Prefeitura SP Mairiporã: Certidão Negativa de Débitos

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

Beyond the annotations (idempotent, non-destructive), the description discloses that no-args calls return a link for browser login, and that passing a token enables session-only access. It also notes that the config approach yields a non-expiring connection. It does not contradict any annotation, and adds practical behavioral context such as the need for user involvement in browser login.

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 information-dense. It is front-loaded with the core purpose, then efficiently explains the two authentication methods in a single sentence each. No wasted words, every clause contributes to guiding the agent's use.

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 a single optional parameter and no output schema, the description is complete: it covers both modes of authentication, the meaning of the parameter, and the no-args behavior. It also addresses the integration context for IDE agents. There is no obvious missing information relevant to using the 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?

The input schema only defines 'token' as an optional string with no description. The description compensates by explaining that the token is a JWT for session login, and that omitting the token retrieves the auth link. This adds meaningful semantics that the schema alone lacks, covering the only parameter and its absence.

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 authenticate an IDE agent via browser login or token. It specifies the resource (authentication) and the two distinct modes (permanent config vs. session token), effectively distinguishing it from siblings like 'connect' or 'marketplace' which serve different functions.

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 explicit guidance on when to use each mode: for a permanent connection, add the token to the server config as a header; for a session-only login, pass the token with { token: '<jwt>' } or call with no args to get the link. This clearly explains the usage scenarios and the trade-off between persistence and session scope.

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 adds significant behavioral detail beyond the annotations: it specifies two distinct output states (all connected vs. missing credentials) and what fields appear (authenticated, pending[], connect_url). This goes well beyond the readOnlyHint and idempotentHint already declared, offering concrete insight into runtime 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?

Two concise sentences with front-loaded purpose, immediately followed by actionable conditional logic. Every word earns its place; 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?

The description covers the main output states and required fields without an output schema. It lacks details on partial-connection scenarios, but given the tool's simplicity and the presence of the pending[] array hint, this is adequate. Slightly incomplete for edge-case behavior, but overall sufficient.

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, the schema trivially covers everything. Per the rubric, a baseline of 4 applies to 0-parameter tools, and the description does not need to compensate since there is nothing to document.

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 and explains conditional behavior (authenticated:true with empty pending[] when all connected, connect_url when credentials missing). This unambiguous verb+resource combination distinguishes it from siblings like authenticate, marketplace, 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?

While not explicitly naming alternatives or saying 'use this when', the description clearly implies it is for checking connection status and provides conditional outputs that guide appropriate use. It lacks explicit exclusions, but the context is strong.

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 thin annotations (readOnlyHint=false, openWorldHint=true), the description discloses critical behaviors: invoke runs tools one-off even when uninstalled, credential/login flows return connect links, empty wallets return checkout links, and writes require workspace owner/admin. It also reveals installed_in_toolkit vs installed_in_workspace flags that search/describe report.

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 dense and front-loaded with purpose and the core flow, and every sentence adds substantive value. It is, however, a long single block mixing the MCP marketplace and prompt-library subsystems, so a bulleted or sectioned structure would improve scannability.

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 complex tool with 14 actions, 23 parameters, and no output schema, this description covers the central flows—discovery, one-off invocation, installation, billing, troubleshooting, and prompts—thoroughly. It omits details on some actions like resume, immediate, and the full cancel workflow, but the core use cases are well supported.

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 compensates at the action level by explaining the action enum values and the tool_id selection flow, plus mention of prompt variables. However, most of the 23 parameters (e.g., immediate, tier_slug, request_details, prompt_targets, cancel_reason) remain undefined, so the agent still lacks precise semantics for many fields.

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 — the in-platform catalog of every MCP/tool, AND the way to run them.' It outlines a specific core flow (search → describe → invoke) and enumerates the major action groups, distinguishing it from sibling tools like authenticate, toolkit_info, 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 explicitly contrasts 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also explains when to use search, describe, invoke, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt-library actions, giving clear 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. The description adds valuable extra context: no platform credentials required, prepaid payment model, non-confidential official data, and LGPD responsibilities. This goes beyond 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, front-loaded paragraph that immediately states the purpose. It includes necessary legal and pricing details without excessive verbosity, making it efficient and easy to scan.

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 one-parameter query tool, the description covers the purpose, official source, payment model, and data governance. However, it omits any explanation of the input parameter and does not describe expected output or error cases. The missing parameter semantics reduce overall completeness.

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 only parameter 'inscricao' is not explained in the description; schema coverage is 0%. Since the schema provides only a type string and no description, the tool description should compensate but does not clarify what value is expected (e.g., taxpayer number). This is a significant 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 states the tool queries Negative Debt Certificates (Certidão Negativa de Débitos) from Prefeitura de Mairiporã, using the verb 'consulta' and specifying the official source. It distinguishes itself from generic siblings like authenticate or marketplace by being domain-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?

The description implies use for official debt certificate queries and mentions paid per-query via prepaid credits, but it does not explicitly contrast with alternatives or state when not to use. The context is clear enough for basic guidance but lacks explicit exclusions or alternative references.

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 (readOnlyHint=false, destructiveHint=false, idempotentHint=true) already convey basic behavioral traits. The description adds the context about including conversation for reproduction, which is helpful but does not disclose what happens on submission (e.g., whether it creates a persistent record). 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 extremely concise: two sentences, no wasted words, and front-loads the core purpose. It is appropriately sized for 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 simple reporting tool with three parameters and no output schema, the description covers the purpose and the most important parameter (conversation). However, it omits the 'context' parameter entirely and doesn't mention any return behavior, leaving some gaps in completeness.

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 explains the 'conversation' parameter and implies the 'message' (the report content), but does not mention the 'context' parameter at all. Thus it only partially fulfills the parameter documentation burden.

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 sending feedback. It uses specific verbs and resource types, distinguishing it from sibling tools like authenticate 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 instructs to include the conversation array for reproduction, providing one specific usage detail. However, it does not explicitly state when to use this vs. alternatives or any exclusions, leaving usage context implicit.

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 establish read-only, idempotent, and non-destructive behavior. The description adds the specific behavioral detail that the tool reports version information for the MCP platform and adapter, which is useful contextual content 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, front-loaded sentence with no filler or redundant content. Every word contributes to the tool's 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, zero-input, read-only version tool with rich annotations, this description is sufficient for an agent to select and invoke the tool correctly. The exact return format is not stated, but it is not essential 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?

The tool has 0 parameters, so there is no parameter semantics burden for the description to carry. The baseline for zero-parameter tools is 4, and the description requires no additions.

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 names a concrete resource ('current MCP platform and adapter versions'), clearly identifying what the tool does. It is also clearly distinct from the sibling tools, none of which describe a version-retrieval purpose.

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 should be used when the agent needs current platform/adapter version information, but it does not explicitly state when to use it versus alternatives like toolkit_info or report_bug. No exclusion or comparison guidance is provided.

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 signal readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context beyond annotations by specifying what information the tool returns, including connection status and per-MCP catalog tool counts.

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 that immediately states the return value and then lists the key data points with a colon and commas. Every word adds value; 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, read-only status tool, the description fully covers the tool's purpose and return contents. The annotations cover safety semantics, and no output schema is needed because the description enumerates the major output components sufficiently.

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 no parameter explanations are needed. Schema coverage is effectively 100% with an empty properties object, and the description confirms this is a stateless informational call with 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 the specific verb 'Returns' and names the resource 'current toolkit state', then enumerates the exact contents: installed MCPs, connection statuses, connected accounts, and catalog tool counts. This clearly distinguishes it from siblings like show_version or connect by scoping to toolkit inventory and status.

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 when an agent needs an overview of installed MCPs and their connectivity, but it does not explicitly state when to prefer this tool over alternatives such as show_version or connect. No when-not-to-use guidance is provided.

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