ai-furniture-hub

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

With no annotations provided, the description carries full burden. It discloses key behaviors: returns affiliate URLs (not product data), automatically selects SearchIndex from category, and expects URL presentation to user. However, it doesn't mention rate limits, authentication needs, or what happens with invalid parameters. It provides useful context but lacks comprehensive behavioral disclosure.

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?

Two concise sentences with zero waste. First sentence establishes when to use, second explains what it does and key behavioral details. Every word earns its place with no redundancy.

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?

For a search/URL generation tool with no annotations and no output schema, the description provides good context about when to use, what it returns, and how to handle the output. It could be more complete by mentioning error cases or response format, but covers the essential usage scenario adequately given the 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%, so parameters are well-documented in the schema. The description adds minimal parameter semantics beyond the schema - it mentions SearchIndex is automatically selected from category (not a parameter) and implies intent should reflect Amazon purchasing context. Baseline 3 is appropriate since the schema does the heavy lifting.

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: generating affiliate URLs for Amazon search results pages specifically for furniture/storage products. It distinguishes from siblings by mentioning 'Amazon' (vs Rakuten in search_rakuten_products) and specifying it returns URLs rather than product data (vs search_products which presumably returns data).

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 user wants to buy on Amazon or can't find on Rakuten') and provides clear alternative context. Also specifies the expected output action ('present affiliate_url to user'), giving concrete usage instructions.

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