@striderlabs/mcp-chickfila

find_locations

Find nearby Chick-fil-A restaurants by entering a ZIP code or city name, with optional search radius.

Instructions

Find nearby Chick-fil-A locations by ZIP code or city name.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "zip_or_city": "<zip_or_city>"
    },
    "name": "find_locations"
  }
}

Input Schema

Name	Required	Description	Default
`zip_or_city`	Yes	ZIP code or city name, e.g. "30301" or "Atlanta, GA"
`radius_miles`	No	Search radius in miles (default: 25)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 2, 2026

TDQS

A3.8/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the basic function and does not mention what 'nearby' entails (e.g., default radius), what the response format is, or how invalid inputs are handled. For a tool with no annotations, this lacks meaningful behavioral insight.

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

Conciseness5/5

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

The description is a single, front-loaded sentence that directly states the tool's purpose. There is no wasted text, and it is appropriately concise for a simple tool.

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?

Given the tool's simplicity, the description and schema together are largely sufficient. However, without an output schema, the description does not clarify what the tool returns (e.g., a list of locations with addresses), which could be important for the agent. It is not severely incomplete, but a brief note on the return type would enhance completeness.

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?

The input schema covers both parameters completely, so the baseline is 3. The description's mention of 'ZIP code or city name' aligns with the `zip_or_city` parameter and 'nearby' implies the radius, but it does not add information beyond what the schema already provides. Thus, it meets the baseline without improving parameter understanding.

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 nearby Chick-fil-A locations by ZIP code or city name.' It uses a specific verb ('Find'), a resource ('locations'), and search criteria ('ZIP code or city name'), distinguishing it from sibling tools that handle menus, nutrition, or orders.

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

Usage Guidelines4/5

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

The description implies when to use the tool: whenever a user needs store locations based on a ZIP code or city. It does not explicitly exclude alternatives, but sibling tools are distinct enough that the intended use is clear. No further usage guidance or prerequisites are provided, which is acceptable for a simple lookup tool.

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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