Prefeitura MS Naviraí: Certidão Negativa de Débitos

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

The description discloses key behaviors: it can establish a permanent non-expiring connection or a session-only login, and calling with no arguments returns a login link. This complements the annotations (idempotent, non-destructive) without contradicting them, though it doesn't mention any potential side effects on server config.

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 reasonably concise and well-structured, presenting two clear options (permanent config and session-only) with a recommendation. It includes a contextual note about IDE agents but remains focused and readable.

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?

While the description explains the authentication workflow and the behavior for no-argument calls (returning a link), it does not specify what the tool returns when called with a token (e.g., success status or session confirmation). This leaves some ambiguity about the output for a token-based call.

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 description explicitly clarifies the meaning of the 'token' parameter: it is a JWT (JSON Web Token) obtained from the browser, used for session-only login. This adds significant semantic value beyond the raw schema which only specifies '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 of authentication for IDE agents, explaining the login process and how to obtain an access token. It is specific and distinguishable from sibling tools like 'connect' 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 provides detailed usage instructions: it explains two methods (permanent config via token, or session-only via pasting token) and specifies when to call with or without the token argument. However, it does not explicitly contrast this tool with alternatives, though the context makes its primary use 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 read-only and idempotent annotations, the description explains the behavior under different conditions (authenticated true vs. connect_url provided), adding useful context about response variations.

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, using two clear sentences to convey the core behavior without redundancy or extraneous 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?

Without an output schema, the description provides essential output details (authenticated, pending[], connect_url) and conditions. It is sufficiently complete for a simple status check, though it does not fully describe the entire response structure.

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 no parameters, and the schema covers this fully. The description adds no parameter-specific details, which is appropriate given the absence of inputs. Baseline score of 3 applies due to high 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 returns connection status and URLs, specifying the output for two scenarios (all connected vs. missing credentials). This distinguishes it from sibling tools like authenticate.

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 connection status but does not explicitly state when to use this tool versus alternatives (e.g., authenticate). It provides conditional output details but lacks clear guidance on when to invoke it.

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 (readOnlyHint=false, openWorldHint=true), the description discloses that invoke runs MCPs even when not installed, a one-off execution without adding to the toolkit. It explicitly states that writes require workspace owner/admin, and details the connect/checkout flow for auth and payment. This adds significant behavioral context not available from 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 long, unbroken paragraph packed with essential details, but it lacks structured formatting (e.g., bullets, sections). It is concise for the amount of information but repeats concepts like 'one-off' and 'installed_in_toolkit vs workspace' multiple times, slightly reducing readability.

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 optional parameters, 14 actions, no output schema, and minimal annotations, the description is remarkably complete. It covers the full workflow (search→describe→invoke), distinguishes install vs invoke, handles auth/payment edge cases, lists all subcommands (subscribe, cancel, report_bug, request_mcp, prompt operations), and explains the prompt library separately.

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 must explain parameters. It explains the action enum values in context (e.g., 'action=search discovers MCPs by intent', 'invoke RUNS that tool'), and mentions tool_id and arguments implicitly. It covers most key parameters but does not individually detail limit, immediate, tier_slug, or prompt_* parameters; however, the action-level guidance compensates for the majority.

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 is explicit: it defines the marketplace as the official catalog of MCPs/tools and the way to run them, covering both discovery and execution. It lists all major actions (search, describe, install, invoke, etc.) and distinguishes from sibling tools by stating report_bug sends feedback and that it also hosts a prompt library separate from MCPs.

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 concrete guidance on when to use invoke vs install ('prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'), explains how to handle credential/payment scenarios (connect/checkout links), and clarifies that list_tools shows what is callable right now. It also notes that search/describe flag installed status, guiding discovery.

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=true, idempotentHint=true, destructiveHint=false, so the tool is known to be non-destructive and idempotent. The description adds that it is hosted by the platform, requires prepaid credit per consultation, and that the client is the data controller under LGPD. This adds useful context about cost and legal responsibility, but no mention of specific return formats or error conditions. 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?

The description is a single long sentence but contains essential information: source, type of certificate, payment model, legal compliance. It's somewhat dense but front-loaded with the main purpose. It could be split into clearer sentences, but it's not overly verbose for the amount of context it provides.

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 output schema, and the description does not explain what the response will contain. However, since it's a certificate consultation, the response is likely the certificate data or a status. The description covers cost, legal aspects, and source, but not detailed behavior or expected output format. Given the lack of output schema and parameter descriptions, the tool description is partially complete but misses key operational details like which parameters are used for individuals vs companies.

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 the description does not explain the meaning of the 6 parameters beyond what the schema shows. The parameters include cpf, cnpj, finalidade, and requester fields, but the description does not clarify which are required for which scenarios (e.g., CPF vs CNPJ). It mentions 'consulta' and 'finalidade legítima' but not the 'finalidade' parameter's purpose. The description fails to compensate for the lack of schema descriptions, leaving the agent to guess parameter usage.

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 consult Certidão Negativa de Débitos (negative debt certificate) from Prefeitura MS Naviraí, a specific municipal government source. It specifies the resource (certidão) and the action (consultar). It does not explicitly distinguish from sibling tools, but siblings are mostly platform-level tools (authenticate, connect, marketplace, etc.), so the purpose is clear enough.

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 context on when to use the tool: for consulting official Brazilian government sources, it's not confidential data, and it requires prepaid credit. It implies it's for debt certificate lookup specifically. It doesn't explicitly say when not to use it or mention alternatives, but it gives a clear context of use under LGPD and payment terms.

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=false and destructiveHint=false, establishing a non-read-only, non-destructive mutation profile. The description adds value by disclosing that recent messages should be included for reproduction purposes, which is genuine behavioral context beyond the annotations. It doesn't detail submission behavior or outcomes, but given annotation coverage, a moderate score is appropriate.

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 highly efficient: two sentences, purpose first, followed by a usage hint. Every clause earns its place and there is zero filler or redundancy. It's front-loaded with the main verb action before diving into the reproduction 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?

For a 3-parameter tool with no output schema and no enums, the description delivers the core purpose and one parameter's semantics (conversation). It falls short on the required 'message' parameter and 'context' field, and given 0% schema coverage, this leaves meaningful gaps in what the agent needs to construct a correct 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?

With 0% schema description coverage, the description must compensate for the schema's lack of parameter documentation, but it only partially does. It mentions the 'conversation array,' covering that parameter, yet the required 'message' parameter and the 'context' parameter are never explained. The agent must infer that 'message' holds the report content, which is a notable gap given the required field.

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+resource: 'Report a bug, missing feature, or send feedback.' The purpose is clear and naturally distinguishes from siblings (authenticate, connect, marketplace, show_version, toolkit_info), none of which overlap with bug reporting or feedback. It covers a small family of related actions but there's no ambiguity about what the tool does.

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 it — when reporting a bug, missing feature, or providing feedback — and adds a practical hint about including the conversation array for reproduction. However, it provides no explicit exclusions or named alternatives, though this is mitigated by the fact that no sibling tool competes in this domain.

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, covering the safety profile. The description adds the specific scope (platform and adapter versions) beyond the annotations, which is useful. However, it does not describe the output format or any side effects, though none are expected. This is acceptable but not rich.

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, focused sentence that immediately states the action and target. It contains only essential information with no fluff, making it highly concise and well-structured.

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 low complexity (no params), the absence of an output schema, and the presence of supportive annotations, the description is fully adequate. It tells the agent exactly what the tool does, which is all that is needed for a version-check 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?

There are zero parameters, so the schema has no properties. The description clarifies the tool's purpose but does not need to add parameter semantics as there are none. Baseline for 0 parameters is 4, and the description meets that baseline.

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: 'Show the current MCP platform and adapter versions.' It uses a specific verb (show) and identifies the exact resource (versions), effectively distinguishing it from siblings like 'connect' or 'authenticate'.

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 context is clear: this is a diagnostic tool for checking versions. No explicit alternatives are mentioned, but given the simple no-param nature, the usage is obvious. The description does not provide explicit exclusions or when-not-to-use guidance, but the purpose is self-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?

With annotations declaring readOnlyHint=true and destructiveHint=false, the safety profile is already established. The description adds what is actually returned (MCPs, statuses, accounts, counts), but could have added a note about potential staleness or that it doesn't require auth.

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?

Single sentence, directly front-loaded with the main verb, no wasted words. Lists just enough detail to be informative.

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 informational tool with good annotations, this is complete. Output schema is absent, so the description's list of returned information suffices. No other context is needed.

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 schema coverage is 100% (vacuously). The description explains what the tool reports, which fully compensates for the lack of 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 uses a specific verb ('Returns') and clearly specifies the resource ('current toolkit state') and details what that includes (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like authenticate/connect/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 doesn't explicitly mention when not to use this tool or name an alternative, but the context of 'current toolkit state' strongly implies its primary diagnostic use case. The clear subject matter and scope make the usage context obvious.

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