SENATRAN: Recall

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

Adds meaningful behavioral context beyond annotations: browser login flow, permanent vs. session-only connection, and that no args returns a link. Annotations already indicate idempotency and non-read-only, and the description does not contradict 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?

Two dense, purposeful sentences with clear formatting for code and token values. No filler; every clause adds necessary information about the auth workflow.

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 auth tool with one optional parameter and no output schema, the description covers the workflow, token format, and two usage modes. It omits explicit error/response details, but that is not critical for this tool's selection and invocation.

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 only defines 'token' as an optional string, but the description explains it is a JWT, that it is pasted by the user, and that omitting it triggers link generation. This fully compensates for the 0% schema description 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 clearly identifies the tool as the authentication mechanism for MCP.AI IDE agents, with a specific verb ('log in', 'copy the access token') and resource. It distinguishes itself from sibling tools by focusing solely on the auth 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 usage context: permanent config-header auth vs. session-only token paste, and when to call with no args vs. with a token. It does not explicitly mention when not to use the tool or name alternatives, but the two-mode guidance is strong.

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, idempotentHint, and destructiveHint as safe/read-only. The description adds meaningful behavioral context beyond that: it specifies two conditional states (autenticado vs pending/connect URLs) and what the response contains in each case. It adds value without contradicting 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?

The description is two sentences, front-loaded with the core purpose ('Returns connection status and URLs'), and every sentence adds needed detail. There is no redundant wording or repetition of schema/annotation 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?

Given zero parameters, no output schema, and strong annotations, the description fully covers functional behavior for this low-complexity tool. It explains both common states (all connected vs credentials missing) and what URLs are returned in each state, making it complete for the agent to select and invoke 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?

There are no parameters, and the schema coverage is 100% because the schema is empty. With 0 parameters, the baseline is 4, and the description adds useful context about what the returned status/URLs mean without needing to describe 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 a specific verb ('Returns') and a clear resource ('connection status and URLs'), and clearly distinguishes the tool from siblings like 'authenticate' by indicating it reports status rather than initiating authentication. The two conditional result cases further clarify exactly 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 conveys that this tool is for checking connection status and obtaining URLs when credentials are missing, making its primary use case clear. It does not explicitly mention when not to use it or name alternatives like 'authenticate', but the intent is strongly implied and clear enough.

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 indicate non-readonly/non-idempotent, but the description adds rich behavioral detail: invoke runs tools even when not installed (one-off), returns connect/checkout links when credentials or payment are needed, and requires workspace owner/admin for writes. It also explains installed status flags and prompt links that open without login.

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 dense but every sentence earns its place, front-loading the core purpose and flow in the opening lines. It covers the entire MCP lifecycle and prompt library without fluff, and the length is justified by the tool's broad functionality (14 actions, 23 params).

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 covers the full journey from search to invoke, including auth/payment edge cases, permission requirements, and result behavior (connect/checkout links, prompt share links). However, it omits details about search result shape, pagination, and the 'resume' action, which would be needed for fully confident use given there is no output schema.

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 compensates by explaining the core action enum and key parameters like action, mcp_id, tool_id, and arguments through the flow. However, several parameters (immediate, conversation, tier_slug, prompt_targets, cancel_reason) remain unexplained, and the mapping between each action and its required params is not fully explicit.

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 the official mcp.ai marketplace and the way to run MCPs/tools, covering capability requests and the search→describe→invoke flow. It distinguishes itself from sibling tools like authenticate, connect, and toolkit_info by focusing on catalog discovery and execution.

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 explains when to use invoke vs install, stating 'prefer invoke for a single/occasional use' and 'install only to make an MCP PERMANENT in the active toolkit.' It also gives clear roles for list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt library actions, providing strong guidance on tool 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?

Annotations already provide safety profile: idempotentHint=true, readOnlyHint=false (not read-only), destructiveHint=false. The description adds little beyond restating purpose, but it does not contradict annotations. It does not disclose any additional behavioral details (e.g., how the report is handled, whether confirmation is returned), but given the simple reporting nature and annotation coverage, 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 a single sentence that front-loads the purpose and immediately follows with a usage hint. There is zero filler or redundancy. Every word earns its place, making it highly concise 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?

For a relatively simple tool with no output schema, the description covers the core purpose and one usage nuance. However, it omits any explanation of the required message parameter and the optional context parameter, which are essential for correct invocation. It is adequate but has clear gaps in parameter coverage, warranting a mid-range score.

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 for explaining parameters. It only mentions 'conversation array' but does not clarify the required 'message' parameter or the optional 'context' parameter. This leaves the agent with incomplete understanding of how to invoke the tool correctly, despite the description hinting at one parameter.

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: 'Report a bug, missing feature, or send feedback.' This is a specific verb+resource combination that distinguishes it from all sibling tools (authenticate, connect, marketplace, etc.), which perform unrelated functions. It is explicit and action-oriented.

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 clear guidance on when to use the tool (for bug reports, feature requests, or general feedback) and includes an actionable instruction: 'Include the conversation array with recent messages for reproduction.' This provides contextual usage direction, though it does not explicitly mention alternatives or when not to use it—unnecessary since no siblings overlap.

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 declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds extra context: no platform credentials, per-query billing, official non-confidential data source, and LGPD controller responsibilities. This goes well beyond the structured 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, front-loaded, and every sentence carries distinct value: purpose, hosting/credential model, data scope, and legal responsibility. There is no wasted text or tautological padding.

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 two-parameter read-only tool with good annotations, the description covers the operational and legal context very well. The main minor gap is the lack of any stated return/output expectations, especially since there is no output schema to fill that 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?

Schema description coverage is 0%, and the description never mentions 'placa' or 'chassi', nor does it give format, relevance, or usage guidance for the parameters. The agent must infer everything from the raw property names, so the description adds no parameter-level meaning.

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 a SENATRAN recall consultation backed by an official source. The verb 'consultar' and resource 'Recall da SENATRAN' are explicit, and the purpose is distinct from sibling tools like authenticate, marketplace, and report_bug.

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 clear usage context: query official Brazilian recall data without platform credentials, paying per query with prepaid credit. It does not explicitly state when not to use it or name alternatives, but none of the sibling tools are recall-related, so the context is sufficient.

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 the safety profile. The description adds the word 'current', implying live state, but provides no further behavioral context such as output format or whether authentication is needed. This is acceptable given strong annotations but adds limited value beyond 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 a single, front-loaded sentence that directly states the tool's function without any wasted words or redundant phrasing. Every word 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?

This is a trivial, zero-parameter read-only tool with strong annotations. The description fully captures its purpose, and no output schema or complex behavior needs elaboration. The context signals confirm low complexity, so the description is complete for an agent to invoke 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?

The input schema has zero parameters, so the description need not explain parameter semantics. The baseline of 4 applies, as no parameters exist to document and the description correctly reflects this by remaining parameter-agnostic.

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: 'Show the current MCP platform and adapter versions.' The verb 'show' plus the specific resource (version) makes the purpose immediately clear and distinct from sibling tools like authenticate or report_bug.

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 usage context is implied by the name and description—use this when you need version information. However, there is no explicit guidance on when to use this versus alternatives such as toolkit_info, and no exclusions or prerequisites are mentioned.

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 value by specifying the exact content returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the bare annotations. 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 one concise sentence, lists exactly what is returned, and contains no filler. All words earn their 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 simple information-gathering tool with no parameters and good annotations, this description is adequate. It lists the key elements without being verbose. However, it does not mention the format or pagination—though given there is no output schema, some might expect a hint. Yet given the simplicity, this is minimally viable 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?

The tool has zero parameters)Skip JSON. Schema coverage is 100% (since no params). Description needs no parameter explanation. The description clearly explains what it returns, which is the main semantic. Baseline for 0 params is 4 per guidelines.

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 current toolkit state, listing specific components (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb+resource (returns state) and clearly distinguishes from siblings like show_version (version info) 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?

The description implies a use case: inspecting the overall toolkit state. However, it does not explicitly contrast with sibling tools like show_version or connect, so the agent must infer when to invoke this vs alternatives. There is no explicit when-not guidance.

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