grounded-aeo

generate_free_record

FINAL STEP of making a site AI-citable: generate a free, self-declared v=AEO1 DNS record and .well-known/aeo.json the user publishes on their own domain, so AI engines can verify the facts came from the owner rather than a scrape. Returns the exact TXT record and JSON file with publishing instructions. No crawl, no verification, no account. WRITE action, rate-limited to 10/hour per caller.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Business name
`hours`	No
`domain`	Yes
`address`	No
`category`	No
`services`	No

TDQS

A3.9/5.0

Behavior4/5

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

Description discloses key behaviors: WRITE action, rate-limited to 10/hour, returns exact TXT record and JSON with publishing instructions, no crawl/verification/account. However, it doesn't mention idempotency or side effects beyond generation.

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?

Description is a single concise paragraph with no wasted words. It front-loads the purpose and efficiently covers key info.

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?

Description covers return values and rate-limiting, which is helpful given no output schema. However, parameter explanations are missing, and sibling tools are not referenced.

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

Parameters1/5

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

Only one parameter (name) has a description in the schema; the other five (hours, domain, address, category, services) have no descriptions. The tool description does not explain these parameters, leaving significant ambiguity.

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?

Description clearly states the tool's purpose: final step to make a site AI-citable by generating DNS record and JSON. It specifies the action (generate and return exact records with instructions) and distinguishes from siblings (no crawl, verification, account).

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?

Description indicates this is the 'FINAL STEP' and mentions rate-limiting and that it's a WRITE action with no crawl/verification/account. While it doesn't explicitly mention when to use alternatives, the context implies it's for self-declaration after other steps.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct resource or action: checking AEO records, reading SERP data, generating records, retrieving facts, citations, competitor snapshots, engine visibility, keyword gaps, etc. Even similar-sounding tools like get_citations and get_cited_domains are clearly delineated by their descriptions. No two tools appear to overlap in purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun convention using snake_case: check_*, get_*, generate_*, propose_*, run_*, search_*. There is no mixing of casing or verb styles, and each name instantly communicates the action and subject.

Tool Count5/5

With 14 tools, the server is well-scoped for the domain of AI citation optimization. Each tool contributes a unique capability, and the count is neither sparse nor bloated. The number fits comfortably within the ideal 3-15 range for a focused server.

Completeness4/5

The tool surface covers the core lifecycle: checking existing records, generating new records, auditing and fixing sites, retrieving data, analyzing gaps, and proposing briefs. Minor gaps exist such as no direct tool for claiming a domain or managing tracked keywords/competitors, but those may be external to the MCP server. Overall, the set supports the intended workflows well.

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