Vínculo Empregatício

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

Annotations declare idempotentHint=true, and the description is consistent, showing that calling with the same token is idempotent. The description adds behavioral context beyond the annotations: it explains that calling with no args returns a link, with a token establishes a session, and mentions the permanent config option. This is valuable context not present in 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 a single multi-part sentence with a recommendation ('Best:') and usage instructions. It contains no fluff and is front-loaded with the core purpose, but it is somewhat dense and could be better structured into separate sentences for readability.

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 explains the authentication flow and both call variants, and it mentions the return of a link in the no-args case. However, it does not explicitly state what the tool returns when a token is provided (e.g., success/failure), nor any error behavior. Given that no output schema exists, this is a notable 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?

The schema has one optional 'token' string with no description (0% coverage). The description compensates fully by explaining that the token is a JWT, how to pass it ({ token: '<jwt>' }), and that it is for session-only login, while permanent auth is via config. This adds significant meaning beyond the raw schema.

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: to authenticate for MCP.AI by either generating a login link (when called with no args) or accepting a JWT token for session-only login. It specifies the resource (MCP.AI for IDE agents) and uses a specific verb (authenticate, log in). It does not explicitly distinguish from sibling tools like 'connect', but the function 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 guidance on how to use the tool ('Best: add it to this server's config...' and 'Or paste it here...'), but it does not explicitly state when to use this tool vs. alternatives (e.g., 'connect'). The usage context is implied rather than contrasted with sibling tools.

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 false. The description goes further by specifying the exact response conditions: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing. This adds valuable behavioral detail beyond 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?

Two sentences, front-loaded with the primary action, and every sentence adds meaningful detail. No fluff or redundancy. The conditional structure is clear and efficient.

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?

As a simple, zero-parameter read-only tool with no output schema, the description fully explains the return values under all relevant conditions. It is complete for an agent to understand what to expect and how to interpret the response.

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, the schema provides full coverage trivially. The description inherently needs no parameter explanation. Baseline 4 applies because there is no parameter information to add, and the description correctly focuses on behavior rather than nonexistent 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 clearly states the tool returns connection status and URLs. It is distinct from siblings like authenticate, which presumably performs authentication. The verb 'Returns' plus the resource 'connection status and URLs' is specific and 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 when to use this tool: to check connection status and obtain URLs. It provides conditional behavior for all-connected versus missing-credentials cases, giving clear context. However, it does not explicitly name alternatives or state when not to use it, so it stops short of 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?

The description adds substantial behavioral context beyond annotations: invoke runs uninstalled tools without bloating the toolkit, returns connect/checkout links on auth/payment failures, and writes require owner/admin. It also notes the flagging of installed_in_toolkit vs installed_in_workspace, giving the agent a clear model of side effects. 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 but every sentence adds value, covering the main flow, edge cases, and the secondary prompt library feature. It is well-organized in a logical progression, though it could benefit from more structural formatting (e.g., bullets) but remains efficient for the tool's complexity.

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 23 parameters, no output schema, and many actions, the description is remarkably complete. It covers discovery, detailed profiles, invocation, permanence, auth, billing, permissions, and the prompt library. It provides the agent with enough context to select and invoke the correct action and parameters without needing additional external documentation.

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?

Even though schema description coverage is 0%, the description explains the key parameters implicitly: action (with its enumeration via flow steps), mcp_id/tool_id for describe/invoke, arguments for invoke, and prompt-related fields for the prompt library actions. However, parameters like limit, immediate, tier_slug, and cancel_reason are not explicitly described, but their names and defaults make them somewhat inferable.

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 is the official mcp.ai marketplace, combining a catalog of MCPs/tools with the ability to run them. It names specific actions like search, describe, invoke, and install, and distinguishes it from siblings by covering both MCP discovery and running, as well as 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 provides an explicit core flow (search → describe → invoke) and explicit guidance on when to use invoke vs install, including the note that invoke is for one-off use while install is for permanent toolkit additions. It also advises on auth/billing link retries and mentions owner/admin permission requirements for writes.

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 indicate this is non-read-only, idempotent, non-destructive. The description adds the practical requirement to include the conversation array for reproduction. It does not disclose any other side effects or expected behavior, but the annotations cover the safety profile.

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 clauses in one sentence. The purpose is front-loaded and the instruction about conversation adds real value without waste.

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 3-parameter tool, the description covers the core purpose and one key parameter, but omits the meaning of `message` and `context`. Since there is no output schema, the description could clarify expected results. It is adequate 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 coverage is 0%, so the description must explain parameters. It only addresses `conversation` ('Include the conversation array') but leaves `message` and `context` unexplained. Also, it calls conversation an 'array' while the schema types it as a string, adding confusion.

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: 'Report a bug, missing feature, or send feedback' – a specific verb plus resources. It stands apart from all sibling tools which are for auth, marketplace, etc., eliminating ambiguity.

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 unambiguous context for when to use: when the user needs to report a bug/feedback. No alternatives are mentioned, but none of the siblings are relevant alternatives. It doesn't explicitly state exclusions, so 4 rather than 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds no extra behavioral traits (e.g., connection requirements, output format) beyond what the annotations provide, which is acceptable for such a trivial read-only tool.

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 directly states the tool's function. Every word earns its place, with 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?

For a simple, no-argument, read-only version tool, the description is complete. It conveys what the tool returns (platform and adapter versions) and needs no additional context. The absence of an output schema is not a gap here because the return value is self-explanatory.

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 description coverage is trivially 100%. The baseline for a zero-parameter tool is 4, and the description appropriately says nothing about parameters since there are none to explain.

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 'Show' and names the exact resource ('current MCP platform and adapter versions'). It clearly distinguishes from sibling tools like authenticate, connect, or report_bug, none of which deal with 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?

The usage context is obvious: it is the go-to tool for checking version info. While it doesn't explicitly mention when not to use it or name alternatives, the clear purpose and lack of similar tools make the intended usage evident.

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 behavioral context beyond annotations by detailing exactly what state is reported (MCPs, statuses, accounts, tool counts), which is useful for an agent.

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 lists all key details without wasted words. Every phrase 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 simple, no-parameter informational tool with strong annotations, the description is complete. It specifies what is returned and covers the tool's scope. No output schema exists, but the description adequately conveys the tool's function for an 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?

The tool has zero parameters, so the schema fully covers parameter semantics (vacuously). The description adds context about the returned information, but no parameter explanations are needed. Baseline for 0 params is 4.

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's purpose: returning the current toolkit state. It enumerates specific components (installed MCPs, connection status, accounts, catalog tool counts), which distinguishes it from sibling action tools like authenticate and 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 implies the tool is for checking state, and its read-only nature is clear from context. It does not explicitly state when to use it over alternatives or list exclusions, but the context is sufficiently clear for an informational 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?

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses payment requirements, credential-free access, public data status, and LGPD compliance responsibilities. These are significant behavioral traits that help the agent understand cost, legal obligations, and data sensitivity.

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, each conveying necessary information: purpose, hosting/payment, and data privacy/legal context. There is no redundancy or fluff, and it front-loads the primary 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?

The description captures the key functional and contextual aspects (purpose, access, cost, legal framing) for a simple 2-parameter read-only query. However, it doesn't describe the output format or the behavior of the 'completo' parameter, which would further improve completeness for an 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?

The schema has zero description coverage for parameters, and the description only references CNPJ as the query key without explaining its format or the meaning of the 'completo' boolean. Since coverage is 0%, the description should compensate but doesn't, leaving parameters under-specified.

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 verb 'Consulta' (queries) with a specific resource 'vínculos empregatícios associados a uma empresa' and identifies the key input 'CNPJ.' This clearly distinguishes it from the generic sibling tools (authenticate, connect, marketplace, etc.) by stating exactly what data it retrieves.

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 use: it queries public employment data from a CNPJ, requires no credentials, and involves prepaid credits. However, it doesn't explicitly mention when not to use it or name alternative tools, but the sibling list contains no similar data-query tools, so the guidance is implicitly clear.

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