openai_moderate_content

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

No annotations are provided, so the description carries the full behavioral burden and does very little with it. It does not say whether the operation is read-only, what happens with the empty-string defaults, how input_text and input_json relate, or what constraints apply to supported image inputs.

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 single sentence is front-loaded and contains no filler. It is efficient, though its brevity contributes to gaps elsewhere rather than being a structural flaw in itself.

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?

An output schema exists, so return values need not be described. However, with three parameters at 0% schema coverage, no annotations, no required parameters, and empty-string defaults that are likely to fail, the definition is too thin for correct invocation.

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?

Schema description coverage is 0%, so the description must compensate for three undocumented parameters. It hints that text or image inputs are supported, but does not explain 'model', 'input_json', or 'input_text', nor does it clarify their formats or mutual exclusivity.

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, 'Classify', with a named resource, 'text or supported image inputs', and identifies the Moderations API. It clearly differs from sibling tools such as chat completions, image generation, or embeddings, though it does not explicitly contrast itself with them.

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?

It implies the tool is used for moderation-style classification but gives no explicit when-to-use guidance, no exclusions, and no alternatives. An agent is left to infer that this is the right tool for content moderation rather than being told.

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