Prefeitura GO Morrinhos: Certidão Negativa de Débitos

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

No annotations beyond basic hints (readOnly=false, idempotent=true). The description explains the two modes: permanent vs session-only, and that it can be called with no args to get a link. It does not mention any side effects like opening browser, network calls, or that token is stored. IdempotentHint=true suggests repeated calls are fine, consistent with description. No contradiction, but lacks detail on what happens after login (e.g., validation).

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?

Description is one long sentence but packed with info. It is front-loaded with the tool's purpose and quickly explains usage options. Slightly dense but not overly long. No fluff.

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 (auth flow, two modes, token handling), the description covers the main paths but lacks detail on error cases, what happens if token is invalid, or how the permanent config is set up. No output schema, so description carries more burden. It is functional but not exhaustive.

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 has 1 param 'token' with no description coverage (0%). The description mentions 'token' as a JWT for session login, providing some semantics, but it is brief and assumes understanding of JWT. It does not describe the format, length, or requiredness clearly. With low schema coverage, description compensates partially but not enough for a critical auth token.

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 the tool authenticates the user via browser login and provides options for token handling. It clearly distinguishes from siblings like 'connect' and 'marketplace' by focusing on authentication flow. However, the verb 'authenticate' is somewhat generic, but the resource (access token) and process (browser login) are specified.

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 explains when to use it: after user pastes token (session-only) or for permanent config. It doesn't explicitly say when not to use, but context is clear given siblings like 'connect' and 'marketplace' are alternatives. Could be improved by referencing alternative tools explicitly, but the description provides clear usage context.

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 goes beyond the readOnlyHint and idempotentHint annotations by detailing the exact return values in different states: `authenticated:true` and empty `pending[]` when connected, and `connect_url` plus per-install URLs when credentials are missing. This is valuable behavioral context that annotations do not provide.

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 then provides conditional behavior. Every sentence earns its place with no redundant information or unnecessary elaboration.

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 that there is no output schema, the description sufficiently explains both primary states of the tool (all connected vs. missing credentials) and includes the relevant URLs. The tool is simple with no parameters, and the description covers all necessary context for an agent to understand its 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?

There are no parameters to document, and the schema confirms this with 100% coverage. The baseline for 0 parameters is 4, and the description appropriately focuses on behavior rather than parameter 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 clearly states the tool's function: 'Returns connection status and URLs.' This is a specific verb (returns) and resource (connection status and URLs), and it distinguishes itself from the sibling 'authenticate' by focusing on status rather than initiating 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 provides clear context for when to use the tool: it returns connection status, and the conditional behavior ('When all providers are connected...' / 'When credentials are missing...') informs the agent of the expected outcomes. However, it does not explicitly mention alternatives or exclusions, so it stops 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?

The description discloses key behavioral traits beyond annotations: invoke works even when the MCP is not installed, it runs one-off without adding to the toolkit, writes require workspace owner/admin, subscribe/cancel handle per-MCP billing, and search/describe include installed_in_toolkit vs installed_in_workspace flags. It also explains what invoke returns for auth and payment cases. The text does not contradict the annotations (readOnlyHint=false, openWorldHint=true).

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 informative and well-structured: it opens with the umbrella purpose, then uses 'Core flow', 'KEY', 'Use install only', and 'It also carries' to organize major behavior and alternatives. Every sentence contributes meaningful information—edge cases, permissions, or workflow distinctions—so the length is justified rather than bloated.

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 very complex multi-action tool with 23 params and no output schema, the description is unusually complete: it explains the main workflows, the key invoke edge cases, install-vs-invoke trade-offs, admin requirements, and the prompt library. It does omit a few behaviors (e.g., resume, immediate, tier_slug semantics) and does not describe output shapes, but overall it gives an agent enough context to navigate the tool safely and 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?

With 23 parameters and 0% schema description coverage, the description carries heavy responsibility. It adds semantic context for the key parameters (action, mcp_id, tool_id, arguments, prompt_title, prompt_body, prompt_vars, request_name, request_details, cancel_reason/comment) by explaining the core flows. However, several parameters remain unexplained in both schema and description (e.g., immediate, tier_slug, conversation, message, limit, report_context), so it does not fully compensate 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 opens with a clear purpose: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It distinguishes itself from siblings by enumerating its own action categories (search, describe, invoke, install, subscribe, prompt library) and explicitly contrasting invoke vs install, making its scope unmistakable even alongside tools like authenticate and connect.

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: 'prefer invoke for a single/occasional use' versus 'Use install only to make an MCP PERMANENT in the active toolkit.' It also handles edge cases (credential/login returns a connect link; empty wallet returns checkout link), calls out admin permission requirements for writes, and suggests request_mcp when nothing fits. This is strong decision-making support beyond a bare verb+resource 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?

Annotations include readOnlyHint=true and destructiveHint=false, and the description aligns: it's a read-only consultation. The description adds context about billing (pay per query with prepaid credits), authentication (no platform credentials), data controller role (LGPD), and that data is not confidential. These are valuable behavioral details beyond annotations. 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 a single paragraph with multiple sentences, each adding distinct information (purpose, hosting, payment, official source, LGPD). It is fairly concise for the amount of context provided, though slightly dense.

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 only two optional parameters and no output schema. The description covers purpose, source, payment, and data handling. It doesn't explain return format or input constraints, but given the simplicity and available annotations, it is reasonably complete for selection and basic usage.

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% and parameters (cpf, cnpj) are not described. The description does not explain that either one can be provided, their formats, or validation rules. It falls short in adding meaning beyond the bare 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 it consults Certidão Negativa de Débitos from Prefeitura GO Morrinhos, using official sources. It clearly identifies the resource and action. Although it doesn't explicitly distinguish from siblings (which are generic), given the context it is sufficiently 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?

No explicit guidance on when to use this tool versus alternatives. It mentions it's a paid query with prepaid credits, and that it's for official Brazilian sources, but does not discuss selection criteria or exclusions relative to other 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 indicate idempotent, non-destructive, and non-read-only. The description adds value by noting the conversation array is required for reproduction, implying the tool uses it to replicate issues. No contradictions with 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 immediately state the purpose and a critical usage hint. No fluff, front-loaded, and easy to parse.

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 3-parameter tool with no output schema, the description adequately covers purpose, usage, and a key parameter. It lacks explanation of the context parameter and what happens after submission, but overall it is sufficiently complete for a feedback tool.

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 explicitly mentions the conversation parameter and implicitly covers the message field. However, it does not address the context parameter, leaving its purpose unclear. It adds meaning for two of three 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's purpose: reporting bugs, missing features, or feedback. It specifies the action (report) and resource (bug/feature/feedback), and is distinct 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?

It provides a clear instruction to include the conversation array for reproduction, guiding on how to use the tool effectively. It does not explicitly state when not to use it, but the context is 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?

The annotations already establish readOnlyHint, idempotentHint, and destructiveHint false. The description adds no deeper behavioral detail beyond saying 'current' versions, and it does not contradict the annotations. Given the strong annotation coverage, the simple description suffices but adds little extra 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?

The description is a single, front-loaded sentence with no surplus words: 'Show the current MCP platform and adapter versions.' Every word contributes to the meaning.

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, no-output-schema, read-only version display tool, the description is complete. There is no workflow context, destination, or pagination to specify, and the existing annotations cover side effects well enough.

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 is also no parameter-specific meaning to explain. According to the established baseline for zero-parameter tools, a 4 is appropriate since there is nothing for the description to add 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 uses the specific verb 'Show' and identifies an exact resource: 'the current MCP platform and adapter versions.' This distinguishes it from sibling tools like authenticate, marketplace, or report_bug, none of which are about version inspection.

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 a self-evident use case, but it does not explicitly state when to choose this tool over alternatives such as toolkit_info. There is no clear exclusions or alternative guidance, but for a version lookup the intended usage is fairly obvious.

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, covering the safety profile. The description adds useful behavioral context by specifying exactly what state is returned and that it reflects the current toolkit. It does not mention potential staleness or network calls, but this is minor for a simple info tool.

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 core purpose ('Returns the current toolkit state') and then lists the specific contents. Every word earns its place with 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 parameterless read-only tool with no output schema, the description sufficiently explains the return value by enumerating the categories of information provided. No additional context is necessary for an agent to select and invoke this tool 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, so the baseline is 4. The description adds no parameter details because none are needed; the schema is empty and fully covered.

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') with a clear resource ('current toolkit state') and enumerates the exact information returned (installed MCPs, connection status, connected accounts, catalog tool counts). This clearly distinguishes it from sibling tools like show_version or connect.

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 inspect toolkit state, but it provides no explicit guidance on when to use it versus alternatives like show_version or marketplace. The usage context is clear enough for a read-only info tool, but no exclusions or alternative comparisons are given.

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