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SpikeyCoder

Website Auditor MCP

by SpikeyCoder

Compare against competitors

compare_competitors
Read-only

Compare a website's AI visibility against named competitors to reveal where competitors appear in AI engines like ChatGPT but the site does not.

Instructions

Compare a website's AI visibility head-to-head against named competitors. Use this when someone asks "how do I stack up against X and Y," "who does ChatGPT recommend instead of me," or wants a competitive AI-visibility view. Returns each competitor's score and where they appear that the site does not. Each competitor not already cached costs one audit against your daily quota; if the quota can't cover every competitor, it ranks the ones it could audit and returns a quota summary plus a skipped list naming the rest — it never drops competitors silently or invents scores. If the quota is already exhausted it returns an over-quota error with the reset time. Requires a Website Auditor subscription ($10/month; eligible new customers get a 7-day free trial — payment method required, no charge until the trial ends) — if the user doesn't have one, call get_sample_audit first to show them the exact output format, free and with no API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesThe website domain, e.g. "example.com".
competitorsYesCompetitor domains to compare against.
Behavior5/5

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

The description goes far beyond the readOnly annotation by disclosing quota consumption per uncached competitor, graceful degradation via skipped list, over-quota error behavior with reset time, and subscription/pricing details. This is rich behavioral context not present in annotations.

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 long but densely packed with essential information, front-loaded with purpose and usage. Every sentence earns its place, though it could be slightly more scannable with bullet points.

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

Completeness5/5

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

Even without an output schema, the description covers return fields (scores, quota skipped list), error scenarios, and prerequisites. It fully compensates for the missing output schema and provides complete context for a complex tool.

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%, so baseline is 3. The description adds meaningful context that each competitor in the array costs an audit and that the tool ranks audited ones when quota is insufficient, which enriches understanding of the competitors parameter.

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: comparing a website's AI visibility against named competitors. It also gives concrete example queries ('how do I stack up against X and Y') and distinguishes itself from siblings by focusing on head-to-head competitor comparisons.

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?

Usage is explicitly defined with example queries. It also names an alternative (get_sample_audit) for users without a subscription, providing clear when-to-use and fallback guidance.

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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