A
licenseNot graded
qualityC
maintenanceScrapes real-time gas prices from GasBuddy.com to find the cheapest fuel in any US city or zip code.
1
MIT
ServiceBuddy Auto Repair Savings
Server Details
Auto repair price benchmarks and current service deals for any US ZIP. No account required.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
A4.4/5.0
Tool DescriptionsA
Average 4.5/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
Only one tool exists, so there is zero ambiguity about which tool to select. The tool's description is clear about its single purpose.
Naming Consistency5/5
The single tool name 'get_evaluated_savings' follows a clear verb_noun pattern, and with only one tool, consistency is trivial.
Tool Count2/5
The server provides only one tool for a domain that could benefit from separate tools for pricing lookup, coupon discovery, and quote comparison. This feels under-scoped for the broad set of services and features described.
Completeness4/5
The tool covers the core needs: typical pricing, best discounts, effective price, and optional quote comparison. Minor gaps exist (e.g., shop listing, specific negotiation handling), but the surface is largely complete for its stated purpose.
Available Tools
1 toolget_evaluated_savingsFind Best Auto Service DealARead-onlyIdempotentInspect
Find the best current auto-service deal near a US ZIP or metro and see what you'd actually pay. Returns the local typical price for the service (oil change, brakes, battery, diagnostic, coolant flush, tire rotation, tires), the best current coupon, discount, or rebate, and the net out-of-pocket "effective price" after discounts and rebates, with caveats. Optionally compares against a shop quote the user already has. Use when someone asks what a repair should cost, whether a quote is fair, or where to find a coupon. US only; 16 major metros are priced locally, other ZIPs use national averages.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| zip | No | 5-digit US ZIP, e.g. "11205". Give zip or city for local pricing; omit both for national averages. | |
| city | No | Metro slug, e.g. "new-york-city", "los-angeles", "houston". Overrides zip. | |
| shop_name | No | Shop or chain the user mentioned, e.g. "Jiffy Lube", to prioritise that brand's deals. | |
| quoted_price | No | A quote the user already has, in USD, e.g. 119. Enables "is this quote fair?" comparison. | |
| service_variant | No | Oil type (oil_change only). Omit to evaluate each offer on its own stated oil type. | |
| service_category | No | Service to price. | oil_change |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| cached | Yes | True if served from the 12-hour deal cache. |
| summary | Yes | Plain-English summary of the local price and best deal. |
| benchmark | Yes | |
| best_match | Yes | Highest-savings offer, or null if none found. |
| offers_count | Yes |
Tool Definition Quality
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safe, read-only nature is already declared. The description adds useful behavior: it returns typical price, best coupon, effective price with caveats, and optionally compares against a quote. It doesn't go into details like data freshness, but given strong annotations, this is solid.
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 a single well-structured paragraph that starts with the main purpose, then details the returns and usage context. It is concise, though a bit long; every sentence adds useful information, but a slight restructuring could make it even more scannable.
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?
The tool returns an effective price with caveats, and there is an output schema (not shown) that likely documents the return structure. The description covers input semantics, including service types and the quote comparison, and notes US-only and local coverage. It's complete for agent use, though it doesn't mention error conditions, but these are not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds value by explaining the overarching logic: zip/city for local pricing, shop_name for brand priority, quoted_price for comparison, and service_variant for oil type. This goes beyond schema descriptions, especially for the interplay between zip and city and the commas in effective price.
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's function: find the best auto-service deal near a US ZIP or metro and compute the effective price after discounts. It specifies available service types and the comparison option. The title reinforces this, and there are no siblings that could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: 'Use when someone asks what a repair should cost, whether a quote is fair, or where to find a coupon.' It also notes US-only and explains the distinction between local pricing for 16 metros and national averages for other ZIPs, providing clear context without naming alternatives.
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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