Prefeitura MG Luz: Certidão Negativa de Débitos

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

The description explains the authentication flow: it provides a link for browser login, accepts a token, and supports both permanent and session-only configurations. It does not contradict annotations; annotations indicate idempotentHint=true and destructiveHint=false, which aligns with a non-destructive authentication tool. It could have mentioned that repeated calls are safe and idempotent, but the description already covers the main 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 concise but packed with useful information: the context (IDE agents), the browser login flow, the two login options, and how to invoke the tool. Every sentence adds value, and the structure flows logically from setup to invocation. It is front-loaded with the main purpose.

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 authentication tool with one optional parameter and no output schema, the description is quite complete. It explains the setup process, the two methods of using the token, and how to call the tool. The context signals indicate low complexity, and the description covers all necessary behavioral details for an agent to use 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 schema has only one optional parameter 'token' with no description. The description clarifies that the token is a JWT pasted by the user for session-only login, and explains the alternative of configuring it server-side. Although the description does not detail token format beyond 'jwt', it provides clear meaning for the parameter, which compensates for the 0% 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: authenticating MCP.AI for IDE agents by logging in via browser and obtaining an access token. It distinguishes itself from siblings by focusing on authentication, while siblings handle connectivity, marketplace, preferences, bug reporting, version, 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 description provides explicit usage guidance: best practice is to add the token to the server config as a permanent header, or alternatively paste the token for session-only login. It explains the two invocation modes: with a token parameter or without arguments to get the link. This clearly tells the agent when and how to use the tool.

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, idempotent, and non-destructive. The description adds specific behavioral outcomes: authenticated true with empty pending, or connect_url for toolkit and per-install URLs when credentials missing. This adds context beyond annotations, though not exhaustive (e.g., partial connectivity not covered), but sufficient.

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 two sentences, front-loaded with the main purpose, then specific scenarios. 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?

For a simple status/check tool with no parameters and no output schema, the description covers the two main cases clearly. It doesn't explicitly mention the exact structure of the response, but it's a simple check. Completeness is adequate given simplicity.

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)Skip 0 params baseline is 4. The description doesn't need to explain parameters, and schema coverage is 100% (empty schema). No additional value needed.

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, with specific detail on the two outcome states (all connected vs missing credentials). This distinguishes it from siblings like authenticate, which actually performs authentication, and show_version, which reports version 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 description implies it's for checking connection status and getting URLs when needed. It doesn't explicitly state when not to use it, but the action is clear. Sibling tools like authenticate indicate a different purpose, so usage context is reasonably clear, though no exclusions 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?

It discloses important behaviors beyond annotations: invoke works without installation, does not bloat the tool list, returns connect/checkout links for auth/payment, and writes require owner/admin. The annotation set is thin, so this rich behavioral detail fully compensates.

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 front-loaded and well organized into marketplace flow, invoke behavior, install-vs-invoke guidance, permission notes, and prompt library. Each section earns its place, though it is dense enough that a reader must parse carefully.

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?

It provides no output schema but still describes expected outcomes such as connect links, checkout/top-up links, shareable prompt links, and installed flags. A few actions and parameters like resume, immediate, and tier_slug receive no explicit coverage, but the description is largely adequate for a complex multi-action 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?

With 0% schema description coverage, the description must compensate, and it does explain the action enum and the role of mcp_id/tool_id/arguments in the core flow. However, many of the 23 parameters (limit, immediate, tier_slug, cancel_reason, prompt_category, prompt_targets, etc.) are left unexplained.

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 identifies the marketplace as the catalog/runtime for MCPs and promptly differentiates its prompt-library feature. It explains the core search → describe → invoke flow with specific resources and even gives example user intents.

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 guides when to use invoke vs install ('prefer invoke for a single/occasional use'; install only to make an MCP PERMANENT), when to use request_mcp, and how connect/checkout links should lead to a retry. This is strong alternative-selection 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool is clearly non-destructive. The description adds context about being hosted on the platform, no platform credentials required, payment via prepaid credit, and data control under LGPD, which provides some behavioral context. However, it doesn't elaborate on return structure or error scenarios.

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, reasonably concise paragraph that conveys purpose, source, payment, and data responsibility. It front-loads the main purpose but could be more structurally clear, though it is not overly long.

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 (low complexity, no output schema, three optional parameters), the description covers purpose, data source, and legal responsibilities, but lacks parameter semantics and usage guidelines. It is adequate for a simple consultative tool but leaves gaps in parameter 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%, so the description must compensate. It mentions the certificate consultation but doesn't explain the three parameters (cpf, cnpj, contribuinte) or their roles. The description doesn't clarify which parameter is required or how they relate, leaving the agent without sufficient semantic guidance beyond the schema names.

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 performs a consultation of 'Certidão Negativa de Débitos' (negative debt certificate) from an official source for Prefeitura MG Luz, which is a specific verb+resource. It distinguishes from siblings by referencing the official source and the certificate type, though it doesn't explicitly name an alternative tool.

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 consulting official Brazilian public data (same available to citizens) and mentions payment with prepaid credit, but it doesn't explicitly state when to use or when not to use this tool versus alternatives. It lacks explicit exclusions or 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 indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=true, so the description adds limited value beyond noting the need for reproduction context. It does not disclose potential effects (e.g., creating a ticket, sending data) beyond what annotations imply, but there is 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, informative sentence that delivers the essential information efficiently. No redundancy or 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's purpose (submitting feedback/bug reports) and the presence of annotations (idempotentHint, destructiveHint=false), the description is fairly complete. It could clarify the format of 'conversation' (e.g., JSON array of messages) but that is hinted. No output schema means return value isn't expected, so no issue there.

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 0% description coverage, so the description must compensate. It mentions 'conversation array' but does not detail the 'message' or 'context' parameters. However, the required 'message' is implied as the feedback text, and 'context' is optional. The description adds the key hint about 'conversation' being a JSON array for reproduction, which is not in 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 the tool's purpose with a clear verb ('Report'), the resource ('a bug, missing feature, or send feedback'), and specifies required content ('conversation array with recent messages'). This distinguishes it from sibling 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?

The description tells when to use the tool ('Report a bug, missing feature, or send feedback') and what to include ('conversation array for reproduction'), but does not explicitly mention when NOT to use it or alternatives, though siblings make context 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?

Annotations already indicate readOnly, non-destructive, and idempotent behavior. The description aligns with these (nothing suggests side effects). It does not add extra context beyond the annotations, but given the low bar for tools with annotations, the transparency is adequate.

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 extremely concise, containing only the essential verb and object. It avoids any redundant phrasing or unnecessary details, making it highly efficient for an agent 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 simple version-check tool with no parameters and no output schema, the description is complete. It implies the return value (version info) without needing explicit detail. The lack of an explicit return format is not a significant gap given the tool's simplicity.

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 in the schema, so the description does not need to describe any. The baseline for 0 parameters is 4, and the description correctly does not imply any inputs. No additional information is required.

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: to show MCP platform and adapter versions. It uses the specific verb 'Show' and the resource is unambiguous. There are no sibling tools provided for comparison, but the purpose is self-evident.

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 this tool is used to retrieve version information, but it does not explicitly distinguish it from potential alternatives (e.g., a tool that shows detailed configuration). Since it is a simple, zero-parameter read-only operation, the context is clear enough for an agent to know when to use 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which cover the safety profile. The description adds meaningful context by detailing exactly what 'state' includes (connections, accounts, tool counts), aligning with the annotations without contradicting them.

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 front-loads the action and resource, then provides a compact, comma-separated enumeration of returned information. Every word contributes meaning; there is no redundancy or 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 zero-parameter, no-output-schema info tool, the description fully specifies the return contents and leaves no ambiguity. Sibling tool context (authenticate, connect, marketplace) further clarifies its role as a status overview, making the description 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?

There are zero parameters, so the baseline is 4 per the guidelines. The description does not need to explain parameter semantics and instead appropriately focuses on the return values, which is the only relevant aspect.

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 identifies a clear resource ('current toolkit state') with an enumerated list of contents (installed MCPs, connection status, accounts, catalog counts). This fully distinguishes it from sibling tools like authenticate, connect, and 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?

The description implies usage as a status/overview tool but does not explicitly state when to use it versus alternatives. There are no exclusion statements or mentions of alternate tools, leaving the agent to infer the appropriate context from the purpose alone.

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