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

Beyond the annotations (which only indicate non-read-only, non-idempotent), the description richly discloses behavior: submits a kie.ai job, polls, copies to R2, writes URL, costs credits, and that the job continues on timeout. It also gives actionable recovery steps. No contradiction with annotations.

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, front-loaded with the primary action. Every sentence adds value: purpose, workflow, cost/fallback. No redundant or filler content.

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?

Despite 8 parameters, the description provides a complete high-level picture, including cost, timeout behavior, and next steps. The presence of an output schema covers return values, so no gap there. Sibling tools give adequate context for alternatives.

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%, with each parameter already described. The description adds context for modelCode (from list_image_models) and mentions cost, but does not elaborate on parameter semantics beyond what the schema provides. Baseline 3 is appropriate.

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 explicitly states the tool's purpose: 'Generate an AI image and attach it as a post's featuredImage.' It details the full workflow (submit job, poll, copy to R2, write URL) and distinguishes itself from siblings like generate_image (which likely only generates) and attach_post_cover_from_job (which is called in the fallback scenario).

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 gives clear context: use this to generate a new cover and attach it, costing credits. It explicitly names an alternative for timeout recovery: 'call attach_post_cover_from_job(postId, jobId) once it finishes to attach without paying again.' However, it does not explicitly contrast with generate_image or upload_post_cover_from_url, leaving some ambiguity about when those should be used instead.

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