Skip to main content
Glama

compare_local_vs_chain

Score a local independent against a national chain at the same location. Returns a side-by-side breakdown with delta and verdict, confirming the independent's edge or the chain's disqualification.

Instructions

Score a local independent head-to-head against a national chain at the same location. Resolves both businesses via Google Places, runs LocalRoots scoring on each, and returns a side-by-side breakdown with a score delta and plain-language verdict. Use this when a user wants to understand exactly how much more independent a local spot is compared to the chain down the street, or to validate that a suspected chain is actually disqualified. National chains will score tier_4 (disqualified) in almost all cases. A warning fires if the chain somehow scores higher than the independent, which usually means the chain name is not in the bundled database or the independent has a very thin Google profile. Checks the Wayback Machine for the independent's website to infer tenure before 2005, 2010, or 2015.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nearYes
categoryNo
chain_nameYes
independent_nameYes
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the Google Places resolution, LocalRoots scoring, side-by-side output, warning behavior, and Wayback Machine tenure check. While it doesn't mention side effects or rate limits, it offers substantial behavioral detail.

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?

At five sentences, the description is slightly long but every sentence adds useful information. The first sentence is a strong front-loaded summary, and the rest covers usage, edge cases, and the tenure check.

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 no output schema, the description covers the key output elements (side-by-side breakdown, delta, verdict) and process steps. It also handles likely edge cases (chain scoring higher, thin Google profile) and the tenure check, making it quite complete for a comparison tool.

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

Parameters2/5

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

Schema coverage is 0%, and the description does not explicitly name the parameters (independent_name, chain_name, near, category). It implies their roles contextually (independent vs chain, location) but leaves category unexplained and doesn't provide format details, so compensation is insufficient.

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 opens with a specific verb and resource: 'Score a local independent head-to-head against a national chain.' It clearly distinguishes from siblings by focusing on comparison, and details the process and output.

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?

Explicitly states 'Use this when a user wants to understand exactly how much more independent a local spot is compared to the chain down the street, or to validate that a suspected chain is actually disqualified.' This provides clear use cases, though it doesn't name alternative tools or when not to use it.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/parissharpe/local-roots-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server