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

The description adds meaningful behavioral context beyond annotations: it verifies job ownership and success, and explicitly states it does NOT charge credits because they were charged at submit time. This is useful safety/billing information not present in the annotations. Minor gap: it doesn't mention whether an existing featuredImage is overwritten, but otherwise transparent.

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 purpose in the first sentence, followed by use cases and key behavioral notes. Every sentence earns its place; no redundancy or fluff.

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?

With an output schema present and a fully self-describing input schema, the description covers the essential context: what it does, when to use it, the verification behavior, and the credit implication. It is complete for this 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% with all parameters documented (jobId, postId, assetIndex, pollIfRunning, pollTimeoutMs). The description adds only context that the job is 'ai-media job's output' and 'featuredImage', but doesn't provide additional meaning beyond the schema. 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 clearly states the tool attaches a previously generated ai-media job's output as the post's featuredImage. This specific verb+resource+field combination distinguishes it from related siblings like generate_post_cover, upload_post_cover_from_url, and attach_tags.

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?

Explicitly states when to use: when generate_post_cover timed out (job kept running) or when reusing the same generation across multiple posts. This provides clear context and names the alternative tool, fulfilling the when/when-not guidance.

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