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AutomateLab-tech

Citation Intelligence MCP

gsc_citation_gap

Find queries where your domain ranks in Google Search but is not cited by AI, revealing editorial gap opportunities.

Instructions

Join Google Search Console performance with am_i_cited per query. Surfaces queries where the domain ranks well in Google but is not cited in AI - the closest editorial wins. Requires GCP service account creds (credentials_path or GOOGLE_APPLICATION_CREDENTIALS env).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to analyze, e.g. 'automatelab.tech'. Used both for the GSC site URL and the citation check.
queriesYesQueries to cross-reference. 1-20 per call.
site_urlNoOverride the GSC siteUrl. Defaults to 'sc-domain:<domain>'.
start_dateYesISO date for GSC range start, e.g. '2026-04-01'.
end_dateYesISO date for GSC range end, e.g. '2026-05-01'.
engineNoAI engine for the citation check.auto
credentials_pathNoPath to GCP service account JSON. Defaults to env GOOGLE_APPLICATION_CREDENTIALS.
Behavior3/5

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

With no annotations provided, the description carries the full burden. It mentions credential requirements but does not disclose behavioral traits (e.g., idempotency, side effects, rate limits). The word 'join' suggests a read-only operation, but more explicit transparency would improve interpretation.

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 quickly covering prerequisites. Every word adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should explain return values. It hints at output (queries with gaps) but lacks structure details. For a tool combining two data sources, more output context is needed for complete understanding.

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

Parameters5/5

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

Schema coverage is 100%, and the description adds valuable context beyond the schema: domain is used for both GSC and citation check, queries are limited to 1-20, and defaults for site_url and engine are noted. This significantly helps an agent understand parameter usage.

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 'joins Google Search Console performance with am_i_cited per query' and 'surfaces queries where the domain ranks well in Google but is not cited in AI', distinguishing it from siblings like am_i_cited or check_citations.

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 specifies a prerequisite ('requires GCP service account creds') and implies the use case (finding citation gaps). It does not explicitly exclude scenarios, but the purpose is clear enough for an agent to decide when to invoke.

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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