SINTEGRA: CE

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

Description discloses important behavioral details beyond annotations: non-expiring connection with config, session-only with pasted token, and that calling with no args returns a login link. It does not contradict idempotentHint=true or destructiveHint=false, and the disclosure of token persistence and link generation adds useful behavioral context.

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 structured in three sentences and front-loads the core purpose. It is slightly dense with config instructions, but each sentence adds necessary usage detail without 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 one-parameter authentication tool with no output schema, the description covers both call modes (with and without token) and the persistence difference. It omits explicit return-value/error details, but the behavior is sufficiently clear for an agent to invoke the tool 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?

Input schema only defines a lone optional 'token' string with no description, and schema coverage is 0%. The description compensates by explaining the token is a JWT, how to pass it for session-only authentication, and that omitting it returns the login link. This fully clarifies the parameter's role and optionality.

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 identifies the tool's purpose: authenticating MCP.AI for IDE agents via a browser login and access token. It specifies the resource (MCP.AI) and action (log in/authenticate), and distinguishes it from sibling tools by describing a distinct login workflow.

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 context for when to use: IDE agents like Cursor, with clear options for permanent (config header) vs session-only (pasted token) authentication. It does not mention alternative tools explicitly, but the instructions give strong guidance on usage modes and when to call with or without the token parameter.

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 and idempotentHint=true, and the description reinforces a non-destructive read operation. It adds behavioral details about the return shape under different conditions. No annotation contradiction exists.

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, no filler. The description is front-loaded with the core purpose, then gives conditional behavior. Highly efficient and well-structured.

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 parametersching and good annotations (readOnly, idempotent), the description thoroughly explains both the success and failure states of the return. It doesn't need to explain return values further since it covers both scenarios. It's complete for this simple 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?

There are no parameters (0 params, schema coverage 100%), so the description doesn't need to explain params. It instead explains the return values, which is the key semantic information. The baseline of 4 applies since schema covers all 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 clearly states that the tool returns connection status and URLs, with specific response examples (authenticated:true and empty pending[] when all providers are connected, and connect_url and per-install URLs when credentials are missing). This fully explains the tool's purpose with concrete details.

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 no explicit 'when to use' is stated, the description implies usage for checking connection status and provides behavioral expectations (e.g., what happens when providers are connected or when credentials are missing). This is sufficient for a status-check tool with no prerequisites or 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?

Discloses many non-obvious behaviors: invoke runs tools without installation, returns connect/checkout links on auth/billing issues, and the description notes that writes require owner/admin. It also explains that search/describe flag installation status. 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?

A single massive paragraph with no headings or bullets, mixing languages and burying key points ('KEY:...') inside the flow. It is information-dense but poorly structured, making it hard 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 23-parameter, 14-action tool, the description covers the core search/describe/invoke flow, the prompt library, billing, auth, and permissions. However, actions like 'resume' are left undefined, and some edge cases may be lost in the disorganized text. Given the complexity, it's fairly complete but not exhaustive.

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 coverage, the description meaningfully explains the `action` enum and the relationships between mcp_id, tool_id, and prompt_* variables. However, many parameters (limit, query, immediate, tier_slug, cancel_*) receive no elaboration, though some are self-evident 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 states the tool is 'The official mcp.ai marketplace' and outlines a specific flow (search → describe → invoke). It names the resource (MCPs) and distinguishes multiple sub-actions like invoke vs install. However, the tool is a monolith covering many capabilities, which slightly dilutes the focus.

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?

Excellent guidance: explicitly says 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It explains the full flow, when to use request_mcp ('when nothing fits'), and warns about permissions for writes. It also contrasts with list_tools ('lists what is callable right now').

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 include idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds no behavioral context beyond the input instruction. It does not disclose what happens after reporting (e.g., whether it sends a notification, creates a ticket, or returns a confirmation), nor does it mention any side effects or prerequisites. With annotations available, some burden is lifted, but the description still lacks transparency about the tool's action.

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 extremely concise—two short sentences—and front-loads the purpose immediately. Every word contributes: the first sentence defines the scope, the second provides the key usage hint. No 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 tool is relatively simple with three parameters and no output schema, so the description need not be elaborate. It covers the core functionality and one critical input guideline. However, it omits details about the expected format of 'conversation' (e.g., a JSON string) and does not mention what the user should expect after invocation. For a reporting tool, that is a moderate gap but acceptable given the simple nature.

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 explains the 'conversation' parameter by asking to include it for reproduction, giving meaning beyond the schema's bare string type. The 'message' parameter is inherently clear from the tool's purpose, but 'context' is completely unaddressed. Thus, the description adds some value but does not fully compensate for the 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: 'Report a bug, missing feature, or send feedback.' This is a specific verb (report/send) with a clear resource (bug/feature/feedback) and distinguishes itself from sibling tools like authenticate, connect, 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 some usage guidance by instructing to 'Include the conversation array with recent messages for reproduction.' This tells the user what to provide. However, it does not explicitly state when to use this tool versus alternatives, though the sibling tools are clearly different in function, making the differentiation 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, so the safety profile is covered. The description adds value by specifying exactly what information is shown (MCP platform and adapter versions) and noting that they are 'current,' which gives context beyond the tool name.

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 concise sentence of 11 words, front-loaded with the action 'Show' and immediately stating the resource. Every word earns its place; there is no fluff, repetition, 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?

For a simple parameterless read-only tool with rich annotations, the description is largely complete. However, there is no output schema, and the description stops short of stating what the return value looks like (e.g., version strings or a structured object). This is a minor gap, but the tool is simple enough that the description suffices.

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 trivially 100%. The baseline for a parameterless tool is 4, and the description does not need to compensate for any missing parameter documentation. No additional parameter semantics are required.

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 as 'current MCP platform and adapter versions.' This clearly distinguishes it from sibling tools like authenticate, connect, and report_bug, 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?

The description implies usage—call this tool when you need to know the current platform and adapter versions—but provides no explicit guidance on when to use it versus alternatives. It does not state exclusions or mention that no authentication is needed, so the usage context 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 mark the tool read-only, idempotent, and non-destructive. The description adds valuable behavioral context: payment via prepaid credit, no need for platform credentials, data is not confidential, and the customer acts as data controller under LGPD. 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 front-loaded with the tool's purpose. It includes relevant operational, legal, and payment context, though 'fonte oficial' is somewhat repeated across sentences.

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 consultation tool with no output schema and no parameter descriptions, the description should clarify what data is returned, how 'ie' and 'cnpj' are used, and whether one is required. It provides good source/payment/LGPD context but lacks essential operational 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 input schema provides only the property names 'ie' and 'cnpj' with no descriptions, and the description does not mention or explain these parameters. With 0% schema description coverage, the agent is left to infer what 'ie' means and whether one or both fields are required.

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 names the specific resource ('SINTEGRA: CE') and the action ('consulta'), stating it queries information from official Brazilian sources. It is clearly distinguishable from sibling tools such as 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 provides clear usage context: it is hosted by the platform, requires prepaid credit, does not need platform credentials, and consults public/non-confidential official data. It does not explicitly discuss alternatives or exclusions, but the sibling tools are largely unrelated.

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, establishing the safety profile. The description adds valuable behavioral context by specifying the exact contents of the returned state (MCPs, connection status, accounts, catalog tool counts), going beyond what annotations alone reveal. No contradiction exists.

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 core action ('Returns the current toolkit state') and then lists the specific aspects covered. Every word serves a purpose, with no redundancy or filler.

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?

This is a simple read-only tool with no parameters and no output schema, so the description carries the full burden of explaining the return content. It fully enumerates the types of information returned, making the tool's behavior clear without needing an output schema. The description is complete for its 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 zero parameters, there is nothing for the description to explain about parameters. The schema is empty and the description correctly makes no parameter claims. The baseline of 4 is appropriate given the absence of any parameter complexity.

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 ('Returns') and resource ('current toolkit state'), and enumerates exactly what information it provides (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like authenticate, connect, and show_version, 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 does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions. However, its purpose is unambiguous given the sibling tools—it is the only one that reports on the overall toolkit state—so an agent can infer its appropriate use. A clear 'use this to check status' would have pushed this higher.

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