Estimate resale margin for buying an item at a given price and reselling at the current eBay market median. Accounts for marketplace fees and optional shipping cost. Returns estimated profit and ROI. Estimates only, not financial advice.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Product to evaluate | |
| fee_pct | No | Marketplace fee percent, default 13.25 | |
| buy_price | Yes | Your acquisition price in USD | |
| shipping_cost | No | Estimated outbound shipping USD, default 0 |
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?
With no annotations provided, the description carries the full transparency burden. It discloses that the output is an estimate, not financial advice, and that the calculation accounts for marketplace fees and optional shipping costs. It does not describe edge cases like missing market data, but the provided disclaimers add meaningful behavioral context.
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 three concise sentences: it states the core purpose, lists what the tool accounts for, summarizes the return values, and adds a disclaimer. No filler or redundant restatement of the tool name.
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 non-destructive estimation tool with fully described parameters and no output schema, the description gives enough context to call it correctly: required inputs are implied, optional inputs are mentioned, and the return content is summarized as profit and ROI. It lacks detail on output format or edge cases, but that is not critical for basic invocation.
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 the schema already documents all four parameters. The description adds a little semantic context by tying buy_price to the acquisition cost and fee_pct/shipping_cost to marketplace fees and shipping, but it does not need to carry the parameter documentation burden.
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 a specific verb and resource: estimate resale margin using buy price and the current eBay market median. It names what the tool computes (profit and ROI) and distinguishes it from a generic price check. However, it does not explicitly differentiate from sibling tools like price_check or scan_deals.
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?
Usage context is implied: the tool is for evaluating a flip opportunity at a given purchase price. It does not explicitly state when to use this tool over siblings, nor does it mention exclusions or prerequisites. The guidance is present but not made explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct role: hot_list provides a cached, curated list of pre-scored deals, scan_deals runs a live product-specific scan, price_check returns market price distribution, and flip_margin estimates profit and ROI. There is no meaningful overlap that would cause an agent to pick the wrong tool.
Names are readable and share a lowercase_snake_case style, but the grammatical pattern is mixed. scan_deals and flip_margin follow a verb_noun pattern, while price_check and hot_list are noun/adjective phrases, so the naming convention is not fully consistent.
Four tools is an appropriate, focused size for a market scan server. Each tool earns its place and covers a distinct part of the workflow without unnecessary bloat or missing essentials.
The set covers the main market-scan lifecycle: discover curated deals via hot_list, scan specific products via scan_deals, verify market value via price_check, and evaluate profitability via flip_margin. There are no obvious dead ends for the server's stated purpose.