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AutomateLab-tech

Citation Intelligence MCP

signals_bing_gap

Read-onlyIdempotent

Find queries where a domain ranks well in Bing but is not cited by AI engines, joining Bing Webmaster stats with citation checks to reveal missed AI visibility.

Instructions

Join Bing Webmaster Tools query stats with am_i_cited per query. Surfaces queries where the domain ranks well in Bing but is not cited in AI - the closest editorial wins. Bing's index backs Copilot/ChatGPT/Perplexity grounding, so a Bing rank gap is an LLM-citation gap. Requires BING_WEBMASTER_API_KEY (Bing Webmaster Tools -> Settings -> API Access).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesDomain to analyze, e.g. 'automatelab.tech'. Used for the citation check.
engineNoAI engine for the citation check.auto
queriesYesQueries to cross-reference. 1-20 per call.
site_urlNoVerified Bing Webmaster site URL. Defaults to 'https://<domain>/'. Bing uses the https origin WITH a trailing slash, NOT the sc-domain: form GSC uses.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYesPer-query Bing rank + AI citation cross-reference.
domainYesDomain analyzed.
engineNoEngine used for the citation check.
site_urlYesBing Webmaster siteUrl used (https origin with trailing slash).
closest_winsYesQueries where domain ranks in Bing top-10 but is not AI-cited (the editorial gap).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.2

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds meaningful context beyond that: the required BING_WEBMASTER_API_KEY, where to obtain it, and a rationale linking Bing's index to Copilot/ChatGPT/Perplexity grounding. It does not discuss rate limits or result volume, and the output schema covers returns.

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?

Three front-loaded sentences with zero filler: purpose, the insight it yields, and the prerequisite. Every sentence carries information an agent needs to select and invoke the tool.

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?

An output schema exists so return values need not be explained, annotations cover the safety profile, and the schema fully documents all four parameters. The description supplies the remaining piece — the API-key prerequisite and its sourcing — making the definition complete for calling correctly.

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 description coverage is 100%, so the schema already documents domain, engine, queries, and site_url (including the trailing-slash/not-sc-domain subtlety). The description adds no parameter-level syntax or constraints beyond what the schema provides, so the baseline 3 applies.

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?

States a concrete operation (joining Bing Webmaster query stats with am_i_cited per query) and the output it surfaces (queries ranking in Bing but not cited by AI). The 'Bing rank gap is an LLM-citation gap' framing makes it differentiable from the adjacent signals_gsc_gap sibling.

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?

Gives clear context for use — finding editorial wins where Bing rank is strong but AI citation is absent — and implies this is a diagnostic gap-finding tool. It does not explicitly name alternatives like signals_gsc_gap or citations_check or state when not to use it, so it stops short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.