This key's usage for the current month: total calls and the separate valuation allowance (which comps, sold history, trend and flip-score draw down), plus the reset date. Call it to pace a long run instead of hitting a 429 mid-task.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safe-read nature is covered. The description adds valuable behavioral detail: what the usage report contains (total calls, separate valuation allowance with components, reset date). It does not contradict annotations. A slight gap is lack of details on response format or error handling, but the added context is substantive.
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. The first front-loads the core information (what is reported), the second provides a practical usage tip. No filler or redundancy. Perfectly sized for the tool's simplicity.
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 no params, no output schema, and a simple read-only function, the description fully covers what the tool does and when to use it. It mentions the return contents (total calls, allowance breakdown, reset date), satisfying the need to explain return values in the absence of an output schema. No other information is needed for such a lightweight tool.
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 tool has zero parameters, so the description carries no param burden. It appropriately references 'this key' (the auth key) as the implicit input. Baseline 4 is suitable given no params need explanation.
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 reports the current month's API usage: total calls, valuation allowance breakdown, and reset date. It distinguishes itself from sibling tools (which focus on comps, listings, trends) by being the only usage-monitoring tool. The verb 'Call it' implies the action of retrieving usage 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: 'Call it to pace a long run instead of hitting a 429 mid-task.' This gives a concrete scenario and outcome. While no alternative tool is named, the context makes clear this is the go-to for monitoring usage. No ambiguity.
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.
Most tools have distinct purposes: search_listings and get_listing differ by lookup method, and get_sold_comps, get_sold_history, and get_price_trend are clearly separated by whether they provide aggregate percentiles, individual sales, or monthly trends. The only minor ambiguity is between get_sold_comps and get_price_trend, both derived from the same comps, but their descriptions make the difference in output format clear.
All tool names follow the consistent verb_noun pattern using lowercase snake_case: get_* for data retrieval and search_listings for searching. There are no mixed conventions or style inconsistencies, making the naming highly predictable.
With 8 tools, the server is well-scoped for its purpose of querying government auction listings and pricing data. Each tool covers a distinct functional need without redundancy, and the count is squarely in the ideal range for a domain-specific API.
The tool surface covers the core read-only workflows: searching and retrieving listings, getting sold-price comps, viewing historical sales, examining price trends, estimating flip value, and checking data coverage. A minor gap is the lack of explicit category or market listing endpoints, but agents can work around this via search_listings and get_comp_coverage.
