DER SP: DARE

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

The description adds meaningful behavioral context beyond the annotations by explaining permanent vs session-only auth behavior and the no-args link flow. It does not describe error handling or token validation, but the annotations already cover idempotency and non-destructiveness.

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 three sentences and packs substantial detail without fluff. It is slightly dense, but the core action and options are front-loaded and easy to parse.

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 tool with no output schema, the description covers the primary usage modes and the login-link result. It could be more explicit about what happens after a token is pasted, but overall it is sufficiently 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?

With 0% schema description coverage, the description fully compensates by explaining the optional 'token' parameter, its JWT shape, and the no-args alternative. This adds practical semantics that the schema alone does not convey.

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 an authentication/login flow for the MCP.AI server and IDE agents, explaining how to log in and use an access token. It is specific about the action and resource, though it does not explicitly distinguish itself from sibling tools 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?

It provides explicit usage guidance: prefer adding the token to server config for a permanent connection, paste a token for session-only login, or call with no args to receive the login link. This directly tells an agent when and how to invoke the 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 declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds valuable behavioral context: it explains the return values under different conditions (authenticated:true vs connect_url and per-install URLs), which goes beyond the 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 two sentences, front-loaded with the primary action ('Returns connection status and URLs') and then provides concise conditional specifics. Every sentence contributes meaning 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?

For a simple no-argument, read-only tool with no output schema, the description fully explains the expected return behavior in the key scenarios (all connected vs. missing credentials). It is complete and self-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 0 parameters and schema coverage is 100% (since there are none). The baseline for 0 parameters is 4 per guidelines. The description does not need to explain parameters, and it doesn't, 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?

The description clearly states 'Returns connection status and URLs,' which specifies the action (returns) and resource (connection status and URLs). It distinguishes from siblings like 'authenticate' and 'marketplace' by focusing on status information. The conditional details further clarify its purpose.

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 without explicitly stating when to use it instead of alternatives. It provides context by describing output scenarios (all connected vs. missing credentials), which suggests it is for verifying connection readiness, but it does not mention sibling tools or 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 convey read-only and idempotent behavior. The description adds valuable context about payment (prepaid credit), legal compliance (LGPD, data controller), and the nature of data (same as available to citizen, not confidential). This goes beyond the annotations without contradicting them.

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 front-loaded with the purpose and then provides context in a logical order. It is slightly verbose due to legal boilerplate, but each sentence contributes meaningful information about usage, payment, and data handling. No 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?

Given the absence of an output schema and zero parameter descriptions, the description should clarify both inputs and expected returns, but it does not. It covers high-level aspects like source and legal context but omits technical details, leaving the agent uncertain about what data to provide and what to expect.

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 has two parameters (ait, cnpj) with zero description coverage, and the description does not explain their meaning or usage. It never mentions cnpj or ait, leaving the agent without guidance on what values to provide. The description completely fails to compensate for the schema's lack of detail.

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: consulting DARE from DER SP in an official source. It uses a specific verb ('consulta') and resource ('DER SP: DARE'), and it stands apart from sibling tools like authenticate or report_bug, which are unrelated.

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 context for usage: it is hosted by the platform, requires no platform credentials, is paid via prepaid credit, and accesses non-confidential official data. However, it does not explicitly name alternatives or state when not to use the tool, so it falls short of a perfect score.

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 only declare readOnlyHint=false, openWorldHint=true, destructiveHint=false; the description carries the real behavioral burden and does so superbly. It discloses that invoke runs one-off even when the MCP is not installed without bloating the tool list, that credential needs yield a connect link and empty wallets yield a checkout/top-up link, and that writes (install/uninstall/subscribe/cancel and the hidden install behind invoke) require workspace owner/admin. It also flags the installed_in_toolkit vs installed_in_workspace distinction in search/describe. 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 (roughly 250 words), but proportionate to a tool with 14 distinct actions and 23 parameters. It is well-structured: core discovery flow first, then the pivotal invoke/install distinction, then peripheral actions, and a clearly delineated prompt-library paragraph. It is front-loaded with the highest-value information (the search → describe → invoke pipeline and the one-off invoke behavior). It loses a point only for sheer length; nearly every sentence earns its place.

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 tool this complex with no output schema, the description covers the critical flows and edge cases thoroughly: one-off invoke, auth/payment redirects, admin requirements, toolkit vs workspace flags, and the prompt library. The main gap is that it does not describe return shapes for any of the 14 actions (e.g., what search or list_tools returns), and a few peripheral params and the 'immediate' flag behavior are unaddressed. Still, the essential behavior surface is well covered.

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 across 23 params, the description must compensate, and it does well for the core flow: it maps action values to behavior, explains tool_id ('so you pick the right tool_id → invoke RUNS that tool'), arguments, mcp_id implicitly via describe, and tier_slug through subscribe. However, several params remain opaque: cancel_reason/cancel_comment, conversation, immediate, limit, prompt_title, and prompt_targets are never explained, though the prompt_* family is implied by the prompt-library section.

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 states the tool is the official mcp.ai marketplace catalog and runner. It names distinct verbs per action (search, describe, install, invoke, subscribe, cancel, report_bug, request_mcp, and the search_prompts/get_prompt/publish_prompt trio), each tied to a clear resource and outcome. It differentiates the marketplace from siblings like authenticate, connect, and toolkit_info by scoping it to discovering/running MCPs.

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?

Extremely explicit guidance: it lays out the core flow (search → describe → invoke) and gives a decisive when-to rule: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also explains list_tools as 'what is callable right now', distinguishes subscribe/cancel for billing, and details when invoke returns a connect or checkout link with a retry instruction. No ambiguity about when to reach for this 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 declare readOnlyHint=false and idempotentHint=true, so the description does not need to re-state those. It adds minor value by instructing to include the conversation array for reproduction, which hints at how the tool uses input. No contradictions 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?

Two sentences, front-loaded with purpose and a key usage hint. Zero unnecessary words, perfect for quick scanning.

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 (3 params, no output schema), but with zero schema coverage, the description should explain all parameters and any expected behavior. It covers purpose and conversation usage but omits context semantics and any post-report actions. Adequate for a basic internal tool, but not fully 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 only explains the conversation parameter (mentioned as 'conversation array'), leaving context and message semantics unaddressed. While message is inferable from the purpose, context is completely unexplained. This is insufficient for 3 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?

Description clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb and resource, and it distinguishes from all sibling tools as none of them handle reporting or feedback.

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 this tool—when users need to report a bug or send feedback. It also includes a practical instruction to include the conversation array for reproduction. However, it does not explicitly mention when not to use it or name alternatives, though the sibling list makes alternatives clear by their absence.

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, so the safety profile is clear. The description adds the 'current' scope but no additional behavioral context; it is consistent 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?

A single, concise sentence that is front-loaded. Every word is meaningful, 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?

The tool is simple with no output schema, and the description fully captures its purpose and expected capability. It is complete and self-sufficient for such a trivial operation.

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 coverage is effectively 100%. Per rubric, baseline for 0 parameters is 4; no parameter description is needed or provided.

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?

Clearly states 'Show the current MCP platform and adapter versions' with a specific verb and resource. It distinguishes itself from siblings like toolkit_info by focusing specifically on version information.

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?

No guidance on when to use this tool versus alternatives. The sibling toolkit_info might overlap, but no differentiation or usage context is provided in the description.

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 read-only, idempotent, and non-destructive behavior. The description adds valuable context by detailing exactly what the returned state includes (installed MCPs, connection status, accounts, tool counts), enhancing transparency without contradicting any 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 a single, well-structured sentence that lists all relevant details concisely without redundancy. It is appropriately sized for the tool's simplicity.

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 fully explains what the tool returns, covering all aspects (installed MCPs, connection status, accounts, tool counts). Given the lack of an output schema, this description is sufficient for the user to understand the tool's output completely.

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 has no parameters, and the description does not need to mention any. Since there are no parameters, the schema coverage is complete, and the tool's invocation is fully clear.

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 specifies the tool's purpose with a verb ('Returns') and defines the resource ('current toolkit state') with a distinct scope (installed MCPs, connection status, accounts, tool counts). It is unambiguous and differentiates from sibling tools that perform actions like authenticate or 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 provides clear context for when to use the tool (to retrieve toolkit state), but it does not explicitly state alternatives or when not to use it. Given the clear read-only nature and the sibling tools, it is obvious when to apply it, but explicit guidance is lacking.

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