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

Adds substantial behavior beyond the annotations (which only declare non-read-only, open-world, non-idempotent, non-destructive): product photos come from the user's catalogue or the web, scheduling reserves the date and creates an idea review card, approval is required before publishing, and it returns a task ID and group ID immediately with the explicit instruction not to claim it is already scheduled. This is exactly the context an agent needs to set expectations.

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?

Front-loaded with the core purpose, then flows through product detection, scheduling/approval, platform targeting, and return semantics. It is dense and long, but nearly every sentence carries actionable instruction; only minor tightening would be possible.

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 an 11-parameter mutation tool with no output schema, the description covers the key gaps: that it returns a task ID and group ID, that approval is required, that the user is notified when ready, and where to check progress. Nothing an agent needs to invoke and report on this tool correctly is missing.

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 baseline is 3, but the description maps natural user phrasing onto parameters ('only TikTok', 'LinkedIn and Instagram', 'everywhere' -> platforms; 'a post about A and B' -> productIds in one call) rather than merely restating schema text. That mapping adds real selection value on top of the schema.

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?

States a specific verb and resource ('Generate new social media posts using AI'), and the body clarifies the scope (auto product detection, scheduling, platform targeting). It does not, however, name the siblings it is distinct from (e.g. generate_from_product, create_post_from_image, generate_from_news), so an agent must infer routing.

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?

Gives concrete conditional guidance: pass scheduledDate/scheduledTime only when a date is explicitly requested, pass platforms when the user names networks, pass instagramPlacement 'story' for a story, and 'Check get_generation_status if they ask for progress' names an alternative. It stops short of stating when this tool should be avoided in favor of image/video-specific siblings.

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