Similaridade de Identidade (Argentina)

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

Annotations already indicate idempotent and non-read-only behavior. The description adds beyond this by explaining that the token provides session-only login, the config header gives a permanent non-expiring connection, and calling with no args returns a link. This adds useful behavioral context not present in 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 three sentences covering purpose, permanent configuration method, and session token method. While the phrasing is slightly informal (e.g., 'Best:'), each sentence provides necessary information with no fluff. It is appropriately sized, though a bit loosely 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 simple one-parameter tool with no output schema, the description covers the full workflow: how to authenticate, both permanent and session modes, and the behavior of calling with no args. It lacks explicit success/error response details, but the description is sufficient for 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 schema only lists an optional string 'token' with no description (0% coverage). The description fully compensates by explaining that the token is a JWT to be pasted for session-only login, and that omitting it triggers link generation. This adds complete semantic meaning to the 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: authenticate MCP.AI for IDE agents by logging in and copying an access token. It distinguishes itself from siblings like 'connect' by focusing on the authentication flow and token configuration. The verb 'log in' and resource (MCP.AI) are specific, making the intent 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?

The description provides explicit usage guidance: best to add the token as an Authorization header for permanent connection, or pass the token as a parameter for session-only login, or call with no args to get the link. It does not explicitly mention when not to use or compare with 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 indicate readOnlyHint, idempotentHint, and destructiveHint false. The description adds value by explaining the exact response states: authenticated:true with empty pending[] when all connected, and connect_url plus per-install URLs when credentials are missing. This provides behavioral transparency beyond the schema.

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 main purpose, and every sentence adds meaningful detail about return values. There is no redundancy or 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?

The description covers the two main states (all connected, missing credentials) but does not specify partial connectivity or error cases. Given the tool's simplicity and zero parameters, this is mostly complete, but a slight gap remains for mixed states.

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 is empty. The description does not need to explain parameters. The baseline for zero parameters is 4, and the description correctly omits parameter details since there are none.

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: 'Returns connection status and URLs.' It distinguishes itself from sibling tools like 'authenticate' by focusing on status and URLs rather than initiating authentication. The conditional behavior for all connected vs. missing credentials adds specificity.

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 on when to use the tool: to check if all providers are connected or to get connection URLs when credentials are missing. It does not explicitly mention alternatives or exclusions, but the conditions imply the use case clearly.

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 annotations, the description discloses key behaviors: invoke works even when the MCP is not installed, returns connect links for credentials and checkout links for payment, requires workspace owner/admin for writes, and flags installed_in_toolkit vs installed_in_workspace. These details go far beyond the basic readOnly/destructive 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?

The description is long but front-loaded with the core purpose and flow. While it is dense and covers a lot, each sentence adds meaningful information about actions or behaviors; no significant redundancy. The structure is a single large paragraph, which could be improved with bullets, but it 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?

The description covers the main flows (search/describe/invoke, install vs invoke, prompt library), auth requirements, billing links, and permissions. It omits details on some actions like 'resume' and parameters like 'immediate' or 'tier_slug', but the core decision-making context is adequately provided for an agent to use the 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 23 parameters and 0% schema coverage, the description compensates by explaining the action enum values, the relationship between mcp_id and tool_id, and the prompt_vars for get_prompt. However, it leaves many parameters (limit, query, tier_slug, cancel_reason, etc.) undocumented, relying on inference from the action 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 identifies the tool as the official mcp.ai marketplace, serving as both a catalog and runtime for MCPs. It enumerates specific functions (search, describe, invoke, install, prompt library) and differentiates itself from sibling tools by being the only marketplace and prompt library among them.

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 explicit guidance on when to use which action: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', and 'request_mcp asks us to build a NEW MCP when nothing fits'. It also explains the flow from search to describe to invoke, making it clear how to navigate the 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 readOnlyHint=false, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds that the conversation array is needed for reproduction, which hints at how data is used. Beyond this, no additional behavioral traits are disclosed, but given the annotation coverage, the description is adequate but not rich.

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 compact sentences, no filler. The first sentence establishes purpose, the second provides a key usage instruction. Every word adds 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?

The tool has three parameters and no output schema, making it relatively simple. The description covers the primary purpose and one parameter's role, but lacks explanation for 'message' and 'context'. It is adequate for basic use but leaves gaps for proper parameter usage.

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 0% description coverage, so the description must compensate. It only mentions the conversation parameter ('conversation array with recent messages'), leaving 'message' and 'context' unexplained. Without details on what message should contain or how context is used, the parameter semantics are notably incomplete.

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 with the verb 'report' and specifies three distinct use cases: bug, missing feature, or feedback. It also includes an instruction about the conversation array, which adds specificity. However, it does not explicitly differentiate from sibling tools, though the siblings are unrelated so confusion is unlikely.

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 ('when you have a bug, missing feature, or feedback') and gives a usage hint ('include the conversation array'). It lacks explicit exclusions or alternative tool mentions, but the 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, so the description does not need to restate safety. The description adds useful context about the version scope (platform and adapter), but it does not disclose the return format or any other behavioral details beyond what annotations provide.

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 that is immediately clear and free of unnecessary words. It fully accomplishes its purpose without wasted content.

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 no-parameter version display tool with strong annotations, the description is sufficiently complete. It names exactly what versions are shown, and the absence of an output schema does not create a meaningful gap since the tool is simple and 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 input schema has zero parameters, and the baseline for zero-parameter tools is 4. The description appropriately adds no parameter-related information because there is nothing 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 identifies the exact resource ('current MCP platform and adapter versions'). This clearly distinguishes it from sibling tools like report_bug and authenticate, which serve 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?

No explicit guidance is provided about when to use this tool versus alternatives such as toolkit_info. The usage context is implied by the tool's name and description, but there is no direct statement of exclusions or preferred scenarios.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds valuable context: no credentials needed, prepaid per-query billing, public-access data (not private), and LGPD data-controller responsibility. It also states the return behavior (similarity score) with 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 three efficiently front-loaded sentences: core function first, then operational context, then legal framing. Every sentence adds information without redundancy, making it easy to scan.

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 has 10 parameters and no output schema or parameter descriptions; the description covers the main purpose and return type but omits key parameter semantics and optional flags. Annotations cover safety, but the description is not a complete guide for a complex consult 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?

The description names a few field categories (DNI, name, birth, address), but the schema has 10 parameters with no descriptions and 0% schema description coverage. It does not clarify the many required fields (e.g., City, State, PostCode, Phone) or the meaning of the 'completo' boolean, leaving the agent under-informed about parameter usage.

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 compares a person's provided data (DNI, name, birth, address) and returns a similarity degree against the registry. It uses a specific verb and resource, and is easily distinguished from sibling tools like authenticate, marketplace, 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 description gives clear context for use: hosted on the platform, no credentials required, pay-per-query with prepaid credit, and access to public data. It does not explicitly name alternatives or exclusions, but no sibling tool competes with this functionality, so the context is sufficient for 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the return content but does not disclose additional behavioral traits such as latency, caching, or potential variability in connection status accuracy. 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 a single, clear sentence that front-loads the purpose ('Returns the current toolkit state') and specifies the output components. Every word earns its place, with no redundancy or irrelevant 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 simple read-only tool with no parameters and a clear output description, the description is complete. It fully describes what is returned (installed MCPs, connection status, accounts, catalog tool counts), which is sufficient given the lack of output schema and low complexity. Annotations cover the safety context, so no additional information is necessary.

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 schema coverage is 100% (empty properties). Per the baseline for 0 params, a score of 4 is appropriate. The description doesn't need to explain parameters because there are none, and it adds no extra semantics that would warrant a 5.

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 the specific contents (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb+resource pairing that distinguishes it from sibling action-oriented 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 implies usage—call this to inspect toolkit state—but does not explicitly state when to use it versus alternatives or provide exclusion criteria. Sibling tools like authenticate or connect have different purposes, but no direct comparison or 'instead of' guidance is given.

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