run_validation

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

Since there are no annotations, the description must carry the full burden of behavioral transparency. It merely lists arguments and scope without detailing error handling, execution state, or potential failure modes (e.g., what happens if no rules match a symptom).

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, beginning with a clear purpose statement followed by a detailed argument list. It uses concise language without being overly simplistic.

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?

Although the input parameters are explained, the description is incomplete for a complex execution tool. Without output schema or comparative guidance, it is impossible for an agent to confidently decide if `run_validation` is the correct next step compared to other 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?

Given that schema description coverage is 0%, the description effectively adds value by explaining the meaning of each parameter—for instance, clarifying that 'symptom' is a 'user-reported problem' and 'area' specifies the domain like 'crm'.

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 two modes of operation: running a specific rule via ID, or finding rules based on a symptom. This provides a good functional definition of the tool's 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 lists what the tool can do (run or find) but offers no guidance on when to use it versus alternatives like 'plan_system_validation' or 'search_knowledge'. It fails to explain the intended operational workflow.

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