List live GoDaddy auctions that already carry at least one bid. Sort by soonest closing, most bids, biggest appraisal-to-price gap, or lowest price. Filter by extension and maximum price. Auctions that have already closed are excluded.
| Name | Required | Description | Default |
|---|---|---|---|
| tld | No | Restrict to an extension, e.g. com | |
| sort | No | Default closing. | |
| limit | No | 1 to 200, default 25. | |
| max_price | No | Only auctions at or below this price in USD. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well: it clarifies that only auctions with at least one bid are returned, that closed auctions are excluded, and outlines sorting and filtering behaviors. It could mention pagination or rate limits, but for a read-only list tool, this is strong.
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, each adding essential information: what is listed, how to sort, how to filter. No wasted words, and the most critical line ('auctions with at least one bid') comes first.
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 zero required parameters, no output schema, and moderate complexity with 4 parameters and a filter, the description covers the key facets (live, bidding, sorting, filtering, exclusion). It lacks explicit mention of pagination or that the default sort is 'closing', but overall is nearly complete for an agent.
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 parameters well. The description adds context about sorting options ('soonest closing, most bids...') and filter behavior ('only auctions at or below this price'), but does not add new parameter semantics beyond enumerating the sort options.
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 uses a specific verb ('list') and resource ('live GoDaddy auctions'), and clearly scopes to auctions with at least one bid. It distinguishes itself from siblings like 'lookup_domain' or 'market_stats' by focusing on live auctions with active bids.
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 states the tool is for finding auctions that are closing soon, have many bids, or good value, and that closed auctions are excluded. It does not explicitly list when not to use it or name alternatives, but the context from siblings and the specific criteria imply appropriate use.
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 targets a clearly distinct aspect of GoDaddy domain auction data: market overview, per-TLD stats, bid rate analysis, live auction listings, and single-domain lookup. There is no overlap in purpose.
Tool names are descriptive but inconsistent in pattern: 'list_auctions' and 'lookup_domain' use verb_noun, while 'bid_rates', 'market_stats', and 'tld_stats' use noun_noun. The mix of imperative and declarative styles could confuse an agent about which tools are actions vs. data queries.
With 5 tools, the server is well-scoped for its domain. Each tool provides a distinct function without redundancy, and the count is neither too thin nor too heavy for a specialized domain auction data server.
The tool set covers the essential operations for querying GoDaddy auction market data: aggregate stats, per-TLD breakdown, bid rate insights, a live auction list, and individual domain lookup. No obvious gaps exist for the stated purpose.