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

Annotations already include idempotentHint=true and readOnlyHint=false. The description adds useful context about the two modes (permanent vs session-only) and the non-expiring nature of the config header, which goes beyond the raw annotation fields. It does not contradict any annotation.

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 moderately sized and front-loaded with the purpose. It could be slightly tightened, but each sentence contributes meaningful usage or behavioral detail, so it avoids 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 tool with one optional parameter and no output schema, the description covers both invocation patterns, the permanent vs session distinction, and how to obtain the link. It is complete enough for an agent to correctly use the tool without additional assumptions.

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 token parameter: it is a JWT to be pasted for session login, and omitting it means the agent should provide the login link. This gives clear semantic meaning to the single optional 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 this tool handles authentication for IDE agents: 'log in in the browser, copy the access token.' It distinguishes from sibling tools (connect, marketplace, etc.) by focusing on the auth flow and token setup.

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, actionable guidance: the best approach is adding a header to the server config for a permanent non-expiring connection, or pasting a token for session-only login. It also specifies that calling with no args returns the login link, so the agent knows exactly when to invoke each variant.

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 and destructiveHint=false, so the safety profile is known. The description adds valuable behavioral detail about conditional return values (authenticated:true vs connect_url), going 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?

The description is two sentences, front-loaded with the core action, and every sentence adds value by explaining both possible outcomes. No fluff or repetition.

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 simple read-only tool with no parameters and no output schema. The description fully explains the two possible return states, making it complete for an agent to understand expected results. Sibling context further helps disambiguation.

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, and the baseline for 0 params is 4 per the guidelines. The description does not need to explain parameters, and it instead clarifies the output semantics, 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 states 'Returns connection status and URLs' with a specific verb and resource, clearly distinguishing it from siblings like 'authenticate' which likely initiates a connection. It further clarifies the two outcomes, leaving no ambiguity about the tool's function.

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 the tool returns different states ('When all providers are connected... When credentials are missing...'), implying use for checking connection status. However, it does not explicitly name alternative tools or state when not to use this tool, so it falls 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 discloses key behavioral traits not covered by annotations: invoke works even when the MCP is not installed, returns a connect link if credentials are needed, and returns a checkout/top-up link if the wallet is empty (with a retry instruction). It also notes that writes require workspace owner/admin and that search/describe flag installation status. This is rich, valuable 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 dense and every sentence adds value, but it is a long single paragraph without visual structuring (bullets or breaks). It could be more scannable, but given the tool's multi-action complexity, the length is justified and information-dense.

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 breadth of this complex tool: the core flow, install vs invoke distinction, permission requirements, prompt library, and handling of credentials/payment. Despite no output schema, it explains what to expect (connect/checkout links, tool profiles). It is remarkably complete for a tool with 14 actions and 23 parameters.

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 for 23 parameters. It explains the action enum values and the core search/describe/invoke flow, mentioning tool_id and arguments implicitly, but it leaves many parameters (limit, query, immediate, tier_slug, conversation, prompt_* details) unexplained. It adds significant meaning for the primary actions but does not fully compensate for the coverage gap.

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 — the in-platform catalog of every MCP/tool and the way to run them. It lists specific capability requests it covers and outlines the core flow (search → describe → invoke), making the tool's purpose distinct 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 provides explicit when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT'. It also explains when to use subscribe/cancel, report_bug, and request_mcp, and differentiates prompt library actions. This goes beyond simple context into actionable decision support.

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 provide idempotentHint=true and destructiveHint=false, so the safety profile is already known. The description adds the useful tip to include conversation history for reproduction, but does not explain what happens after submission (e.g., confirmation, ticket creation) or any external side effects. It does not contradict 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, no filler. The key instructions are front-loaded and every phrase contributes to understanding the tool's purpose and usage.

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 no output schema, the description covers the core purpose and reproduction guidance. However, it omits parameter descriptions (especially 'context'), possible return/confirmation behavior, and any note about idempotency implications. 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 description coverage is 0%, so the description must compensate. It explains 'message' implicitly as the bug/feedback content and mentions the 'conversation array', but the schema defines conversation as a string (likely JSON-encoded). The 'context' parameter is entirely undocumented. The description adds some value but leaves gaps and introduces a minor type mismatch.

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 feedback. The verb 'report' plus specific resources (bug, feature, feedback) distinguishes it clearly from sibling tools like authenticate, connect, and marketplace.

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 clear context on when to use the tool (for reporting issues/feedback) and provides practical guidance ('Include the conversation array with recent messages for reproduction'). It does not explicitly mention alternatives or exclusions, but the sibling tools are unrelated, so this 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 and idempotentHint=true. The description adds the qualifier 'current', indicating that the tool reflects the runtime state of the platform and adapter. This provides useful context beyond simple 'show version' and is consistent with the non-destructive nature hinted by 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 sentence of 10 words that is front-loaded with the verb and object. It contains no filler, repetition, or unnecessary details, 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?

Given the tool's simplicity (no parameters, no output schema, comprehensive annotations), the description fully explains what the tool does. It is complete enough for an agent to select and invoke the tool correctly without ambiguity.

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 of 4 applies. There are no input semantics to clarify; the description appropriately avoids irrelevant parameter details.

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 'Show the current MCP platform and adapter versions' uses a specific verb ('Show') and clearly identifies the resource (versions). It distinguishes itself from siblings like 'authenticate' or 'marketplace' by focusing solely on version information, making the purpose unmistakable.

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 explicit guidance is given on when to use this tool versus alternatives, such as 'toolkit_info'. However, the purpose strongly implies usage whenever version information is needed. Since it lacks explicit when-not-to-use or alternative references, it only meets the 'implied usage' standard.

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 detail about the output contents but discloses no additional behavioral traits such as latency, errors, or permissions. This meets the baseline for annotation-covered tools.

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 efficiently packs five distinct data points (installed MCPs, connection status, accounts, tool counts) without wasted words. It is front-loaded with the action and resource.

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 parameterless, read-only introspection tool, the description is complete. It compensates for the absence of an output schema by listing exactly what will be returned. Annotations cover safety, so no critical information is missing.

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 zero parameters and schema description coverage is 100% (trivially), so the baseline is 4. The description correctly avoids adding parameter information that would be meaningless, providing no unnecessary noise.

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 identifies a clear resource ('current toolkit state'), then enumerates the exact contents (installed MCPs, connection status, connected accounts, catalog tool counts). This clearly distinguishes it from siblings like show_version or connect, which address different concerns.

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 about what information is returned, so an agent can infer when to call it (e.g., to check connection status or account bindings). It does not explicitly mention alternatives or exclusions, but that is not necessary for a simple state-getter 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 indicate read-only, idempotent, and non-destructive behavior. The description goes beyond annotations by disclosing the payment model ('pague por consulta'), the absence of credential requirements, and the legal/public nature of the data (LGPD note). These are meaningful behavioral traits not present in the structured metadata.

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 front-loaded with purpose. The second sentence covers hosting, credentials, and cost, while the third provides legal context. No obvious filler, though the LGPD clause could have been shortened without losing value.

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 lookup tool, the description explains what the tool does, the data source, and cost, while annotations cover safety. However, the parameter schema is not fully explained (especially 'completo'), and the CPF/CNPJ OR/AND conflict remains unresolved. There is no output schema, so the return value is also unspecified, leaving notable 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?

Schema descriptions cover 0% of parameters, so the description must compensate. It explains that CPF or CNPJ are used as query identifiers, but it says 'ou' while the schema requires both 'Cpf' and 'Cnpj'—a direct ambiguity. The optional 'completo' parameter is not mentioned at all, leaving its purpose unknown.

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 a specific verb ('Verifica') and a clear resource: checking whether an employer appears on the forced labor/slavery list using CPF or CNPJ. It distinguishes itself from the sibling tools (authenticate, connect, marketplace, etc.) by stating the exact domain and input identifiers.

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 useful operational context: it is hosted on the platform, requires no credentials, and is paid via prepaid credit. It also clarifies that the data is public and official, which helps the agent decide when this tool is appropriate. It does not explicitly name alternative tools or give when-not-to-use conditions, 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.