Óbito

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

The description adds context about permanent vs session-only login and the behavior of calling with or without a token, which goes beyond the annotations. It does not contradict the idempotentHint and provides useful behavioral details.

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 covers all necessary information, though it is slightly verbose and mixes config advice with API usage. It is still concise enough and front-loaded with the main purpose.

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 optional-parameter tool, the description covers the main call patterns and provides sufficient context. It does not describe output or error cases, but given the low complexity and lack of output schema, it is adequately 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?

Since schema description coverage is 0%, the description fully compensates by explaining the token parameter as a JWT and when to include it. It clearly states that calling with no args is valid, making the optional nature of the parameter 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 states that the tool authenticates to MCP.AI for IDE agents and explains the login and token retrieval process. It is specific about the resource and action, but 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?

The description provides clear instructions for both permanent (config header) and session-only (token argument) authentication, and explains calling with no arguments to get a link. It does not explicitly mention when not to use it or alternatives, but the context is 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 declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds value by detailing conditional responses (authenticated:true + empty pending[] vs connect_url for toolkit/per-install), which goes beyond the annotations. This is useful context without contradiction.

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 purpose, and includes only essential conditional details. No redundant or irrelevant 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?

For a simple no-parameter status tool, the description covers the two main states (all connected vs missing credentials). However, it does not specify behavior when only some providers are connected, which is a minor gap but not critical given 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 tool has zero parameters, and the schema covers 100% trivially. According to the rubric, a baseline of 4 applies for 0 params, and no additional parameter explanation 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?

The description explicitly states the tool 'Returns connection status and URLs,' which is a specific verb+resource combination. It distinguishes itself from siblings like 'authenticate' by focusing on status/URLs rather than performing authentication.

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 clearly implies use when checking connection status or retrieving connection URLs. However, it does not explicitly mention when not to use it or compare with alternatives like 'authenticate', so it lacks exclusions but provides clear context.

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?

Beyond the annotations, the description discloses key runtime behaviors: invoke runs the MCP one-off without installing it and 'without bloating the tool list', returns a connect link when credentials are needed, and returns a checkout/top-up link if paid and wallet is empty. It also reveals that writes require owner/admin. Nothing contradicts the annotations (readOnlyHint=false, destructiveHint=false).

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, but the tool is genuinely complex with 14 actions and 23 parameters. It is well-organized with headings like 'Core flow', 'KEY', and 'It also carries...', and front-loads the primary search→describe→invoke usage. A few sentences are dense, but every sentence adds meaningful guidance.

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 and absence of an output schema, the description is exceptionally complete. It covers the full lifecycle (search, describe, invoke, permanent install), permission requirements, handling of missing credentials or wallet, and the entire prompt library subsystem. It addresses all major capabilities and exceptional flows.

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 compensates well by explaining the meaning of core parameters through the workflow (action, mcp_id, tool_id, arguments, prompt_slug, prompt_vars, etc.). However, it leaves several parameters underdescribed, such as limit, immediate, tier_slug, cancel_reason, conversation, prompt_body, and prompt_targets, so some semantics are still left to inference.

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 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', clearly stating the verb+resource. It goes on to define the core search→describe→invoke flow and differentiates itself from sibling tools by explaining its coverage of MCP discovery, execution, installation, billing, and the prompt library.

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 instructs when to use which action: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and contrasts invoke with list_tools ('list_tools lists what is callable right now'). It also provides the search→describe→invoke sequence and notes that writes require workspace owner/admin, plus covers the prompt library actions.

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, so the safety profile is clear. The description adds value by stating the data is public, not private or confidential, that the client is data controller under LGPD, and that there is a usage cost involved. This adds context beyond annotations, though it does not describe the response format or rate limits.

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 front-loaded with the main functionality, followed by relevant operational details. It does not include excessive fluff, though it could be tightened by removing some legal language, but overall it is appropriate in 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?

The description covers the core purpose, cost, data accessibility, and legal responsibilities, which is strong context. However, it does not specify the meaning of the 'completo' parameter or describe the expected return structure beyond 'indício de óbito.' Given the lack of an output schema, this leaves some ambiguity for the agent.

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 explain parameters. It clarifies that the CPF is the key input ('a partir do CPF'), but it does not explain the 'completo' boolean parameter. The description leaves this parameter entirely ambiguous, which is a significant gap given the low 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: 'Verifica indício de óbito de uma pessoa a partir do CPF, em bases oficiais.' This is a specific verb and resource, clearly distinguishing it from the sibling tools, which are platform utilities rather than data lookup tools. The purpose is 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 provides practical context: it is hosted by the platform, requires no credentials, and is pay-per-query with prepaid credit. This tells an agent when it is appropriate to use this tool (i.e., when CPF lookup is needed and the user has credit), but it does not explicitly exclude alternative approaches or mention any when-not-to-use conditions. Therefore, it offers clear usage context without explicit 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 provide the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds useful behavior context by instructing to 'Include the conversation array with recent messages for reproduction.' It does not describe side effects or delivery, but this is acceptable given annotation coverage.

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 concise sentences, front-loaded with the tool's purpose and a single practical instruction. Every sentence earns its place with no verbosity.

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 three-parameter tool with annotations and no output schema, the description covers the main purpose and gives key reproduction guidance. However, it leaves the context parameter unexplained and creates minor ambiguity by calling the conversation property an 'array' when the schema expects a string.

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 adds meaning to the conversation parameter ('recent messages for reproduction'), but does not explain the message or context parameters, nor clarify that conversation is a JSON string despite being called an 'array'.

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 sibling tools like authenticate, marketplace, or toolkit_info.

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 makes the primary use case explicit: reporting bugs, missing features, or feedback. It does not mention when not to use it or name alternative tools, but the context is unambiguous given the tool's name and siblings.

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, so the burden is lower. The description adds valuable context by specifying that it reports platform and adapter versions, going beyond the bare annotation 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?

A single, focused sentence communicates the tool's purpose without any filler. It is immediately understandable and appropriately sized.

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 extremely simple, with no parameters and annotations covering its safety profile. The description fully specifies what it reports, and the absence of an output schema does not hinder understanding for a version check 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?

With zero parameters and a schema that covers 100% of the (empty) property set, there is no parameter semantics to add. The baseline of 4 applies as the description cannot meaningfully compensate further.

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 the specific verb 'Show' and identifies the resource as 'current MCP platform and adapter versions.' It clearly distinguishes from sibling tools like authenticate or marketplace, making its purpose 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 implies the tool is for checking version information, providing clear context without explicit exclusions or alternative recommendations. Since siblings are unrelated, the usage context is sufficiently 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, matching the non-mutating 'Returns'. The description adds useful detail about the returned content (installed MCPs, statuses, accounts, catalog tool counts), providing value 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 a single well-structured sentence, front-loaded with the verb and object, and uses a clear list to enumerate the returned components. Every word earns its place, and there is no 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?

For a simple read-only tool with no parameters and no output schema, the description fully explains what the tool returns, listing each component of the toolkit state. It is self-contained and adequately comprehensive for an agent to understand the tool's function.

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 there is no parameter information for the description to add. Per the baseline rule for 0 parameters, a score of 4 is appropriate; the description doesn't need to compensate for any schema gaps.

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 specific resource ('current toolkit state') while enumerating the exact components returned: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly differentiates it from sibling tools like show_version 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 clearly establishes the use case: when you need to inspect the toolkit's current state. It doesn't explicitly mention exclusions or alternative tools, but the context is evident from the description, and no further guidance is necessary for this simple info tool.

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