Indicadores PF (Transparência)

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

Beyond annotations (idempotentHint, non-destructive), the description adds meaningful behavioral context: it explains that calling with no args returns a link, that passing a token performs session-only login, and that config-based auth is permanent. 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 concise (three sentences), front-loaded with the core purpose, and clearly structured with 'Best:' and 'Or' to separate alternatives. Every sentence contributes value 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 tool with one optional parameter, no output schema, and a user-interactive flow, the description covers all essential aspects: how to initiate login, what to do with the token, and the two authentication modes. It could mention the expected response or success criteria, but that is not critical given the 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 schema only lists an optional 'token' string with no description. The description fully compensates by explaining that 'token' is a JWT from the browser login and that omitting it yields the login link. This adds complete semantic meaning 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 clearly states the tool's purpose: authenticate an IDE agent to the MCP server via browser login and token acquisition. It uses specific verbs ('log in', 'copy the access token') and distinguishes itself from siblings like 'connect' by focusing on the authentication flow.

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 usage instructions for both permanent (config header) and session-only (token parameter) authentication, and explains when to call with no args. It lacks an explicit 'when not to use' or comparison to sibling tools, but the context is sufficiently 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 declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds valuable behavioral context by specifying response states: authenticated:true with empty pending[] when connected, and connect_url plus per-install URLs when credentials are missing. No contradiction 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?

The description is composed of three concise sentences that efficiently convey the tool's purpose and two key behavioral scenarios. Every sentence contributes meaningful information, with no redundant or filler text.

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 covers the main return states (fully connected and missing credentials) sufficiently. It does not enumerate intermediate/partial states or detailed URL formats, but these are not critical for initial selection or invocation. Overall, it is complete enough 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 zero parameters, so the schema is empty. Per the rubric, 0 params sets a baseline of 4; the description correctly does not attempt to describe nonexistent parameters. No additional parameter information is 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 'Returns connection status and URLs', using a specific verb and resource. It effectively distinguishes itself from sibling tools like authenticate (which likely performs an action) by focusing on status/URL retrieval rather than state change.

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: it is used to check connection status and obtain URLs when credentials are missing. It does not explicitly mention alternatives or exclusions, but the scenarios described ('when all providers are connected' vs 'when credentials are missing') imply the appropriate usage. Sibling differentiation is not explicit, so it misses full marks.

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 reveals critical behavioral traits beyond the annotations: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente... without adding the MCP to the toolkit.' It also discloses side effects and permissions: 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin.' It even explains conditional response behaviors like returning a connect link or a checkout/top-up link. No contradiction 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?

The description is long but each sentence earns its place for a tool with 14 actions and 23 parameters. It is front-loaded with the main purpose, then progresses logically from core flow to edge cases, permissions, and the prompt library. It avoids redundancy and maintains a coherent structure despite the density.

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 (14 actions, 23 params, no output schema), the description is remarkably complete. It explains the full lifecycle from search to invoke, covers auth and payment interruptions, distinguishes permanent install from one-off invoke, lists list_tools as a status check, and fully covers the prompt library sub-feature. It omits no major behavioral outcome and provides enough context for an agent to invoke any action 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?

With schema description coverage at 0%, the description carries the burden of explaining parameters. It successfully adds meaning for the most critical ones: action values ('search', 'describe', 'invoke', 'install', etc.), tool_id selection ('so you pick the right tool_id'), and arguments (implicitly via 'invoke RUNS that tool'). However, it leaves many parameters unexplained (limit, immediate, tier_slug, cancel_reason, etc.), relying on their names for inference. Still, the workflow-level guidance is substantial enough to offset the lack, so this is above baseline but not perfect.

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, specific purpose: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It distinguishes this tool from siblings by establishing it as the central catalog and execution hub, and it further enumerates the two primary capability areas (MCP discovery/invocation and the prompt library).

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 when-to-use guidance: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... so you pick the right tool_id → invoke RUNS that tool.' It also gives direct preference rules: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' This is superior, actionable context for choosing among the 14 actions.

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 provide readOnlyHint=false and idempotentHint=true, but the description adds little behavioral context beyond instructing to include conversation. It doesn't explain side effects, whether a report is sent, or if duplicates are possible, leaving significant ambiguity.

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 purpose and a key usage instruction. 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 3-parameter tool, the description covers the core purpose and the important conversation instruction, but it lacks clarity on the conversation format and does not describe any return behavior or prerequisites like authentication. It is minimally viable but with gaps.

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 explain parameters. It mentions conversation but calls it an 'array' while the schema shows string, causing ambiguity. The 'context' parameter is entirely undocumented, and 'message' is only implicitly understood.

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 reports bugs, missing features, or feedback. The verb 'Report' and specific objects distinguish it from unrelated 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?

The description implies when to use the tool (when submitting bug reports or feedback) and instructs including the conversation array. It does not explicitly mention exclusions or alternatives, but no sibling tool overlaps this purpose.

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, providing a clear safety profile. The description adds no additional behavioral traits such as authentication requirements, potential side effects, or return format. It is consistent with annotations, so a 3 is appropriate for adding minimal context 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 a single sentence, concise and clearly structured. It contains no redundant words or filler, making it easy to parse and immediately 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 tool with zero parameters, strong annotations, and a simple purpose, the description is complete. It states exactly what information is returned (current versions) and does not require additional explanation of return values or parameters. The presence of no output schema is not a gap given the trivial nature of 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 tool has zero parameters, resulting in 100% schema coverage. The description does not need to elaborate on parameter semantics because there are none to document. The baseline of 4 applies for zero-parameter tools.

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 clearly identifies the resource (MCP platform and adapter versions). It is unambiguous, but it does not explicitly differentiate from sibling tools like toolkit_info, which might also provide general toolkit information. Thus it earns a 4 for clear but not explicitly differentiated 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?

There is no explicit guidance on when to use this tool versus alternatives. However, the purpose is so specific that usage is implied: whenever version information is needed. The description does not mention when not to use it or provide alternatives, so it falls short of a higher score but is not misleading.

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, so the safety profile is known. The description adds meaningful context about what the state includes (installed MCPs, connection status, accounts, tool counts), going beyond the annotation coverage without contradicting it.

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 front-loads the main purpose ('Returns the current toolkit state') and then lists specifics without redundancy. Every part earns its 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 simple, no-parameter, read-only info tool, the description is fully adequate. It enumerates the key contents of the return value, and annotations cover safety and idempotency, making the description complete in context.

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 is empty with zero parameters, so there is nothing to describe. The baseline for zero-parameter tools is 4, and the description naturally does not need to add 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 identifies the tool's function with the verb 'Returns' and the resource 'current toolkit state'. It enumerates specific details (installed MCPs, connection status, accounts, count of catalog tools), which distinguishes it from sibling tools like show_version 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 description implies the tool is for checking toolkit status but does not explicitly state when to use it or contrast it with alternatives. There is no exclusionary guidance or mention of alternatives, but the read-only info nature is implied.

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 mark it as read-only and idempotent. The description adds useful details: it is hosted by the platform, requires no credentials, is pay-per-query, and accesses public data with LGPD responsibilities. This goes beyond the annotation hints 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 tight three-sentence paragraph, front-loaded with the core functionality. It includes payment model, data access type, and legal context without unnecessary fluff, though the LGPD sentence could be seen as slightly verbose.

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 'indicadores' means or what the response contains. It covers data type, access, and compliance, but misses parameter details and return value expectations, making it incomplete for a 3-parameter 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 schema has three parameters with 0% description coverage, so the description must compensate. It mentions CPF and NIS as inputs in the first sentence, but does not clarify their format, purpose, or the meaning of the optional 'completo' parameter. 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 provides 'Indicadores de uma pessoa física no Portal da Transparência' using CPF and NIS, and later says 'Consulta informação' with a query verb. It is clearly distinct from sibling tools like authenticate or marketplace, which serve different purposes.

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 usage context: no credentials required, pay-per-query with prepaid credit, and that it accesses public data. It doesn't explicitly provide when-not-to-use or alternatives, but the sibling tools are unrelated, so the context is sufficient for selecting this tool.

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