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AKzar1el

GEO MCP by DigestSEO

by AKzar1el

get_citations

Read-only

Retrieve actual AI citation events where assistants mention or link your brand. See the triggering prompt, response excerpt, and whether it's a link, mention, or paraphrase.

Instructions

Get the actual citation events where AI assistants mentioned or linked to the brand. Each citation includes the prompt that triggered it, the LLM's response excerpt, and whether it was a linked citation, a mention without a link, or a paraphrase. Use when the user asks 'show me where I'm cited', 'what are ChatGPT/Claude/Perplexity actually saying about my brand?', or 'give me proof of AI citations'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoNumber of previous days from which to return citations.
engineNoOptional engine filter for the citation events.
brand_idYesStable identifier of the tracked brand to inspect.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysYes
engineYes
brand_idYes
citationsYes
Behavior4/5

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

Annotations declare readOnlyHint=true, so safety is covered. The description adds value by explaining the structure of each citation (prompt, response excerpt, and whether it is a linked citation, mention, or paraphrase), which goes beyond the schema. No contradictions with annotations.

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 two sentences, front-loaded with purpose, and includes usage examples without redundancy. Every sentence earns its place; no filler or repetition.

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?

With read-only annotations, a full output schema, and clear usage guidance, the description is sufficient for an agent to select and invoke the tool. It does not mention ordering or pagination, but those are not critical for this straightforward read operation.

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 coverage is 100% and all parameters have descriptive comments. The description does not add parameter-specific syntax or semantics beyond what the schema provides, so it stays at the baseline of 3 for high schema coverage.

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 ('Get') with a clear resource ('actual citation events') and details the content (prompt, response excerpt, citation type). It distinguishes itself from siblings like check_visibility and get_visibility_history by focusing on citation events rather than aggregate visibility, and it provides example user queries.

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?

Explicitly states when to use: 'Use when the user asks...' followed by three concrete example queries. This gives clear context for invocation, but it does not mention when NOT to use or mention alternatives, so it stops short of a 5.

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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