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

No annotations are provided, so the description carries full behavioral disclosure burden. It does add valuable context that changes are scoped to one email and do not affect the rest of the flow, which is a meaningful safety guarantee. However, it omits details like reversibility, required permissions, error conditions, or side effects beyond the scoped fields, which are important for a mutation 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 two sentences long, front-loaded with the main action and scope. The second sentence provides a safety rationale without unnecessary detail. Every word contributes value, and the structure is clean 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?

While the description excels at purpose and scope, it leaves gaps typical for a mutation tool with no annotations or output schema: no return value description, parameter format details for blocks, or error handling expectations. For a 6-parameter tool, the description is above the minimum viable but still incomplete for an agent needing full invocation confidence.

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 schema description coverage at only 17%, the description compensates by explicitly naming all editable fields: subject, preheader, blocks, and label. This adds meaning beyond the bare property types. It does not explain the structure of blocks or the roles of flow_id and node_id, but these are inferable from the tool's purpose, so the compensation is solid but not complete.

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 'Edita' (edits) and identifies the resource as a specific email within an automation, listing the editable fields (subject, preheader, blocks, label). It also distinguishes itself from editing the entire flow by stating 'sin tocar el resto del flujo' (without touching the rest of the flow), which differentiates it from sibling update_flow.

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 usage context: use this to modify a single email without affecting the rest of the flow. It suggests an alternative ('reescribir el graph entero' – rewriting the entire graph) and positions this as safer, implicitly indicating when to prefer this tool over a broader update. However, it does not explicitly name the alternative tool or provide 'when not to use' conditions, 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.