SINTEGRA: RR

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

Annotations indicate idempotentHint=true and destructiveHint=false; description doesn't contradict. It adds behavior details like returning a link when no token, and distinguishes between permanent and session login, but doesn't explicitly mention potential side effects like overwriting existing token.

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, dense paragraph, but it's front-loaded with the primary purpose and then details options. No wasted words, though it could be broken into bullet points for easier 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?

For an authentication tool with no output schema, it covers the main invocation scenarios (with/without token, config vs session) and describes the overall flow. Missing explicit return value formats, but adequate for 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 single parameter 'token' is clearly explained: it's a JWT to paste for session login, and the no-argument call is described. Since schema has no per-parameter descriptions, this fully compensates.

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 it handles authentication for IDE agents, with a specific action (log in, get token, configure). It distinguishes from siblings like 'connect' and 'report_bug' by focusing on 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?

Provides explicit guidance on when to use permanent config vs session token, and how to call with or without token. It even mentions the preferred approach (best: config header) and alternative, making usage 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, idempotentHint=true, and destructiveHint=false, covering safety. The description adds meaningful conditional behavior: 'authenticated:true and empty pending[]' versus 'connect_url for the toolkit and per-install URLs', which goes beyond the annotations. No contradiction is 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?

The description is two sentences, front-loaded with the core purpose, and contains no filler or repetition. Every clause contributes useful behavioral 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 zero-argument, read-only, idempotent status tool, the description covers the main states (all providers connected vs. missing credentials) and mentions returned URLs. It leaves minor gaps such as partial-connection behavior and exact URL structure, but these are not critical given the simple scope and strong annotations.

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 accepts zero parameters, so the schema description coverage is 100% and no parameter-level clarification is needed. The description appropriately focuses on output behavior instead of 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 uses a specific verb and resource ('Returns connection status and URLs') and clarifies conditional outcomes. It does not explicitly differentiate itself from the sibling 'authenticate' tool, but its read-only status-check purpose is unambiguous.

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 when checking connection status and describes expected results in different states. However, it provides no explicit guidance on when to use this tool versus alternatives like 'authenticate', and no exclusions or prerequisites are 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?

The description thoroughly discloses behavioral traits beyond annotations: invoke works for non-installed MCPs, returns connect/checkout links for auth/payment, requires owner/admin for writes, and explains the prompt library. This goes far beyond the sparse 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 information-dense, starting with the core purpose and then detailing flows and edge cases. It could benefit from headings or bullet points but remains organized and each sentence adds value.

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), the description covers discovery, execution, credential handling, payment, permissions, and the prompt library. It is exceptionally complete for an agent to understand when and how to use 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?

Despite 23 parameters and 0% schema coverage, the description adds meaning for the central `action` parameter and explains the purpose of mcp_id, tool_id, and arguments through the search/describe/invoke flow. However, many parameters (e.g., tier_slug, prompt_vars, cancel_reason) remain unexplained, leaving gaps.

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 is 'the in-platform catalog of every MCP/tool, AND the way to run them' and outlines a specific flow (search → describe → invoke). It differentiates from siblings by covering capability requests and offering unique actions like install and publish_prompt.

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?

Explicitly tells when to use invoke vs install ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use'), names alternatives like list_tools and subscribe/cancel, and provides the core flow with search/describe/invoke.

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 idempotentHint=true and destructiveHint=false, so the safety profile is known. The description adds that the conversation array aids reproduction, which is useful but does not disclose side effects, recipients, or response behavior. 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 concise sentences, front-loaded with the purpose and followed by a clear usage instruction. Every word adds value, with no redundancy or 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?

For a simple bug-reporting tool with no output schema and three parameters, the description covers the core purpose and the most important parameter guidance. The only gap is the 'context' parameter, which has a default and is likely optional, so the description is nearly 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 coverage is 0%, so the description must compensate for all parameters. It only explains 'conversation' as needing recent messages for reproduction, while 'context' and 'message' remain unexplained. 'Message' is implicitly the bug description but not explicitly stated.

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 'Report a bug, missing feature, or send feedback', using a specific verb and resource. This distinguishes it from the sibling tools, which are all unrelated authentication or lookup operations.

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 instructs to 'Include the conversation array with recent messages for reproduction', providing clear context for how the tool should be used. It does not explicitly list when not to use it or alternatives, but the purpose is self-evident and no conflicting tools exist.

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 already indicate read-only, idempotent, and non-destructive behavior. The description adds no extra transparency about side effects, permissions, or limitations, but given the simple getter nature, it is acceptable.

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 conveys the necessary information without any fluff or 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?

The description is sufficient for a simple read-only version getter. It does not elaborate on what 'MCP' stands for or what 'adapter versions' refer to, but these are likely understood from context, and the tool's simplicity does not require extensive additional 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 tool has no parameters, so there is no need for parameter descriptions. The schema confirms zero parameters, making this dimension trivially satisfied.

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 that the tool shows the current MCP platform and adapter versions, which is precise and directly reflects the tool's function. It is unambiguous and easy to understand.

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 versus alternatives like 'toolkit_info' or 'sintegra_rr_consultar'. It lacks context about typical usage scenarios or prerequisites.

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 annotations (readOnly, idempotent), the description adds valuable details: hosted by the platform, no credentials needed, pay-per-query, non-confidential data, and LGPD responsibility. 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 relatively concise, with the purpose front-loaded. Some sentences about legal liability (LGPD) are peripheral to tool usage but not excessive. It earns a 4 for efficient 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?

Given 2 optional parameters, no output schema, and existing annotations, the description provides useful context (pricing, data non-sensitivity) but lacks detail on response format, parameter usage, or examples. It is adequate but not comprehensive.

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 does not explain the parameters 'ie' and 'cnpj' at all. Schema coverage is 0%, so the description should compensate, but it only mentions 'SINTEGRA: RR' without connecting the parameters. Users must infer that 'ie' likely means Inscrição Estadual, but it's not stated.

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 it is a query (consulta) to official sources, specifically SINTEGRA RR, which differentiates it from the generic sibling tools like authenticate or show_version. However, it could be more explicit about the exact data returned (e.g., state registration info), so 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?

It mentions payment via prepaid credit and no platform credentials, giving practical usage context. It does not explicitly state when to use this vs alternatives, but since siblings are unrelated platform tools, that is less critical. It lacks explicit exclusions or preferred scenarios.

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?

While annotations already declare readOnlyHint and destructiveHint, the description goes further by detailing the exact information returned, such as 'connection status' and 'how many catalog tools each exposes'. This enriches the agent's understanding of the tool's behavior beyond the schema, making the operation fully transparent.

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 entire description is a single, well-structured sentence that front-loads the primary action ('Returns the current toolkit state') and then uses a colon and comma-separated list to add specifics. Every word earns its place, with no redundancy or 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?

For a simple, zero-parameter, read-only tool, the description is fully complete. It specifies what is returned (MCPs, connection status, accounts, catalog tool counts) without requiring an output schema, and it does not over-explain trivial details. It fully answers the likely questions an agent would have.

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 trivially 100% covered. According to the rubric, a 0-parameter tool earns a baseline of 4 since there is no parameter semantics to add; the description appropriately focuses on the output rather than 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 the verb 'Returns' and specifies the resource as 'the current toolkit state', followed by a detailed enumeration: 'installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes'. This clearly differentiates it from sibling tools like 'authenticate' or 'connect' which imply actions rather than state retrieval.

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 its use case by being a read-only state getter, but it does not explicitly state when to choose it over alternatives or mention any exclusions. There is no reference to sibling tools or 'use this when' guidance, so usage is only implied by the tool's name and descriptive content.

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