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

No annotations were provided, so the description carries the full burden of disclosing behavior. It explains this is a read-only network operation, provides the exact code format, and notes case-insensitivity. It could be more explicit about what happens when a ticket is not found or network errors occur, but for a read-only lookup tool, this is quite thorough.

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 well-structured with a clear summary, context, and use cases. It avoids unnecessary fluff and uses whitespace effectively. Every section adds value, from the primary description to the code format details and case-insensitivity note.

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 query tool with one parameter, the description covers the essentials: what it does, how to invoke the parameter, and format validation rules. It's accessed via read-only operation, has no nested objects, and has an output schema. Could add network/rate-limit caveats, but those are typically beyond the scope of a tool description.

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 coverage and a single L2 parameter 'codigo', the description does the heavy lifting by defining the format: 'TCK-0000' with the number portion being any number. While the description could add regex or validation rules, it provides the key semantic information: the acceptance criteria for the code format and that it's case-insensitive. However, it doesn't explicitly state what the tool is FOR (to fetch a ticket by its id), which is implied by the tool name 'consultar_ticket.'

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+resource combination ('Consulta los datos de un ticket específico') and clearly defines what it does. It distinguishes itself from siblings by focusing exclusively on single-ticket queries, while 'listar_estados_de_ticket' implies a different purpose. The code format and use cases further clarify the tool's intended 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 explicitly states a primary use case ('El agente pregunta por un ticket con su código') and clarifies it's read-only ('Únicamente lee información de un ticket, no modifica nada'). It also explains that it hits the network ('Toca la red'), implying it may have performance implications. However, it doesn't explicitly mention when NOT to use it or name alternative 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?

The description states that the tool is purely informational ('No toca la red, es una tool únicamente informativa') and does not return specific ticket data. Since no annotations are provided, this disclosure is valuable because it explicitly tells the agent that this tool has no side effects and is safe to call. It also clarifies the scope of the return (list of valid states, not ticket-specific data), adding context 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 concise, with two short paragraphs and a bulleted list of use cases. Every sentence adds value: the first clarifies the scope, the second lists use cases. However, the use cases could be seen as slightly repetitive (the second and third are similar), but overall it is efficient 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 is a simple zero-parameter informational tool, the description is complete. It explains what the tool returns, that it is non-network and informational, and provides usage examples. The output schema exists (context signal), so return value specifics are presumably covered there. The description provides sufficient context for an agent to invoke this tool appropriately, distinguishing it from the sibling tools.

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 description's role is to explain the output, which it does (lists possible states and explanations). The schema has no properties, so there is no parameter information to add. With 0 parameters, baseline is 4, and the description adequately compensates by explaining what the tool returns and its informational nature.

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 what the tool does: it lists the possible ticket states and their explanations. It is distinguished from siblings by explicitly stating it is informational only and does not return data for a specific ticket, which contrasts with consultar_ticket. The verb 'Lista' specifies the action and resource (estados de ticket).

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 cases: when the agent asks about existing states, when the agent doesn't understand a ticket state, and when the agent needs an explanation of why it cannot touch a ticket. It also explicitly states when NOT to use it: it does not return data for a specific ticket. This clearly differentiates from consultar_ticket, which would be the alternative for specific ticket data.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic function of checking server aliveness, without mentioning potential side effects, whether it's a read-only operation, response behavior, or error handling. For a simple health check, more detail (e.g., that it makes no changes, what it returns) would be expected.

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 with no extraneous information. It is entirely front-loaded 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?

Given the tool's simplicity and the presence of an output schema, the description is largely complete for a health-check tool. However, it lacks optional details like common failure modes (server down, timeouts) or typical use cases beyond 'is it alive', which leaves some ambiguity for the agent about handling results. Still, for a basic ping, it is adequate.

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 reflects this (100% coverage). The baseline for 0 parameters is 4, and there is no parameter information to elaborate on. The description correctly adds nothing about parameters, 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 clearly states the tool's purpose: to verify the Nimbus MCP server is alive. It uses a specific verb ('Verifica') and resource ('servidor MCP de Nimbus'). This is distinct from sibling tools (list and consult tickets), which are about ticket operations.

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 (as a health check for the server) but does not explicitly mention alternatives or scenarios where it should not be used. Given the sibling tools are unrelated, the context is clear, but there is no explicit guidance on usage.

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