df_rule_list

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

No annotations are provided, so the description carries the behavioral disclosure burden. 'Listar' implies a read-only operation, and the description adds that the output includes activation state. However, it does not explicitly state side-effect-freedom, permission requirements, or pagination/response behavior.

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 compact sentence with no filler. It front-loads the action and resource, then adds the key detail about rule state, making every word informative.

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 list operation with no output schema, the description is largely sufficient: it tells the agent what will be returned (all configured rules with status). It could be more complete by describing the output shape or empty-result behavior, but the low complexity keeps the gap small.

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 there is nothing for the description to clarify beyond the schema, which already covers 100% of the parameter space. The baseline for a zero-parameter tool is 4, and the description provides appropriate context by stating the scope of what will be listed.

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 ('Listar') and a specific resource ('todas las reglas configuradas'), and it clarifies the returned data includes each rule's state. This clearly distinguishes df_rule_list from single-rule tools like df_rule_get and from mutating tools like df_rule_create or df_rule_delete.

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 states what the tool does but gives no explicit guidance on when to choose it over alternatives such as df_rule_get or df_rule_flow_list. There are no conditions, exclusions, or comparisons, so an agent must infer usage from the tool name and context.

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