SINTEGRA: PR

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

Annotations already indicate idempotent and non-destructive behavior; the description adds valuable context about the non-expiring config-based approach versus session-only token login, and that calling with no args returns a link. It does not fully disclose token storage or response details, but the key behaviors are surfaced.

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, front-loaded with the audience and action, and uses a clear 'Best' / 'Or' structure for alternatives. It is slightly dense and runs multiple instructions into one long sentence, though nothing is wasted.

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 one-parameter authentication tool with no output schema, the description covers the main workflows: obtaining a link, pasting a token for session login, and the recommended permanent config approach. It could mention the response after a successful token call or failure modes, but those are minor 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?

The input schema only lists an optional string 'token' with no description, so the description carries full weight. It explains that the token is a JWT to paste after the user provides it and distinguishes that omitting it returns the login link.

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 defines the tool's purpose: authenticating this MCP server with MCP.AI for IDE agents, including the browser-login/link flow and token submission. It is specific and actionable, but it does not explicitly distinguish this tool from siblings like '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 gives explicit when-to-use guidance: 'Best: add it to this server's config as a header' for permanent access, and 'Or paste it here for a session-only login' for tool invocation. It also clarifies exactly when to call with a token versus with no arguments.

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 repeat safety traits. It adds useful context about the two return scenarios (authenticated:true with empty pending[] vs connect_url when credentials missing), enhancing transparency 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 two sentences, front-loaded with the main purpose, and efficiently explains the conditional outcomes without redundancy. Every word contributes to understanding the tool's behavior.

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 has no parameters, no output schema, and annotations covering safety, the description fully explains what the agent will receive in both possible states. It is self-sufficient for a status-check tool and clearly differentiated from siblings.

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 is fully covered (100%). The description adds no parameter details, but none are needed. Baseline for 0 params is 4, and the description doesn't introduce any ambiguity, so it earns this.

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, with a specific verb 'Returns' and resource 'connection status and URLs'. It distinguishes from siblings by focusing on connectivity and authentication status, unlike 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?

It provides contextual guidance by explaining when credentials are missing (returns connect_url for toolkit and per-install URLs), implying usage for checking connectivity or obtaining authentication URLs. However, it doesn't explicitly mention when not to use it or contrast with siblings like authenticate.

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 discloses key behavioral traits beyond annotations: the one-off install behind invoke (side effect), the fact that invoke returns connect/checkout links when credentials/wallet are needed, and that writes require workspace owner/admin. It also clarifies that invoke does not bloat the tool list. These are subtle, high-value details that annotations alone (readOnlyHint=false, openWorldHint=true) do not convey. 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 and dense, but structured: core purpose -> core flow -> key invoke/install distinction -> safety/permissions -> prompt library. Every sentence adds value, though there is slight redundancy ('pontualmente' and 'one-off' repeated). It is appropriately detailed for the tool's complexity, but could be tightened without losing 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 highly complex tool with 14 actions, 23 parameters, no output schema, and no parameter descriptions, this description covers the essential flows thoroughly: discovery, execution, installation, billing, permissions, and prompt library. It does not explain every action (resume, immediate, tier_slug) or output formats, but an agent can infer most invocation patterns. Overall, it is nearly complete for practical 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?

With 0% schema description coverage, the description carries the full burden. It explains the meaning of several parameters through context: action (all enum values mapped to flows), mcp_id, tool_id, arguments, prompt_vars, and more. However, many parameters (immediate, tier_slug, resume, prompt_tool, conversation, report_context, etc.) are not explicitly described, leaving some gaps. The description compensates significantly but not completely 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 identifies the tool as the official mcp.ai marketplace, functioning as both a catalog and execution environment for MCPs/tools. It explicitly names the core actions (search, describe, invoke) and distinguishes from siblings by being the central hub for discovery, running, installation, and billing. The verb+resource is specific and comprehensive.

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: '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 contrasts invoke vs install clearly and even covers the prompt library as a separate capability with its own search/get/publish flow. This is excellent when-to-use 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 convey readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds that the conversation array aids reproduction, but does not disclose side effects such as where the report goes or whether confirmation is returned. 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 two sentences, front-loaded with the core purpose, and contains no redundant or filler content. Every sentence contributes useful 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 feedback tool, the description covers the main purpose and one key parameter. However, it omits guidance on the required 'message' field and the optional 'context' field, and it does not clarify the string-serialized array format of 'conversation'. The absence of an output schema reduces the need for return-value details, but the parameter gaps keep this from being 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%, so the description must compensate. It adds meaning for 'conversation' by calling it an array of recent messages, but it does not explain the required 'message' parameter or the optional 'context' parameter. This is insufficient compensation for the complete lack of schema descriptions.

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 function with a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'). It is immediately distinguishable from sibling tools like authenticate, marketplace, or sintegra_pr_consultar.

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 ('Report a bug, missing feature, or send feedback') and gives one usage hint about including the conversation array. However, it does not explicitly discuss alternatives or exclusions, leaving the usage guidance somewhat 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety profile. The description adds no extra behavioral context beyond stating what it shows, but it does not contradict annotations. Given the annotation coverage, a score of 3 is appropriate.

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. It front-loads the action and resource, making it immediately understandable.

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 version-check tool with no parameters, no output schema, and safety annotations present, the description adequately covers what it does. It could optionally elaborate on what 'platform and adapter versions' entails, but the current level is sufficient for an agent to use it 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?

There are no parameters, so the schema provides complete coverage (100%). The description adds no parameter-specific information, which is unnecessary here. Baseline for no parameters 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 tool displays current MCP platform and adapter versions, using a specific verb ('Show') and resource ('versions'). This distinguishes it from sibling tools like authenticate, connect, and toolkit_info, 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 implies use whenever version information is needed, but provides no explicit guidance on when to use it versus alternatives, nor any exclusions. Since it's a trivial info-gathering tool, this is acceptable but not explicitly stated.

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, consistent with the description's 'consulta' wording. The description adds valuable behavioral context: the platform hosting, lack of platform credentials, prepaid credit per query, and LGPD compliance. It also clarifies the data is not confidential, which is useful risk-relevant info. No contradictions found.

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—a single paragraph of three sentences—and front-loads the core purpose ('SINTEGRA: PR, consulta em fonte oficial'). It avoids redundancy and wastes no words, though it interleaves legal/payment details that could be considered secondary. Overall, it's well-structured for quick parsing.

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 5 parameters, no output schema, and only basic annotations. The description covers payment and legal aspects but fails to explain parameter usage, expected return format, or any constraints (e.g., which identifiers can be combined). This leaves agents underinformed about how to invoke the tool effectively, making it incomplete for its complexity.

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 provides zero explanation of the five parameters (ie, cpf, cnpj, ie_produtor, cnpj_produtor). The description does not compensate for the schema gap—it never mentions what identifiers are needed or how they relate to the query. This is a significant deficiency for a tool with multiple identifier types.

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 query ('consulta') on SINTEGRA PR, an official Brazilian source. It identifies the resource and distinguishes from generic sibling tools (auth, connect, etc.) by specifying the domain. However, it doesn't explicitly mention what specific data is returned or how the parameters map to queries, leaving some ambiguity.

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 context (official source, paid, no credentials) but never states when to use this tool versus alternatives or when not to use it. It implies usage for querying Brazilian official data, but there are no explicit exclusions or alternative tool references. This is sufficient for a simple consult tool with no competing siblings, but lacks direct 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, covering the safety profile. The description adds value by specifying exactly what data it returns (MCPs, connection status, accounts, tool counts), which goes beyond annotations. No contradictions.

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-structured sentence that front-loads the purpose and lists the returned components efficiently. Every word earns its place with zero 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?

Given the tool's simplicity (no parameters, no output schema), the description is complete: it describes what is returned in enough detail for an agent to understand the tool's output. Annotations cover behavioral aspects, and no further info is needed.

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 baseline is 4. The description does not need to add parameter details; it already fully explains what the tool does, and the schema is empty. No additional compensation 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 uses specific verb 'Returns' and clearly defines the resource as 'toolkit state' with detailed components (installed MCPs, connection status, accounts, catalog tools). It is distinct from siblings like show_version or connect, which have 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?

While the description clearly indicates it is a status/info tool, it does not explicitly state when to prefer it over alternatives or mention any exclusions. However, the context makes its use case obvious—checking toolkit state—so it meets the baseline without explicit guidance.

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