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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds useful behavioral context: it 'without publishing,' 'Returns generated content variants for each target platform,' and 'Respects brand voice profiles if configured.' This goes beyond the annotations, though it does not mention fallback behavior (e.g., strictAi), which is a minor 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 four sentences long, with the main purpose front-loaded in the first sentence. Each sentence adds a distinct piece of information (what it does, inputs, brand voice, outputs/alternatives), and there is no redundant or filler language.

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?

For a complex tool with 7 parameters and no output schema, the description provides essential return-value context ('Returns generated content variants for each target platform') and workflow guidance (publishing alternatives). It does not delve into fallback templates or strictAi behavior, but those are covered in the schema. Overall, it is adequately complete for the tool's complexity.

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 100%, so the baseline is 3. The description adds relational meaning by explaining 'from a prompt or media URL' (tying to prompt and mediaUrl parameters) and 'target platforms' (platforms). This clarifies how the inputs relate, which is more than just repeating schema descriptions, so a 4 is warranted.

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 'Generate AI-powered platform-optimized content without publishing,' which specifies the verb, resource, and scope. It distinguishes from sibling tools by explicitly stating that it does not publish and by naming publish_content and publish_ai as alternatives for publishing, while its focus on 'text, hashtags, and titles' differentiates it from generate_ai_media.

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 last sentence gives explicit guidance: 'Use publish_content to publish the generated content, or publish_ai to generate and publish in one step.' This directly tells the agent when to use this tool (generation-only) versus alternatives. The opening 'without publishing' also reinforces the appropriate context.

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