Validate Poietic design

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

No annotations are present, so the description bears the full burden. It discloses the return shape and issue fields, and implies a non-mutating validation behavior. It does not explicitly state that the design is not modified, but 'validate' plus the return report makes this reasonably clear.

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?

Two dense, purposeful sentences cover the operation, the exact return structure, and the workflow position. No redundant wording or repetition of the tool name.

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?

With a single optional parameter, no output schema, and no annotations, the description supplies everything an agent needs: what is validated, what the result looks like, and when to invoke it. This is sufficient for a low-complexity read-only validation tool.

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 only parameter is fully documented in the schema with its path meaning and default resolution behavior. Schema coverage is 100%, so the description does not need to add parameter details; the baseline of 3 applies.

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 validates a design for errors, specifically formula errors and unknown parameters. This distinguishes it from sibling tools like poietic_run or poietic_get_design, which serve different purposes.

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?

Explicitly tells the agent when to run this tool: after editing and before simulating. It does not explicitly mention alternatives or exclusions, but the timing guidance is clear and actionable.

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