Prefeitura SC Balneário Camboriú: Certidão Negativa de Débitos

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

Annotations already declare idempotentHint=true and destructiveHint=false, but the description adds context about permanent vs. session-only login and that calling with no args returns a link. It does not specify what happens after providing a token (e.g., success response), but the disclosures go beyond 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 front-loaded with the action ('log in in the browser, copy the access token') and then provides two clear alternatives. Each sentence adds value without redundancy, and it is appropriately sized for the tool's complexity.

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 tool with one optional parameter and no output schema, the description covers the main usage scenarios. It does not explicitly state what the tool returns when a token is provided, but it implies the flow. Given the straightforward purpose, this is nearly complete, with only a minor gap on response format.

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 one token parameter with no description (0% coverage), so the description must compensate. It fully explains that token is a JWT from the browser login, and clarifies that it's optional (no args for link vs. token for session) and how it's used. This is excellent at parameter explanation.

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 IDE agents. It explains the flow of logging in, getting a token, and either using it as a config header or passing it to the tool. It distinguishes from sibling tools by its focus on 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 explicit usage guidance: it explains both the permanent setup (adding a header to server config) and the session-only option (passing the token), and when to call with no args to get the login link. This clearly instructs 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 establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which fully cover the safety profile. The description adds valuable context about the response structure (authenticated flag, pending array, connect_url presence) and conditional behavior based on credential state, which goes 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?

Two concise sentences, front-loaded with the core purpose, and the conditional behavior is explained efficiently. Zero 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 zero-parameter read-only tool with robust annotations, the description covers the essential states and returned values. It doesn't detail the format of URLs, but that's a minor gap given the simplicity of the tool and no output schema.

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 schema cannot document them. The description adds no param info (which is fine), but the baseline for 0 params is 4 because there's nothing to add. The description focuses on output semantics instead, which is appropriate.

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 specific verbs ('Returns') with a clear resource ('connection status and URLs'), and it clearly distinguishes itself from sibling tools by focusing on connection status rather than authentication or other operations. It also provides specific behavioral details (authenticated:true, empty pending[], connect_url) that differentiate it from alternatives.

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 clearly implies when to use this tool: to check whether connections are set up and to get URLs when credentials are missing. It doesn't explicitly name alternatives or state 'use this when', but the context about authenticated and pending states provides clear usage context. No exclusions needed since it's a status check.

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?

Even with useful annotations, the description adds substantial behavior: invoke runs tools one-off without bloating the toolkit, writes require workspace owner/admin, credential and payment gaps surface as connect/checkout links, install makes MCPs permanent, and prompt publish links open without login. This goes far beyond the basic read/write hints in 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 text is long but appropriately dense for a tool with 14 actions and 23 parameters. It front-loads the core search→describe→invoke flow before addressing install, permissions, billing, and the prompt library. Minor issues include a run-on opening and the out-of-place Portuguese word "pontualmente", but most sentences earn their place.

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 multi-action hub, the description is remarkably complete: it covers discovery, one-off execution, installation, billing, permissions, bug reports, MCP requests, and prompt library operations. It does not fully describe return payloads for search/list_tools/invoke success, but it does explain key result links and flags. A few actions like resume and the immediate parameter remain underspecified.

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 carry the parameter-meaning burden. It does meaningfully explain the core action parameters (action, mcp_id, tool_id, arguments), billing actions, and prompt parameters like prompt_vars and prompt_slug. However, some parameters such as immediate, resume, tier_slug, and conversation receive no explanation, leaving gaps for a 23-parameter tool.

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 what the tool is: "the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them." It then enumerates a concrete core flow (search → describe → invoke) and distinct action families (install, subscribe, prompts), making the tool's broad purpose explicit and distinguishable from simple 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 gives explicit routing guidance: "prefer invoke for a single/occasional use", "Use install only to make an MCP PERMANENT", "list_tools lists what is callable right now", and "request_mcp asks us to build a NEW MCP when nothing fits." It also explains when invoke returns connect/checkout links and to retry afterward, giving the agent clear decision rules.

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 context beyond those: payment with prepaid credit, no platform credentials needed, data is public/non-confidential, and LGPD responsibility lies with the client. This meaningfully supplements the annotation-level safety profile.

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 three sentences with front-loaded purpose, then payment/hosting context, then data and legal notes. It is efficient and well-structured, though the LGPD detail could be more concise. Every sentence adds some value, but the legal sentence is secondary.

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, so the description should at least hint at the result format; it does not. It does cover the data source, payment model, and legal accountability. However, the lack of parameter guidance and return-value description leaves gaps for a paid consultation 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 description coverage is 0%, and the description does not mention the cpf or cnpj parameters at all. While the parameter names are self-explanatory Brazilian identifiers, the description fails to clarify whether either is required, if they are alternatives, or how the query uses them. The description carries no burden for parameters, creating a 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 performs a 'consulta' (query) of 'Certidão Negativa de Débitos' from a specific official source (Prefeitura SC Balneário Camboriú), using a specific verb and resource. It is clearly distinct from the generic sibling tools like authenticate, 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 context: this is a paid per-query service using prepaid credits, hosted on the platform without requiring platform credentials. It does not explicitly state when-not-to-use or name alternatives, so it stops short of a 5, but the usage context is unambiguous.

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 provide readOnlyHint=false, idempotentHint=true, destructiveHint=false, which covers the safety profile. The description adds that it requires conversation data for reproduction, but doesn't disclose other behaviors like whether it blocks or how feedback is handled.

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 sentences, one for purpose and one for requirement. No fluff, every word earns its place. Front-loaded with the 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?

Given the simplicity of the tool (report bug) and the presence of annotations and required field, the description is adequate but incomplete on parameter details and return behavior. The output schema is absent but not critical for a report action. Still, more detail on 'context' and 'message' would help.

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 explains 'conversation' is an array for reproduction, but 'message' and 'context' are not explained beyond their schema names. The description adds some value but not enough for a 3-parameter tool with no schema help.

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, and specifies the action (report) and resource (bug/feature/feedback). It distinguishes from siblings like marketplace or show_version, though not explicitly from other reporting tools.

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 there's a bug or feedback) but does not provide explicit exclusions or alternatives. It mentions including conversation for reproduction, which gives context on usage.

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 (readOnlyHint: true, destructiveHint: false, idempotentHint: true) already declare the safety profile. The description adds that it shows 'MCP platform and adapter versions', which is a specific scope. It doesn't describe return format or any caveats, but since it's a trivial read-only tool, 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 a single sentence, front-loaded with the key information. Every word is necessary, and there is no redundancy. It perfectly balances brevity and 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?

With no parameters and no output schema, the description is mostly sufficient. It does not mention what the output will look like (e.g., version numbers format), but for a versioning tool, that is often implied. It could be slightly more descriptive about the exact scope, but given the simplicity, it is adequately 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, and schema description coverage is 100% (trivially). The description does not need to add parameter semantics because there are none. It correctly omits any param-related text, and the baseline for zero params is 4.

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 action (show) and the object (current MCP platform and adapter versions). This is unambiguous and directly aligned with the tool name 'show_version'. It leaves no room for confusion 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 does not provide any guidance on when to use this tool or why it might be relevant. However, given the tool is a simple read-only version check, the lack of explicit usage guidance is not a critical flaw, but it still misses an opportunity to suggest contexts like debugging or compatibility checks.

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 safe read-only nature is covered. The description adds useful context about the content returned but does not disclose additional behavioral traits such as network probing or rate limits, though the annotations reduce the burden.

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 is front-loaded with the core purpose and then lists the key data elements. Every phrase earns its place with 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 informational tool, the description sufficiently covers what the return value includes: installed MCPs, connection status, accounts, and catalog tool counts. It does not describe formatting or edge cases, but the low complexity and strong annotations make this adequate.

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 schema fully covers parameter semantics. The description does not need to explain parameters, and the 0-parameter baseline of 4 is appropriate.

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'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from siblings like authenticate, connect, and marketplace, which perform different actions.

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 explains what the tool reports but gives no explicit guidance on when to call it or when to prefer a sibling tool. A user can infer it is appropriate for inspecting state, but the description does not state prerequisites, exclusions, or alternatives.

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