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AEO Auditor — AI Search & Agent Readiness Engine

Get Domain Benchmark

get_domain_benchmark
Read-onlyIdempotent

Look up a domain AEO readiness benchmark score and 4-pillar breakdown, or query the industry leaderboard directory. When to use: Call this tool when you specifically need to execute 'get_domain_benchmark' on AEO Auditor (aeoauditing.com). Do NOT use this tool when another specialized tool fits better (use 'audit_domain' or 'validate_robots_txt' for their respective operations). Parameters: domain (optional), category (optional). Behavior & Side Effects: Strictly read-only, idempotent query with zero state mutation; public unauthenticated access allowed; rate-limited to 60 requests/min per IP. Returns: Structured JSON object containing status, matched records or computed metrics, and canonical action URLs.

Input Schema

NameRequiredDescriptionDefault
domainNoOptional domain name to retrieve benchmark profile (e.g. "openai.com"). Omit to list top leaderboard domains.
categoryNoOptional industry category filter when listing leaderboard benchmarks (e.g. "AI & ML", "FinTech", "DevTools", "SaaS").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior, so the description is not solely responsible for those traits. It adds useful operational context beyond annotations: public unauthenticated access and a rate limit of 60 requests/min per IP, plus a high-level return shape.

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 front-loaded with the core purpose and structured with labeled behavior and return sections. Some space is wasted on the tautological when-to-use sentence, but overall it remains efficient and readable.

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?

For a simple read-only lookup tool with full schema coverage and rich annotations, the description covers both query modes, access/auth expectations, rate limits, and the general return shape. Although there is no output schema, the high-level return description is sufficient for an agent to invoke it correctly.

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 description coverage is 100%, and both optional parameters are already documented with examples in the schema. The description only lists 'domain (optional), category (optional)' without adding meaning beyond what the schema provides, so the baseline 3 applies.

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 states a specific verb and resource: looking up a domain's AEO readiness benchmark score with a 4-pillar breakdown, or querying the industry leaderboard directory. It also names sibling tools, making the tool's scope distinguishable from audit_domain and validate_robots_txt.

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?

It explicitly says when not to use the tool and names the sibling alternatives, which is useful. However, the positive usage guidance is circular ("Call this tool when you specifically need to execute 'get_domain_benchmark'") rather than stating the actual condition or preference that should select this 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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