SINTEGRA: BA

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

The description discloses the tool's dual-mode behavior (permanent vs session) and the difference in outcome when called with or without a token. It adds context beyond the annotations, such as the need for browser interaction to obtain the JWT, without contradicting the idempotentHint.

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 concise and well-organized, starting with the primary use case and then presenting options via 'Best' and 'Or'. It covers necessary details without redundancy or excessive length.

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 lack of an output schema, the description does a good job of explaining what the agent should expect: a link upon token-less invocation and successful authentication when a token is provided. It could include more error-handling details, but it is complete enough for this straightforward 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?

The schema's 'token' parameter has no description, but the description explains it is a JWT copied from the browser and that it is optional (omitting it yields the link). This fully clarifies the parameter's meaning and usage, compensating for the 0% schema coverage.

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 explicitly states the tool's function: 'log in in the browser, copy the access token' and provides two authentication options. It uses specific action verbs and clearly distinguishes this from connection tools by focusing on authentication, making the purpose unmistakable.

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 offers clear usage directives: either add the token to the server config as a header for a permanent connection, or pass it via the 'token' parameter for a session. It also specifies that calling with no arguments retrieves the login link, giving the agent concrete instructions on when to invoke each variant.

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 clear. The description adds behavioral context about response states (authenticated:true vs connect_url), which is useful. However, it does not disclose any potential side effects or additional behaviors beyond what annotations cover, but given the annotations are comprehensive, a 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 two sentences, front-loaded with the core purpose, and every sentence adds value. It efficiently conveys the tool's function and key response variations without any 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 the tool has no parameters, no output schema, and simple annotations, the description is complete enough. It explains the two main response states (all connected vs missing credentials) and mentions the URLs returned. It could potentially mention the exact structure of the response, but for a status-check tool, this is sufficient.

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 coverage is 100% (vacuously). The description adds value by explaining what the response will contain in different scenarios, which is the main semantic content for a parameterless tool. Since there are no parameters to document, the description's focus on output states is appropriate and earns a 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 returns connection status and URLs, and distinguishes it from siblings like 'authenticate' by focusing on status rather than initiating authentication. It specifies the resource (connection) and the action (returns status/URLs), which is clear 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 implies usage for checking connection status, but does not explicitly state when to use this tool versus alternatives like 'authenticate'. It provides context on what the response looks like in different states, but lacks explicit when-to-use or when-not-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?

The description reveals critical behavioral details well beyond the basic annotations: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit'; explains authentication/checkout link flows; mentions that writes require workspace owner/admin; and notes that subscribe/cancel handle per-MCP billing. There is no contradiction with the annotations (readOnlyHint=false, destructiveHint=false), and the text enriches understanding of side effects and prerequisites.

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 an extremely long, run-on paragraph with no formatting, headings, or bullet points, making it difficult to scan. While it contains a wealth of useful information, the lack of structure significantly hampers quick comprehension. For a tool with this many capabilities, the text would benefit from bolding, line breaks, or a list format.

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 (23 parameters, multiple sub-actions, and no output schema), the description covers all functional areas: marketplace catalog, one-off execution, installation, billing, bug reporting, feature requests, and prompt library. It also addresses edge cases (authentication, wallet top-up, permissions) and explains the distinction between one-off and permanent installations. This is a comprehensive overview relative to the tool's scope.

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 23 parameters and 0% schema description coverage, the description carries the full burden of explaining parameters. It clarifies the meaning and purpose of `action` (through enumeration of its values), `query`, `mcp_id`, `tool_id`, `arguments`, and several `prompt_*` parameters via the prompt library context. However, some parameters like `tier_slug`, `conversation`, `report_context`, and `cancel_reason` are only indirectly implied, so the description does not fully compensate for the schema's lack of detail. Still, the core flow is well documented.

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 and accurate statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then enumerates concrete actions (search, describe, invoke, install, subscribe, prompt library) and clearly distinguishes this umbrella tool from potential siblings. This is a detailed yet unambiguous definition of what the tool does.

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 which sub-action: 'prefer invoke for a single/occasional use' vs. 'Use install only to make an MCP PERMANENT'; differentiates report_bug/request_mcp; and explains that subscribe/cancel handle billing. It also gives a high-level flow ('search discovers MCPs by intent → describe returns profile → invoke RUNS') and notes when results appear (list_tools shows what is callable). This is outstanding guidance for selecting among 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 indicate non-destructive and idempotent behavior. The description adds the requirement to include the conversation array, which is useful context. It doesn't detail side effects or confirmation, but with annotations covering safety, this 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?

Two concise sentences with front-loaded purpose and no redundancy. Every word earns its place, making it highly 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 simple reporting tool, the description covers the main usage and the key parameter (conversation). However, it omits any description of the 'context' parameter and doesn't mention what happens after submission, leaving some gaps. 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?

Schema coverage is 0%, so the description must explain parameters. It implicitly covers 'message' (the bug/feedback) and explicitly mentions 'conversation' for reproduction, but provides no explanation for the 'context' parameter. Partial compensation only.

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 reports bugs, missing features, or feedback, with a specific verb and resource. It doesn't explicitly distinguish from siblings, but no sibling tool overlaps with this purpose, so it's 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 gives a clear context for when to use it (to report issues or send feedback) and instructs to include the conversation for reproduction, but doesn't mention alternatives or when not to use it. It's adequate for a self-contained 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 indicate read-only, idempotent, and non-destructive behavior, so the description need not duplicate that. It adds minimal context about what is shown (versions), but does not mention any potential side effects or prerequisites (e.g., authentication). With high annotation coverage, a score of 3 is reasonable.

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 sentence that is concise and directly states the purpose without any extraneous words. It is front-loaded and 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?

Given the tool's simplicity (no parameters, no output schema, well-covered annotations), the description provides sufficient information for an agent to select and invoke it correctly. It could arguably mention that no arguments are required, but the parameter count is zero and the schema makes that clear.

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 carries no parameter burden. The schema is minimal (empty properties), but the description clearly explains what the tool does without needing parameter details. Thus, a 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 clearly states the tool's function: displaying current MCP platform and adapter versions. It uses a specific verb ('show') and a specific resource ('versions'), and it is distinct from the sibling tools listed.

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 that the tool is for checking versions, but it does not specify when to use it versus alternatives, nor does it mention any context (e.g., after authentication or for troubleshooting). No explicit guidance is given.

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. The description adds valuable context beyond that: hosting, prepaid payment, data is non-confidential (same as citizen access), and LGPD compliance responsibility. This gives the agent awareness of cost, legal obligations, and data sensitivity nuances.

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 concise (three sentences) and front-loaded with the core purpose. It conveys essential operational and legal context without excessive verbosity. Each sentence adds information; no 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?

With no output schema and no parameter descriptions, the description should cover what the tool returns and parameter semantics. It only says 'consulta informação' without specifying output fields or structure. It also doesn't clarify whether exactly one identifier is required or combinations are allowed. This leaves significant gaps for an agent to use the tool effectively.

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% and the description does not explain the three optional parameters (ie, cpf, cnpj) or their usage. It doesn't state that these are alternative identifiers or that at least one is likely needed. The parameter names are self-explanatory to Portuguese speakers, but the description adds no semantic guidance beyond 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 clearly states it's a query tool for SINTEGRA BA (official Brazilian source) and clarifies it's hosted by the platform with no platform credentials required. It distinguishes purpose from sibling tools (which are about auth/utility), but doesn't specify exactly what data is returned (e.g., company registration 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?

The description provides context: it's an official source, pay-per-query, no credentials needed, and the client bears LGPD responsibility. However, it doesn't explicitly say when to use this vs alternatives (though siblings are unrelated). There's no exclusionary guidance, but the implicit use-case is clear for SINTEGRA lookups.

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 adds concrete details about return contents (installed MCPs, connection status, accounts, catalog tool counts). No contradictions. It adds behavioral context about what the tool reveals without overstating side effects.

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?

Single sentence, front-loaded with the primary action ('Returns the current toolkit state') and then lists the specific data items. No wasted words, highly scannable.

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 tool with no output schema, the description sufficiently covers what it returns. It doesn't describe the exact structure, but that's not critical given the tool's simplicity and the annotations already indicating safety. Could mention return format, but it's not a major 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?

There are 0 parameters and schema coverage is 100% (empty schema), so the baseline is 4. The description does not attempt to add parameter semantics because there are none; it focuses on the returned state information, which 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?

Description clearly states the tool returns the current toolkit state, listing specific components: installed MCPs, connection status, accounts, and catalog tool counts. This is a specific verb+resource (returns state) and distinguishes from siblings like authenticate (auth) and connect (establishing connections).

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?

Implied usage (when you need an overview of toolkit state) but no explicit when-to-use vs alternatives, exclusions, or prerequisites. For a simple info tool, this is acceptable but lacks clear guidance on when to call it over other tools.

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