What the LinkedIn archive analysis for performance patterns, AI clichés and content similarity prompt does

Act as a multilingual LinkedIn content-forensics and performance analyst.

The prompt will, at minimum:

  • Validate post IDs, dates, exposure metrics, denominators, paid status, edits, missing posts and reporting windows before comparing performance
  • Separate association by topic, format, author, hook, length and timing from causal claims, and report sample sizes and confounders
  • Define exact duplication, structural reuse, semantic similarity, boilerplate and generic AI-style phrasing as separate, explainable classes
  • Do not infer AI authorship, plagiarism or intent from text patterns alone; use the supplied pattern dictionary as a review aid, not proof
  • Convert findings into a preserve/rewrite/retire/test backlog while protecting required disclosures and legitimate brand repetition

Who it is for

Gökhan Güzel's SaaS prompt for ChatGPT users: marketers, founders, agencies and consultants who need an auditable, evidence-based deliverable instead of generic advice.

What you get

  • Input-integrity and metric-definition report
  • Segmented LinkedIn performance pattern analysis
  • Duplicate and similarity clusters with exemplars
  • AI-style cliché review queue with evidence limits
  • Prioritised content remediation and experiment backlog

Variables

PlaceholderPurpose
{{ai_pattern_dictionary}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{audience_context}}Target audience, segment, persona, customer/player or industry group
{{brand_voice}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{content_taxonomy}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{date_range}}Date, time or period value; state ISO format, time zone, start/end boundary and comparison period
{{decision_goal}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{exclusions}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{linkedin_export}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{metric_definitions}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{paid_organic_flags}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{post_archive}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{similarity_thresholds}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{timezone}}Date, time or period value; state ISO format, time zone, start/end boundary and comparison period

How to use

Copy the prompt with the button above, replace every {{placeholder}} with your verified data, and paste it as the first message in a new ChatGPT conversation. The prompt runs a short question gate first; answer it, then the deliverable is produced.

Run LinkedIn archive analysis for performance patterns, AI clichés and content similarity in ChatGPT

Open a new ChatGPT chat, paste the filled-in LinkedIn archive analysis for performance patterns, AI clichés and content similarity prompt and answer the short question gate. ChatGPT then returns the executive decision, the evidence ledger and the task-specific tables in one reply.

Source

Original file in the multilingual prompt library on GitHub: