses only public non-secret data, and places LGPD-related controller responsibility on the client. This materially clarifies what happens and the obligations involved.

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 and front-loaded with the core purpose, then adds relevant operational context about payment, confidentiality, and LGPD. A few phrases are slightly boilerplate or redundant, but every part contributes useful context.

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 read-only query tool, the description covers purpose, official source, payment, authentication expectations, and data confidentiality. The main gap is parameter behavior, especially because the schema provides no descriptions and there is no output schema to compensate.

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 has two unannotated string parameters, cpf and cnpj, with 0% description coverage and zero required parameters. The description does not explain whether one must be provided, whether both are allowed, which identifier applies in which scenario, or what formats are accepted. This makes correct invocation ambiguous.

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 is a consulta (query) of a Certidão Negativa de Débitos (CND) from Prefeitura MG Uberaba, using an official source. This is specific enough to distinguish it from the generic sibling tools like authenticate, connect, 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 usage context: no platform credentials are needed, queries are paid via prepaid credit, and only official non-confidential data is accessed. It does not explicitly name alternative tools or list exclusion cases, but the context is strong enough for correct selection.

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 (mutating) and idempotentHint=true (safe to repeat). The description adds the useful guidance about including the conversation for reproduction but does not disclose any side effects (e.g., system notifications, rate limits) beyond that. No contradiction found.

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 one concise sentence that front-loads the purpose and provides a key usage hint. 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?

Given the tool has 3 parameters (one required, two with defaults) and no output schema, the description gives enough to get started but omits details about the 'context' parameter and how the 'conversation' string should be formatted (e.g., JSON array vs plain text). It also does not explain what happens after submission, but the low complexity keeps this from being a critical gap.

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 explain parameters. It explicitly mentions message (implicitly) and conversation (and how to use it), but context is unexplained. The description partially compensates but not fully, leaving context ambiguous.

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 is distinct from siblings like authenticate, connect, or show_version, and directly names the action and scope.

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 implicitly tells when to use (when reporting issues/feedback) and gives a specific instruction to include the conversation array for reproduction. However, it does not explicitly mention alternatives or when not to use, so it falls short of a 5.

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. The description adds no additional behavioral context beyond restating the tool's function, but given the tool's trivial nature, no further disclosure seems necessary.

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, concise sentence that conveys the entire purpose without filler. Perfectly proportionate to the tool's simplicity.

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 version introspection tool with no parameters and no side effects, the description completely fulfills all necessary informational needs. No output schema is required, and the description covers everything an agent needs to know.

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 schema coverage is trivially 100%. Per the rubric, 0 parameters receives a baseline of 4, and there is nothing further the description needs to add.

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'). It is immediately clear what the tool does and is distinguishable from sibling tools 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?

No guidance is given on when to use this tool versus alternatives. It does not mention use cases like 'check before connecting' or reference siblings (e.g., toolkit_info), leaving the decision to the agent without contextual support.

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 read-only, idempotent, and non-destructive behavior. The description adds value by disclosing the specific state elements returned (installed MCPs, connection status, accounts, catalog counts), which is beyond the annotations. No contradictions. Slight deduction for not mentioning network behavior or response format.

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, information-dense sentence that front-loads the core purpose ('Returns the current toolkit state') and immediately enumerates the key data points. Every word earns its place; no 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 read-only informational tool with no parameters and clear annotations, the description provides sufficient context: it lists all expected return categories. It could be more explicit about output format or error behaviors, but such details are not critical given the tool's simplicity and the strong annotations.

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 zero parameters and 100% schema coverage, the baseline is 4. The description adds no parameter details, but none are needed since the tool takes no 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?

The description uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state') while enumerating the exact contents (installed MCPs, connection status, accounts, catalog tool counts). It is readily distinguishable from sibling tools like show_version or authenticate, 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 inspecting state but provides no explicit 'when to use' or alternatives. It doesn't contrast with siblings like show_version, though the detailed return-value list gives strong contextual hints. Missing exclusions or direct alternative references keep it at a minimum-viable level.

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