run_asset_ai

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

No annotations are provided, leaving the description to carry the transparency burden. It discloses that the action is AI-enabled and lists example tasks, but it fails to mention side effects (e.g., async processing, cost, or asset modification), authentication needs, or irreversibility. For a mutation-like 'invoke' action, this is a significant gap.

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, front-loaded sentence with no redundant filler. Every phrase contributes meaning, and the parenthetical examples aid comprehension without bloating the text.

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?

Given no output schema and no annotations, the description omits critical behavioral details like return value or job semantics. It adequately explains the core purpose but leaves questions about what happens after invocation. For a two-parameter action tool, this is a moderate gap.

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 description adds semantic value beyond the schema: 'on an asset' clarifies the vague 'ID of the resource' for the id parameter, and 'custom meta field action' maps directly to custom_meta_field_id. With only 50% schema coverage, this compensation is useful and helps disambiguate both parameters.

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 provides a specific verb ('Invoke') and resource ('asset'), coupled with a clear scope ('AI-enabled custom meta field action'). It includes concrete examples ('LLM-driven extraction, classification, or description') that distinguish it from sibling tools like auto_tag_asset or generate_asset_alt_text.

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 implies a usage context (triggering a custom AI action on an asset) but does not explicitly state when to use this versus sibling AI tools, nor does it mention any prerequisites or exclusions. This is acceptable but not fully explicit.

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