analyze_product_images

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

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior (pulls galleries, surveys coverage, returns counts and a plan) but doesn't mention potential side effects, rate limits, or data freshness. For a read-only analysis tool, this is acceptable but not rich. The description doesn't contradict any annotations since none exist.

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?

The description is two sentences with no fluff. It front-loads the core purpose, then lists outputs and the concrete plan. Every sentence earns its place, and the structure is easy to scan.

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?

The tool has 4 parameters, 0 required, and an output schema exists. The description covers the main use cases and outputs, but doesn't detail the output schema structure or edge cases (e.g., what happens if both asin and product_name are provided). Given the output schema exists, the description doesn't need to explain return values, but a note on parameter precedence would improve completeness.

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 0%, so the description must compensate. It explains the two key parameters (asin and product_name) and their roles, and implies the marketplace and max_listings parameters through context (Amazon India, search page). However, it doesn't explicitly describe marketplace or max_listings semantics, which is a minor gap given the 0% coverage.

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's purpose: analyzing product imagery on Amazon India. It specifies two distinct modes of operation (by ASIN or by product_name) and lists the concrete outputs (image counts, thin galleries, requirements, gallery plan). This distinguishes it from sibling tools like analyze_competition or scrape_amazon_product, which focus on different aspects.

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 explains when to use each mode: pass an ASIN for a single listing's gallery, or a product_name for a search-page survey. It doesn't explicitly state when NOT to use this tool or name alternatives, but the clear mode distinction provides adequate usage context. The absence of explicit exclusions is a minor gap.

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