ECRVSP Estampagem: Autorização

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

The description adds behavioral details beyond annotations, such as permanent vs. session-only connection and the need for user browser interaction. However, it does not fully disclose potential side effects or state changes beyond what is hinted.

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 relatively wordy with multiple clauses ('MCP.AI for IDE agents...', 'Best:...', 'Or...'), which could be streamlined. It is not overly long but lacks clear structure.

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 a single parameter, the description covers the essential usage scenarios (permanent and session) and the input behavior, making it fairly complete despite 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 description clearly explains the 'token' parameter: it is a JWT to paste for session login, and calling without args returns a link. This adds meaning beyond the schema's bare string type.

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 it is for IDE agents and mentions logging in, but it does not explicitly say 'authenticate' and starts with a vague 'MCP.AI for IDE agents'. The purpose is implied but not clearly stated as a concise verb+resource phrase.

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 two usage methods (permanent config vs. session token) with specific instructions on when to use each, but does not contrast with alternatives or explicitly state when not to use this 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 readOnly, idempotent, non-destructive. Description adds specific behavioral details: return format when all connected vs when credentials missing, and that it returns per-install URLs. 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?

Two sentences, very focused, front-loaded with the main purpose, then conditional details. 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?

Given it's a read-only status tool with no parameters and no output schema, the description covers the two main states (connected vs missing credentials) and what URLs are returned. It could mention what happens when partial connection, but for such a simple tool, it's near 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?

Tool has zero parameters, and schema descriptions coverage is 100%, so schema fully documents. Description adds no param info needed; baseline 4 for 0 params.

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 clearly states the tool returns connection status and URLs, with specific behavior for connected and missing-credential states. It distinguishes from siblings like authenticate (which likely initiates auth) and toolkit_info (general 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?

Implies usage: call to check connection status before operations. Does not explicitly say when not to use or name alternatives, but context from sibling names (authenticate) makes it clear this is for checking status, not performing auth.

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 read-only/idempotent/non-destructive; the description adds meaningful behavioral context: payment via prepaid credits, no platform credentials, data source equivalence to citizen-accessible official information, and LGPD data-controller responsibility. 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 compact and purpose-first, with four short sentences covering payment, source, and legal context. Slight redundancy exists between 'consulta em fonte oficial' and 'Consulta informação de fontes e órgãos oficiais brasileiros', but it remains efficient.

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 7-parameter tool with no output schema and no parameter descriptions, the description provides useful high-level context (official source, payment, LGPD) but lacks parameter semantics and return-value expectations, making it adequate but not fully 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?

Schema description coverage is 0% and the description does not explain required parameters such as a3, a3_pin, login_cpf, or login_senha. It only hints that the credentials are not platform credentials and that consultation is paid, leaving parameter meaning largely to inference from 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 clearly identifies the tool as a query/consulta for ECRVSP Stampagem Authorization data from official Brazilian sources ('consulta em fonte oficial'). It distinguishes this from generic sibling tools by naming the specific official-source query domain, though it does not explicitly contrast it with siblings.

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 operational context: the tool is hosted by the platform, requires no platform credentials, works on prepaid per-query credit, and concerns non-confidential official data. It implies when to use it but does not explicitly list when not to use it or name alternative tools.

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 minimal annotations (readOnlyHint=false, openWorldHint=true, etc.), the description discloses rich behavioral detail: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente... without adding the MCP to the toolkit,' connect-link behavior for missing credentials, 'checkout/top-up link (the user opens it, then you retry)' for empty wallets, and permission requirements ('Writes... require workspace owner/admin'). No contradiction with annotations — openWorldHint=true aligns with invoking uninstalled MCPs and readOnlyHint=false aligns with the stated 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?

The description is front-loaded with the core purpose and every clause adds distinct information (one-off invoke semantics, connect/checkout links, install permanence, permissions, prompt library). However, it is a ~330-word single paragraph with run-on sentences and semicolon chains; it restates invoke behavior across multiple clauses and lacks any bullet/section structure, making it harder for an agent to parse quickly.

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 15 enumerated actions, 23 parameters, and no output schema, the description thoroughly covers the action taxonomy and exception behaviors (auth links, payment links, admin permissions, one-off vs permanent). But it never describes return values or response shapes for search/describe/invoke (no output schema exists to compensate), and the 'resume' action plus 'immediate' parameter are entirely unexplained — a meaningful gap at this complexity level.

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 across 23 parameters, the description must carry the burden. It does give meaning to the central flow parameters (action='search→describe→invoke', mcp_id, tool_id, arguments, prompt_slug/prompt_vars via '{{variables}} filled'). However, many parameters remain opaque — immediate, conversation, limit, query, request_name, request_details, prompt_targets, prompt_category, prompt_description, tier_slug — so the compensation is only partial for a 23-parameter surface.

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 specific statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' clearly identifying the resource and its dual role of discovery and execution. It distinguishes itself from siblings by positioning itself as the catalog/runner (vs. authenticate, connect, toolkit_info, etc.), but the tool bundles two distinct domains (MCP management and prompt library), which slightly dilutes single-purpose clarity.

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?

Extremely explicit guidance: 'prefer invoke for a single/occasional use; use install only to make an MCP PERMANENT,' and it names alternatives for every sub-action — 'subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits; list_tools lists what is callable right now.' It also clarifies when the prompt-library functions apply versus MCP functions. No exclusions needed.

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 idempotent=true and destructive=false, lowering the burden on the description. The description adds valuable context beyond annotations by instructing the agent to include the conversation array for reproduction, which clarifies expected input behavior. No annotation contradictions present.

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 tightly packed sentences with zero fluff. The first sentence front-loads the tool's purpose, the second delivers the critical usage detail. Every word 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 3-parameter feedback tool with annotations and no output schema, the description adequately covers the tool's purpose and key input consideration. Only minor gaps around post-submission behavior prevent a 5, which is largely immaterial for fire-and-forget feedback tools.

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 carries full burden for explaining parameters. It meaningfully covers the 'conversation' parameter's purpose ('recent messages for reproduction') but leaves 'context' and 'message' unexplained. The single tip helps but is insufficient compensation for 3 undocumented parameters.

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+resource structure ('Report a bug, missing feature, or send feedback') that clearly states what the tool does. It's distinguishable from the siblings (authenticate, marketplace, etc.) even though it doesn't name alternatives explicitly.

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 through its enumerated use cases (bug, missing feature, feedback), but provides no explicit when/when-not guidance or named alternatives. The 'Include the conversation array...' sentence gives a usage tip but for parameter filling, not tool selection.

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 safety profile is well covered. The description adds that it shows both MCP platform and adapter versions, which is a useful detail beyond the bare 'show_version' name. 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?

The description is a single, clear sentence that gets straight to the point. Every word earns its place, with no fluff or unnecessary detail.

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 extremely simple with zero parameters and no output schema. The description is sufficient for an agent to understand what the tool does. It could potentially mention return format, but with no output schema, it's not required. Given the low complexity, the description 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?

The tool has zero parameters, so the description doesn't need to explain parameter semantics. The schema has 100% coverage (empty object), and the description adds context about what the output relates to (platform and adapter versions), even though no output schema exists.

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: it displays the current MCP platform and adapter versions. The verb 'show' and the resource 'versions' are specific. However, it doesn't explicitly differentiate from siblings like 'toolkit_info', which might also provide version info, so it's not a 5.

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 implicitly indicates when to use this tool (to check versions) but gives no explicit guidance on when not to use it or mention alternatives like 'toolkit_info'. Given it's a simple standalone tool, the context is somewhat clear but lacks explicit 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds transparency about the scope of the introspection result, but it does not mention details like whether it contacts external systems or might be stale — though this is not a significant omission for such a tool.

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, well-formatted sentence with a front-loaded verb and outcome. Every phrase is informative, and the return categories are itemized in a compact way without unnecessary prose.

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 toolkit status tool with no output schema, the description is complete: it specifies exactly what categories of results will be returned. The strong annotation metadata plus the enumerative description are enough to select, invoke, and interpret the result.

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 schema coverage is complete, so there are no parameter semantics gaps to fill. The baseline of 4 applies here since the description does not have to compensate for undocumented 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 a specific verb ('Returns') and identifies a concrete resource ('current toolkit state') while enumerating the returned data: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like connect, authenticate, and show_version, which cover actions or versioning.

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 this tool is for inspecting the current toolkit and MCP connection state, making it the natural diagnostic/status tool. However, it does not explicitly call out when to prefer this over a sibling like show_version or state exclusions, so it stops just short of a 5.

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