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get_citations

Get the latest citation check per (question, engine) for a cataloged domain: the question asked, the engine, whether the answer cited this domain, the URL of theirs it cited, and the day checked. Claimed domains only, read-only, one row per cell so re-running the checker cannot inflate anything. The engine answers are stored verbatim as the evidence behind each verdict but are NOT served here; the owner sees those in their dashboard. An empty list means no check has run yet, never "never cited".

Input Schema

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

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description fully discloses crucial behaviors: read-only nature, idempotency (re-running cannot inflate), that engine answers are stored but not served here, and the meaning of an empty list as 'no check run yet' rather than 'never cited'. This goes beyond a basic description and provides valuable operational context.

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 concise yet information-dense, with every sentence contributing value: it lists output fields, states scope and idempotency, clarifies content exclusions, and explains list interpretation. There is no redundancy or filler, making it efficient for an agent to parse.

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 one-parameter tool with no output schema, the description thoroughly covers what is returned, what is not returned, and how to interpret results, including edge cases. It is complete enough for an agent to understand the tool's behavior and expected output without additional context.

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?

The schema already fully describes the single parameter 'domain' with example (acme.com) and the description confirms it should be a cataloged domain. Since schema coverage is 100%, the description adds no additional parameter meaning beyond restating the context. Baseline 3 is appropriate.

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 retrieves the latest citation check per (question, engine) for a cataloged domain, listing the specific fields returned (question, engine, citation status, URL, day). It distinguishes from sibling tools by focusing on granular per-question/per-engine citation data rather than aggregate domain lists.

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 gives clear context: it is for claimed domains only, is read-only, and returns one row per cell. It also explains how to interpret an empty list. However, it does not explicitly name alternative tools or state when not to use this tool, though the context strongly implies its narrow scope.

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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