Nível Socioeconômico e Renda Estimada

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

The description discloses that a config-header approach yields a non-expiring connection, while passing a token is session-only, and that no args returns a login link. This adds meaningful behavioral context beyond the annotations (idempotentHint, destructiveHint, readOnlyHint). No contradiction with annotations is present.

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 exceptionally concise, using three focused sentences to cover purpose, best practice, and alternative usage. Every sentence contributes actionable information and the structure is front-loaded with the tool's context.

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 tool with one optional parameter and no output schema, the description covers the core workflow, parameter semantics, and important behavioral nuances. It does not describe return values or error handling, but these are not essential given the tool's simplicity and the strength of the other information provided.

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 a string with no description. The description explains the token is a JWT, provides an example call format ({ token: '<jwt>' }), and clarifies that the parameter is optional since calling with no args yields a link. 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 states the tool authenticates an MCP.AI server for IDE agents via browser login and access token. It specifies the resource (MCP.AI) and the action (log in, copy/paste token), but does not explicitly differentiate from the sibling tool 'connect', so it doesn't fully earn a 5.

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 gives explicit guidance for two usage scenarios: adding the token to config for a permanent connection, or passing it as a parameter for a session-only login. It also notes calling with no args to get the link. However, it does not mention when to use this tool instead of siblings like 'connect', so it lacks explicit exclusions or 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context by describing the two conditional outcomes: when all providers are connected vs. when credentials are missing, including the specific return fields (authenticated:true, empty pending[], connect_url). This goes 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, front-loaded with the main purpose, and no wasted words. Every sentence provides meaningful behavioral detail.

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 with no parameters and no output schema, the description covers the essential return scenarios (all connected vs. missing credentials). It is sufficiently complete for an AI agent to understand what to expect without further details.

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 is empty with zero parameters. The description correctly adds no parameter information since none exist. Baseline for 0 parameters is 4, and the description does not 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 clearly states 'Returns connection status and URLs' with a specific verb and resource. It distinguishes from the sibling 'authenticate' by focusing on status retrieval rather than the authentication action itself.

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 context for when to use the tool (to check connection status and obtain URLs). However, it does not explicitly mention when not to use it or point to alternatives like 'authenticate', so it lacks 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?

The description adds rich behavior beyond annotations: invoke works even when the MCP is not installed, runs one-off without bloating the toolkit, returns connect/checkout links for auth/payment, and writes require owner/admin. It also details the prompt library's shareable link behavior. No contradiction with 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 a long, dense block of text that covers many scenarios but lacks clear sectioning or bullet points. It is informative but not concise, and the stream-of-consciousness structure could overwhelm an agent trying to parse key facts quickly.

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 23-parameter tool with no output schema, the description is remarkably complete: it covers core flows, edge cases (not installed, auth, payment), permissions, and the prompt library. Still, some sub-actions like 'resume', 'immediate', 'tier_slug', and detailed cancel/report inputs are not mentioned, so there are gaps.

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 must compensate. It explains the roles of action, tool_id, and arguments in the core flow, and high-level purpose of prompt-related params. However, many params such as limit, query, message, immediate, tier_slug, cancel_reason, and report_context are not explained, leaving the agent to guess their semantics.

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 mcp.ai marketplace catalog and runtime, and lays out the core flow: search → describe → invoke. It also distinguishes special sub-capabilities like the prompt library, so an agent knows what the tool does at a glance. However, it covers so many sub-features that the overall purpose is broad rather than a single verb+resource.

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?

Explicit guidance is abundant: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use', 'list_tools lists what is callable right now', and clear differentiation of the prompt library. It also explains when invoke returns a connect or checkout link and to retry after the user acts. This is exemplary when-to-use vs alternative 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?

Annotations already indicate readOnly and idempotent, and the description adds valuable behavioral context: no credentials required, pay-per-query with prepaid credit, consults credit bureaus and official bases, and mandates LGPD compliance with the client as controller. These details go beyond annotations and give the agent a full picture of costs, data sources, and legal obligations.

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 paragraph of four sentences, each providing distinct information: purpose, hosting/pricing, data sources, and legal compliance. It is structured with the purpose first, and while somewhat dense, every sentence adds value. A 4 is appropriate for its efficient yet informative structure.

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 two parameters and no output schema, the description covers the core functionality and constraints well, but it omits details about the 'completo' parameter and expected response format. The legal and payment context is thorough, yet parameter clarification and output expectations are missing, making it average completeness for this complexity level.

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 parameter documentation. It mentions CPF implicitly ('a partir do CPF') but does not explain the 'completo' boolean parameter or any parameter semantics. This leaves agents guessing about the optional parameter's purpose, which is a significant gap given the lack of schema descriptions.

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: 'Estimativa de nível socioeconômico e renda de uma pessoa física a partir do CPF' (estimate socioeconomic level and income from CPF). It specifies the input (CPF) and the computation basis (income, occupation, education), distinguishing it from generic sibling tools 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 on when to use the tool: it is a hosted, prepaid service that queries credit bureaus to estimate income, and requires a legal basis (e.g., risk analysis requested by the data subject). It does not explicitly mention alternatives or exclusions, but the sibling tools are unrelated, so the context is sufficient 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?

Annotations already convey that the tool is not read-only but is idempotent and non-destructive. The description adds a note about including conversation for reproduction, which is a behavioral requirement, but it does not disclose what happens after reporting (e.g., confirmation, ticket creation) or any rate limits. The bar is lowered by annotations, yet the description could provide more context.

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: a clear action clause followed by a specific instruction. Both sentences earn their place with no filler or repetition, making it easy for an agent to quickly understand the tool.

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 bug-report tool with 3 parameters and no output schema, the description covers the main intent and an important parameter. However, it omits the 'context' parameter's purpose and does not describe the expected outcome or response. Given the lack of an output schema, these gaps leave the agent without full guidance.

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 explains the 'conversation' parameter explicitly ('recent messages for reproduction') but leaves 'message' and 'context' largely implied. This partial compensation is insufficient to earn a higher score, especially since 'context' is entirely undocumented in both schema and description.

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 with a specific verb: 'Report a bug, missing feature, or send feedback.' This distinguishes it from sibling tools like 'connect' or 'show_version', leaving no ambiguity about 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 the obvious usage context (reporting issues/feedback) and provides a specific directive to include conversation messages for reproduction. However, it does not explicitly mention alternatives or exclusions, which would be expected for a 5.

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, covering the safety profile. The description adds the specific context that it shows MCP platform and adapter versions, but does not disclose additional behaviors like return format or error handling. Since annotations carry the main behavioral load, 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 concise sentence that immediately states the purpose. There is zero wasted verbiage, and the most critical information is front-loaded.

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 tool with no parameters and no output schema. The description fully captures the tool's purpose without needing to explain return values or additional behavior. Complete for its complexity.

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 per the rubric, the baseline is 4. The description does not need to explain parameters, and the schema already documents the empty parameter set.

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' with a clear resource ('current MCP platform and adapter versions'). It distinguishes itself from sibling tools like authenticate or marketplace, which have different purposes.

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 the tool (when version information is needed) but does not explicitly state when not to use it or compare with alternatives. No exclusions or conditions 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, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds value by explaining what data the tool returns (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. It doesn't mention rate limits or auth, but it's a simple read-only getter.

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 core purpose ('Returns the current toolkit state') and then lists the specific contents. Every word earns its place; no fluff 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?

Given the tool has no parameters, no output schema, and strong annotations, the description provides sufficient detail about what the tool returns. It covers the key information an agent needs to decide to call this tool and understand its output. No significant gaps.

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 baseline is 4. The description doesn't need to explain parameter semantics, and the schema is empty. No additional parameter context is required.

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 'the current toolkit state' and enumerates specific contents (installed MCPs, connection status, accounts, catalog tool counts). This uses a specific verb ('returns') and resource ('toolkit state'), distinguishing it from sibling tools like 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?

The description implies usage context: use this to inspect toolkit state. While it doesn't explicitly exclude alternatives or name when-not-to-use, the purpose is clear enough for an agent to select it over siblings. No explicit alternative guidance is provided, so a 4 is appropriate.

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