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grounded-aeo

by com.groundedaeo

propose_briefs

Propose ranked content briefs for a cataloged domain, built from data already collected for it: tracked questions where the answer did not cite them, keywords with AI-prompt demand no tracked question covers, People Also Ask questions nothing answers, and terms asked far more of AI assistants than of Google. Each brief names the exact question to answer, a format (9:16 UGC video, on-site answer, or short post), an outline, and the ONLY claims that may be made: the owner's published verified facts, verbatim. Deterministic and read-only: no new data is fetched and nothing is generated, so a brief with no evidence behind it is never returned. Claimed domains only; up to 6 briefs; an empty list means there is not yet enough collected data, never that there is no opportunity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesCompany domain, e.g. acme.com

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It transparently states that the tool is deterministic, read-only, fetches no new data, generates nothing, and never returns a brief without supporting evidence. It also restricts claims to verified facts verbatim, giving strong insight into side effects and constraints.

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 dense but every sentence serves a purpose: purpose, data source, output contents, constraints, and behavioral guarantees. It is front-loaded with the main verb and resource, and the structured elaboration flows logically. No filler or repetition.

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?

Given the tool's complexity (multiple data sources, formats, claim restrictions, limits), the description covers all key aspects: what it produces, what evidence is used, what claims are allowed, the maximum number of briefs, and the meaning of an empty result. Even though there is no output schema, the description sufficiently explains return behavior.

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?

The schema already provides a clear description for 'domain' (Company domain, e.g. acme.com). The tool description adds critical constraints that 'domain' must be cataloged and claimed, which enriches parameter semantics beyond the schema baseline. This additional context is valuable and not redundant.

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 uses a specific verb ('Propose') and resource ('content briefs for a cataloged domain'), clearly distinguishing it from sibling tools like 'get_keyword_gap' or 'run_audit' by emphasizing it generates briefs from already-collected data rather than performing new analysis. The scope and output are precisely defined.

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 clearly states when to use the tool: for a cataloged domain with collected data, and for claimed domains only. It also provides guidance on interpreting results (empty list = insufficient data). It does not explicitly name alternative tools for other scenarios, but the context is strong enough.

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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