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

Annotations only declare the non-read-only, non-idempotent profile; the description goes well beyond by disclosing the async job model (returns job_id, poll check_job, ~1 minute latency), the billing situation ($0.00 on beta), and an operational constraint (rate-limited capacity). These are exactly the traits an agent needs before committing to a non-idempotent call.

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 dense sentences with zero filler: output mapping first, then use cases, then the async/billing/capacity caveats. Each sentence carries distinct information and the most decision-relevant facts are front-loaded.

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?

Although an output schema exists, the description still supplies the workflow detail an agent needs (job_id handoff to check_job, roughly one-minute wait), plus cost and rate-limit context. Nothing needed to invoke or sequence 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 description coverage is 100%, so both parameters are already documented in the schema and the baseline is 3. The description adds nothing about the aspect parameter (ratios, defaults) or prompt-authoring hints beyond what the schema already says.

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 a precise input→output mapping ("Text prompt → a generated image") and names the concrete artifact (a hosted URL embeddable in Markdown, HTML, or chat). That distinguishes it cleanly from the sibling generators (make_chart, make_qr, render_diagram, make_badge), which produce deterministic artifacts from structured input rather than free-text generation.

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?

It gives concrete use cases (illustrations, covers, concept art, social cards, mockups) that tell an agent when this tool fits. It also explicitly routes the agent to the follow-up tool ("poll check_job") with timing, though it never states when to prefer a sibling generator over this one.

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