Auxílio Reconstrução

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

Beyond the annotations (idempotentHint, destructiveHint, readOnlyHint), the description adds valuable behavioral context: the token can be stored permanently in config for a non-expiring connection, or passed directly for a session-only login. It does not mention side effects or error handling, but with annotations present, this is 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?

The description is informative but structured as a single run-on sentence with multiple clauses separated by colons and 'or'. Every clause adds value, but better sentence breaks or bullet points would improve readability. It is not overly verbose, so it earns a 4.

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 a simple tool with one optional parameter and no output schema, the description covers the essential usage patterns (with/without token), explains the two authentication modes, and indicates the outcome (getting a link). It does not explain what happens after a successful token-based login or how to confirm success, which is a minor gap.

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 defines a token string with no description, so the description fully compensates by explaining that it expects a JWT access token, linking it to the browser login process, and showing how to use it in the call. This makes the parameter's meaning and format crystal clear.

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 implies authentication by describing the login-token process, but it does not explicitly state the tool's core purpose in a direct declarative sentence. It also distinguishes from sibling tools by focusing on authentication steps, though without naming 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 provides explicit usage guidance: it explains the recommended permanent method (config header) versus the session-only method (pasting token), and clarifies when to call with or without the token argument. This gives clear 'when-to-use' and alternative selections.

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 readOnly, idempotent, and non-destructive. The description adds valuable context: data is public, no credentials needed, pay-per-query, and LGPD responsibility. This goes beyond the annotation coverage.

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 the main purpose. The LGPD sentence adds legal context but is not overly verbose; overall it is efficient and 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?

The tool is simple with 3 params and no output schema. The description covers the main query intent and data nature, but lacks explanation of 'completo' and expected result format, making it incomplete for fully autonomous use.

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 names CPF and NIS but does not explain the 'completo' boolean parameter or input formats. This is a significant gap for proper invocation.

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 'Verifica' and names the exact resource 'Auxílio Reconstrução' with required inputs CPF and NIS. It clearly distinguishes this from sibling tools like authenticate, 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 clear context: it checks benefit receipt from CPF/NIS, is hosted without credentials, and costs prepaid credit. It does not explicitly state when not to use or name alternatives, but given the unrelated sibling tools, the context is 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?

Annotations already indicate read-only and idempotent behavior; the description adds value by detailing response shapes in different states (authenticated:true with empty pending[] vs connect_url for toolkit/install), which goes beyond the safety hints.

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 the core function, and each sentence provides distinct scenario information without 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 simple no-parameter tool, the description covers the two main outcomes and the expected return fields. Minor gaps like explaining 'pending' or next steps are acceptable but could improve 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 tool has zero parameters, so schema coverage is complete. The description correctly avoids adding irrelevant parameter details, and the 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' with a defined resource ('connection status and URLs'), and clearly distinguishes itself from siblings like 'authenticate' and 'show_version' by describing its exact output conditions.

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 connectivity status by describing conditional outcomes, but it does not explicitly state when to use this tool versus alternatives or provide exclusionary 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?

The description goes well beyond annotations by explaining key behaviors: invoke works even when the MCP is not installed (one-off execution), may require connect or checkout links, and performs an implicit one-off install. It also discloses that writes require owner/admin privileges and describes the prompt library. There is no contradiction with annotations (readOnlyHint=false aligns with write actions).

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?

Despite being long, the description is dense and logically structured: purpose, core flow, key distinction, actions, permissions, and prompt library. Every sentence adds value, and the flow is easy to follow. The length is justified by the tool's complexity (23 parameters, 14 actions).

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 nearly all facets of the tool: all actions (except resume, which is only in the schema), permissions, billing, and prompt library. It also hints at return values (e.g., describe returns profile, publish_prompt returns shareable link). With no output schema, it does a good job, but a bit more detail on return structures for each action would make it 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?

With 0% schema description coverage, the description must compensate. It explains the meaning of core parameters like action, mcp_id, tool_id, arguments, prompt_vars, and prompt_slug through the workflow and action examples. However, it does not explicitly document all 23 parameters (e.g., tier_slug, cancel_reason, report_context) and relies on inference. Still, it provides substantial semantic value beyond the bare 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 identifies the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It specifies a concrete resource (MCPs and prompts) and action (discover, describe, invoke, install, etc.), distinguishing it from sibling tools like authenticate or connect. The purpose is unambiguous and 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 provides explicit guidance on when to use each action, including a core flow (search → describe → invoke) and contrasts: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT.' It also notes permission requirements for writes (owner/admin) and explains when to use subscribe/cancel, report_bug, request_mcp, and prompt-related actions. This is thorough and actionable.

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 this as non-destructive, non-read-only, and idempotent. The description adds the useful behavioral hint to include the conversation for reproduction, which helps the agent understand the intended use. No contradictions 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?

Two sentences with no filler. The key action and a crucial usage tip are front-loaded, earning every word.

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 feedback tool with three params and no output schema, the description covers the core purpose, highlights the one non-obvious parameter (conversation), and relies on the existing annotations for safety. Minor gap: 'context' param remains undocumented, but this does not undermine overall usability.

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 explains the 'conversation' parameter but does not clarify the 'message' (obvious from context) or 'context' parameter. The description compensates only partially for the lack of schema documentation.

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?

Description states 'Report a bug, missing feature, or send feedback' with a clear verb and resource. It explicitly distinguishes from sibling tools, none of which are feedback-related.

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?

Provides clear context on what to include ('conversation array with recent messages for reproduction'), though it does not explicitly name exclusion criteria or alternatives. Since no sibling tool offers similar functionality, this is 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to restate safety. It adds a small detail (platform and adapter) but does not describe response format, error behavior, or any additional side effects. This is acceptable for a simple read tool, hence a middle score.

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, clear sentence with no fluff or redundancy. Every word contributes to conveying 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?

Given the tool's simplicity (no parameters, no output schema), the description is adequate to inform an agent about its function. However, it doesn't specify what exactly the returned version data looks like (e.g., strings, structure), so a small gap remains.

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 has zero parameters, so according to the rubric the baseline is 4. The description correctly implies no arguments are needed, and there is nothing additional to explain about parameter meaning.

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 ('current MCP platform and adapter versions'). This unambiguously distinguishes it from sibling tools like authenticate and connect, which imply 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?

No explicit usage context or alternative tool comparisons are provided. While the purpose is self-evident (checking versions), there is no guidance on when to invoke this tool (e.g., during troubleshooting or compatibility checks). The need is only 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 declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations by specifying exactly what the returned state contains (installed MCPs, connection status, accounts, catalog tool counts), which helps the agent predict the tool's output and side-effect-free nature.

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 action ('Returns') and then lists the key output components. Every word contributes value, with no filler or repetition of schema 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?

For a simple read-only tool with zero parameters and no output schema, this description adequately covers the return content. It could be improved by noting the data format or providing an example, but the enumerated elements give a solid picture. The sibling context does not demand additional clarification.

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, and the schema is trivially covered. Per the baseline for 0-parameter tools, the description need not explain parameter syntax. The absence of parameters is self-evident from 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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state'), enumerating the exact data elements (installed MCPs, connection status, accounts, catalog tool counts). This fully distinguishes it from siblings like authenticate, connect, marketplace, report_bug, and show_version, which serve entirely 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?

No explicit guidance is provided about when to use this tool versus alternatives. The description does not mention exclusions, prerequisites, or scenarios where another sibling tool would be more appropriate. Usage must be inferred solely from the described purpose.

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