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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral detail by enumerating the 5 factors and specifying the return payload (overall score, per-factor breakdown, improvement suggestions).

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?

Three sentences: an opening purpose statement, a bullet-style list of the 5 factors, and a return-value sentence. Every line adds value and is front-loaded with the most important information.

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?

The tool is moderately complex (5 params, no output schema), but the description covers evaluation logic and expected output behavior. It does not detail edge cases or exact response formatting, but that is acceptable given the schema and read-only annotations.

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?

All 5 parameters have schema descriptions, so baseline is 3. The description enhances semantics by linking 'scheduledTime' to the time alignment factor and 'mediaUrl/mediaUrls' to media presence, helping the agent understand how inputs are used.

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 opens with 'Score content quality on a 0-100 scale before publishing,' which is a specific verb, resource, and outcome. It lists five concrete evaluation factors and clearly distinguishes itself from content generation (generate_content) and publishing tools by emphasizing pre-publish scoring.

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 phrase 'before publishing' provides clear context for when to invoke the tool. It does not explicitly name alternative tools like critique_post or validate_content, but the 5-factor scoring approach implies a quality-assessment use case distinct from other content operations.

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