SUSEP: Administradores

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

Beyond annotations, the description discloses the two modes of operation (session-only via pasted token vs. permanent via config header), and explains the browser login flow. It does not contradict annotations; idempotentHint=true is consistent with the token/no-args behavior. It could add response details but overall is 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?

Two sentences, but the first is slightly rambling ('MCP.AI for IDE agents...'). The key information is front-loaded, and every part adds value, but a more structured format would improve scannability. Still concise overall.

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 auth tool with no output schema, the description covers the main flow, parameter behavior, and the two integration methods. It implicitly describes return behavior (getting a link). Lacks explicit success/failure details, but is adequately complete 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 schema has only 'token' with no description, leaving 0% coverage. The description fully compensates by explaining the token parameter as a JWT to paste, and the no-arg behavior to get the link, including example syntax. This is excellent compensation for the schema gap.

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: authenticate/log in via browser and token. It specifies the resource (MCP.AI server) and the action (login, token exchange), and distinguishes itself from sibling tools like 'connect' or 'marketplace' as the auth-specific entry point.

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 context for when to use (IDE agents like Cursor) and explicitly recommends the best integration method (adding an Authorization header to the config for a permanent connection). It does not explicitly list alternatives or exclusions, but the context makes the appropriate use 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 indicate read-only, idempotent, and non-destructive behavior, so the description's added value lies in specifying the output structure for different states (authenticated vs. missing credentials). It provides concrete behavioral expectations beyond the 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?

Two sentences, with the first stating the core purpose and the second covering the conditional scenario. It is front-loaded, precise, and contains no filler 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 simple (no params, read-only, no output schema), and the description covers the key return values and the two main states. It is sufficient for an agent to understand what to expect, though it could mention that it is a status check for troubleshooting or pre-authentication validation.

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 carries no burden. The description adds no parameter-related info, but it explains behavioral variance (different outputs depending on connection state), which is more relevant. Given zero parameters, 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 returns connection status and URLs, with specific details on the two possible outcomes based on credential state. This differentiates it from siblings like authenticate, which is about performing authentication rather than checking status.

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 and mentions the conditional behavior, but does not explicitly state when to use it vs. alternatives (e.g., 'Use authenticate to establish a connection'). The context is clear but lacks explicit exclusions or alternative suggestions.

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 rich behavioral traits beyond annotations: invoke works on non-installed MCPs as one-off, returns connect/checkout links on auth/payment failure, does not bloat tool list, and the prompt library returns shareable links. The annotations (openWorldHint=true, readOnlyHint=false) are consistent with these behaviors, and the description adds significant context about 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 a single dense paragraph, quite long and not broken into sections or bullets. While front-loaded with the core purpose, it becomes hard to scan and buries details like auth requirements and prompt library in the middle. It is informative but not concise; every sentence earns its place, but structure could be improved.

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 high complexity (14 actions, 23 params) and no output schema, the description covers major contexts extensively: discovery flow, one-off invocation, auth/billing fallbacks, installation semantics, permission requirements, and prompt library. Gaps remain (e.g., 'resume' action, error handling), but overall it is nearly complete for an agent 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?

Schema has 23 parameters with 0% description coverage. The description compensates by explaining the action enum and core parameter roles (mcp_id, tool_id, arguments, prompt_*), but does not explicitly map every parameter (e.g., limit, immediate, tier_slug). The conceptual overview covers the most important semantics, though some parameters remain undefined.

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 what the tool does: it is the official mcp.ai marketplace, catalog of every MCP/tool, and the way to run them. It enumerates concrete actions (search, describe, invoke) and distinguishes from siblings by positioning itself as the central discovery/execution hub, unlike authenticate/connect or show_version.

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 when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'install only to make an MCP PERMANENT in the active toolkit', plus distinct flows for billing (subscribe/cancel), feedback (report_bug), and new MCP requests (request_mcp). Also states owner/admin requirement for writes, helping choose between 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 idempotentHint=true multiplayer and non-destructive, covering the safety profile. The description adds the instruction to include a conversation array for reproduction, which is useful but not a behavioral trait per se. It doesn't disclose what happens after submission (e.g., creates a ticket) or any side effects beyond what annotations already imply. Given annotation coverage, this is adequate but not exceptional.

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 that front-load the purpose. No fluff, no redundancy. Every word adds value, including the specific instruction to include the conversation for reproduction.

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 simple with 3 parameters serious, and the description covers the core purpose and key usage instruction. Despite having no output schemaChinese, the description doesn't explain what happens after reporting (e.g., response format), but for a feedback tool that may be acceptable. It does mention the crucial need for reproduction context. Missing param detail prevents a 5.

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 coverage is 0%, so the description must clarify parameter meanings. The description mentions 'conversation array' (parameter 'conversation') and implies 'message' as the content of the bug/feedback, but the 'context' parameter is entirely unexplained. With 3 parameters and one left undefined, the description only partially compensates for poor schema coverage. An agent would need to guess the purpose of 'context', making this a weak area.

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: reporting bugs, missing features, or feedback. It uses a specific verb (

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 explicitly states when to use the tool ('Report a bug, missing feature, or send feedback') and provides a key instruction ('Include the conversation array with recent messages for reproduction'). It doesn't explicitly compare to alternatives, but the sibling tools are unrelated, so the context is clear enough. A 4 is warranted for clear guidance without exclusions.

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 the specific behavior of showing versions, which goes beyond annotations by specifying what is returned, without contradicting any hints.

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, front-loaded sentence with no unnecessary words. It perfectly fits the 'Show' + resource structure and earns its place without 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's simplicity (no parameters, no output schema, read-only), the description fully covers what is needed. It informs the user that it shows both platform and adapter versions, which is complete for a version-display 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 tool has zero parameters, and schema description coverage is trivially 100%. Per the rubric, a baseline of 4 applies to zero-parameter tools, and there is no parameter documentation needed beyond that.

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 'Show the current MCP platform and adapter versions.' clearly states the verb 'Show' and the specific resource (MCP platform and adapter versions), distinguishing it from sibling tools like connect and authenticate. It is concise and not a tautology.

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 no guidance on when to use this tool versus alternatives (e.g., 'toolkit_info'). There are no explicit when/when-not conditions or alternative tool names mentioned, leaving the agent without context for 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?

The annotations declare readOnlyHint, idempotentHint, and destructiveHint=false, and the description is consistent with these. The description adds substantial context beyond annotations: prepaid per-query cost, no platform credentials required, public/non-confidential data, and LGPD controller obligations, which helps the agent assess risk 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 compact and front-loaded with the core purpose, and most sentences carry distinct information about cost, credentials, and legal responsibility. Sentence 3 partially repeats the 'official source' idea from sentence 1, which keeps it from being maximally tight.

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 read-only tool with strong annotations, the description covers cost, authentication, data sensitivity, and legal responsibilities. It does not describe the return shape or CNPJ formatting, but the tool is simple and the annotations already convey the safety profile.

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 has one required cnpj string with no field description and 0% schema description coverage. The description never mentions cnpj or explains its format or meaning, so it adds no parameter-level value beyond the bare property name.

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 SUSEP Administradores as the resource and uses 'consulta' to indicate a query against an official source. It is clear enough and distinguishes itself from the unrelated sibling tools, though it does not detail what administrator data is returned.

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 useful usage context: it is hosted without platform credentials, paid via prepaid credits, and subject to LGPD responsibilities. However, it does not explicitly state when to use this tool over alternatives or when not to use it, so usage guidance remains implied rather than explicit.

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 valuable detail about the exact return contents (installed MCPs, connection status, accounts, catalog tools), which goes beyond annotations and helps the agent understand what information to expect. 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, front-loaded sentence that perfectly encapsulates the tool's purpose and output. Every word contributes meaning, with no fluff or redundancy. This is an exemplary model of brevity.

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 a straightforward read-only purpose, the description fully specifies what the agent can expect. It covers the key aspects of the returned state without needing additional detail. The simplicity of the tool makes this 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 and an empty input schema, so schema coverage is effectively 100% and there is nothing for the description to add. With no params, a baseline of 4 is appropriate, but the description's clarity about the static nature of the call (no inputs needed) earns a 5.

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 toolkit state, specifying the exact contents: installed MCPs, connection status, accounts, and catalog tool counts. This is a specific verb+resource with clear scope, distinguishing it from sibling action-oriented tools like connect or authenticate.

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 for checking state before performing actions, but provides no explicit 'when to use' or 'when not to use' guidance, and does not mention alternatives. For a simple info tool, the context is reasonably clear, but it lacks the explicit guidance seen in higher-scoring examples.

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