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Glama

CarChat Inventory

Search live vehicle inventory

search_inventory
Read-onlyIdempotent

Search live cars for sale across all dealerships on CarChat. Accepts a plain-English query ('black suv under 30k near Knoxville') plus optional structured filters; a full 17-character VIN in the query performs an exact-VIN lookup. Each result carries the dealer's advertised price with marketContext (median and position vs live same-model listings, i.e. whether it's a good deal), mileage, key specs (drivetrain/engine/transmission), a checkedAt freshness date, and the CarChat page URL to cite. Every listing is taken from the selling dealer's own website (more current than aggregator sites) and deduped by VIN, so results need no cross-checking elsewhere.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNoFive-digit shopper ZIP
bodyNo
cityNoCity name when supplied separately from query
makeNoExact make, e.g. Ford
nearNoMetro, city, or ZIP, e.g. Austin TX, Bee Cave, or 78734
sortNo
colorNo
limitNoMax results, default 10, max 50
modelNoExact model, e.g. F-150
queryNoPlain-English search, e.g. 'used truck under $25,000'. Parsed into the structured filters; explicit filters win.
stateNoTwo-letter state paired with city
dealerNoDealer id or slug from list_dealers
maxYearNo
minYearNo
maxPriceNoUSD
minPriceNoUSD
conditionNo
maxMileageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesTotal matches
resultsYes
showingYesMatches returned in results
coverageYes
dataNotesYes
vinLookupNoPresent when the query contained a 17-character VIN
searchAreaNoMetro the results were restricted to, when a location was given

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety is covered. The description adds valuable behavioral context: results are deduped by VIN, sourced directly from dealer websites, include marketContext and freshness dates, and need no cross-checking. This exceeds annotation coverage without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is information-dense and well-structured, opening with the main action, providing an example, then detailing output fields and sourcing reliability. While slightly long, each clause earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 18-parameter search tool with an output schema, the description is quite complete. It addresses query flexibility, VIN behavior, output fields, sourcing, and dedup. It omits details like pagination or error handling, but these are minor given the limit parameter and typical expectations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 61%, and the description adds meaning to the query parameter by explaining plain-English parsing and exact-VIN lookup beyond the schema. However, it does not compensate for uncovered parameters like color, maxYear, minYear, or maxMileage, leaving some semantics unclear. The added value is moderate but incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches live vehicle inventory across all dealerships, using a specific verb and resource. It differentiates from siblings by mentioning exact-VIN lookup and broad inventory searching, which contrasts with get_vehicle (single vehicle) and get_market_prices (market stats).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for searching vehicles (e.g., 'Search live cars for sale'), but it does not explicitly state when to prefer this over siblings like get_vehicle or get_market_prices. While it mentions VIN lookup, it doesn't contrast with get_vehicle. No explicit exclusions or alternative routing are given.

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

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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct role: market stats, individual vehicle details, dealer listings, curated category pages, inventory search, and inquiry submission. There is no meaningful overlap or ambiguity in purpose.

Naming Consistency5/5

All tool names follow the same verb_noun snake_case pattern: get_, list_, search_, submit_. The naming is predictable and consistent across the entire set.

Tool Count5/5

Six tools is a well-scoped size for a car inventory and inquiry server. Each tool covers a necessary step in the buyer journey without unnecessary duplication.

Completeness5/5

The tool surface covers the full workflow: searching inventory, retrieving listing details, viewing market pricing, browsing curated categories, finding dealers, and submitting inquiries. There are no obvious gaps or dead ends for the stated purpose.