df_rule_get

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 disclosing behavior. 'Ver' indicates a read operation with no mutation implied, which is a useful signal, but it does not mention error cases, required permissions, or what the returned detail contains. The transparency is adequate for a simple get 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?

The description is a single, focused sentence with no filler or redundant content. It front-loads the tool's purpose clearly and is appropriately sized for a simple get operation.

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 one-parameter read tool, the description is minimally viable: it states the action and resource, and the schema covers the parameter. However, with no output schema and no annotations, the description leaves ambiguity about the exact structure of the returned rule details and how this differs from list behavior.

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 already fully describes the single required parameter 'name' as 'Nombre de la regla', with 100% coverage. The description adds no extra meaning about the parameter, so it does not go beyond the baseline set by the input 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 action and resource: viewing the complete details of a rule. It is specific enough to convey the core purpose, but it does not explicitly contrast with sibling tools such as df_rule_list, which likely lists rules rather than fetching one rule's full detail.

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 no guidance on when to use this tool versus alternatives like df_rule_list, df_rule_update, or df_rule_delete. There are no exclusions, prerequisites, or context hints, leaving the agent to infer usage from the name alone.

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