Scrape Etsy listings (price, seller, reviews). Use for handmade-marketplace research.
Example call: {"listing_or_query": "handmade+ceramic+mug"}
Cost: $0.005–$0.05 USDC on Base per call.
| Name | Required | Description | Default |
|---|---|---|---|
| listing_or_query | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions the cost range ($0.005–$0.05 USDC per call), which is a behavioral trait, but does not disclose whether the tool is read-only, requires authentication, has rate limits, or any side effects. This is insufficient for a scraping tool.
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 concise with two sentences plus an example and cost. It is front-loaded with the purpose. No fluff, but it achieves only moderate completeness in a few words.
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?
Given the lack of output schema and annotations, the description should explain the return format. It mentions scraped fields (price, seller, reviews) but not the structure. It also omits important details like pagination, rate limits, or legal considerations. Overall, it leaves significant gaps for effective use.
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?
The single parameter 'listing_or_query' has no schema description (0% coverage). The description provides an example value ('handmade+ceramic+mug'), hinting it can be a search query, but does not clarify if it accepts URLs or listing IDs. This leaves ambiguity in how to format the input.
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 it scrapes Etsy listings for price, seller, and reviews, and specifies the use case (handmade-marketplace research). This is specific and actionable, though it could more explicitly differentiate from the many other scrape_* sibling tools.
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 provides a use case ('handmade-marketplace research') which implies an appropriate context, but lacks explicit guidance on when to use this tool versus alternatives like scrape_amazon or other marketplaces. No when-not-to-use information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.