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

With no annotations, the description carries the full burden. It explains the process (vetted human expert), the types of errors checked (hallucinations, factual errors, weak parts, domain mistakes), and expected outputs (verdict, issues, improvements, certificate). It does not cover costs, rate limits, or turnaround time, but for a human-review tool, it provides sufficient behavioral insight.

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 three sentences, all front-loaded with the most critical information: what the tool does, when to use it, and what it returns. Every sentence serves a purpose, no filler.

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 the tool's moderate complexity (handles multiple media types, includes certification), and the presence of an output schema, the description covers the essential aspects: purpose, input format, use cases, and outcomes. It lacks details like turnaround time or how the certificate works, but the output schema likely fills those gaps.

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 coverage is 100%, so the schema already documents both parameters. The description adds value by clarifying that 'content' can be direct text or a URL for non-text media, which goes beyond the schema's description. This extra guidance justifies a score above the baseline of 3.

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 specifies a clear verb ('Get a human expert to review'), defines the resource ('AI-generated content'), and details the scope ('text, images, videos, social posts, audio, or any media'). It distinguishes from siblings like 'ask_a_human' or 'consult_domain_expert' by focusing on content review before publishing.

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 provides explicit guidance on when to call: 'before publishing, before forwarding to another agent, or before acting on the content.' While it gives clear context for use, it does not explicitly mention alternatives or when not to use this tool, leaving a minor gap.

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