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

Annotations cover the safety profile (not read-only, not destructive, not idempotent), and the description adds genuinely new context: it consumes 'one generation from the monthly quota,' which explains the cost of repeat calls. No auth or failure behavior is described, but the quota disclosure is meaningful added value.

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 short sentences with zero waste: when-to-use is front-loaded, followed by returns and the quota cost. Every sentence earns its place.

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?

Output schema exists, so the return enumeration is a helpful bonus rather than a necessity. The quota note covers the main behavioral risk for a non-idempotent generation tool; only auth/prerequisite details are absent, which is a minor gap.

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 only two parameters, both fully documented in the schema (category with example, product_name with length constraints). The description adds no parameter guidance beyond what the schema already provides, so the baseline 3 applies.

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 ('generate') and resource ('SEO-optimized Etsy listing') and clarifies the input is a product idea. It distinguishes itself reasonably well from analyze/optimize siblings by framing the tool as creating a listing from scratch, though it never names those siblings explicitly.

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?

"Use this when the user wants a complete SEO-optimized Etsy listing from a product idea" gives a clear triggering condition, and the 'complete' framing implies it is not for partial edits. No explicit exclusions or named alternatives (optimize_listing, suggest_keywords) are provided, so the agent must infer boundaries.

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