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Winning Copy Extraction

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kenny589
winning-copy-extraction

Extract, analyze, and replicate the patterns behind your highest-performing email copy. Turn individual campaign wins into repeatable copy frameworks your team can deploy across every campaign.

Overview

Publisherkenny589
Repositorygtm-flywheel
Skill namewinning-copy-extraction
Stars
71
Forks
26
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by kenny589 on GitHub. Read the source before you install it.

Installation

Install the Winning Copy Extraction AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/kenny589/gtm-flywheel/tree/main/campaign-analytics/winning-copy-extraction
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kenny589/gtm-flywheel.git /tmp/gtm-flywheel
mkdir -p .claude/skills
cp -r /tmp/gtm-flywheel/campaign-analytics/winning-copy-extraction .claude/skills/winning-copy-extraction
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Winning Copy Extraction in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Winning Copy Extraction on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Winning Copy Extraction is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Winning Copy Extraction

When to Use

  • After accumulating 30+ campaigns with performance data
  • When onboarding a new copywriter or SDR who needs to learn "what works here"
  • Building AI-assisted copy generation systems that learn from your data
  • Creating a copy playbook for a specific vertical, persona, or campaign type
  • Quarterly copy audits to identify trends and refresh stale templates

Framework

The Copy Extraction Pipeline

Winning copy doesn't come from brainstorming — it comes from data. Here's the systematic process for extracting what works from what you've already sent.

Step 1: Pull Campaign Data
    → All campaigns with 200+ sends and at least 14 days of data
    ↓
Step 2: Rank by Positive Reply Rate
    → Sort descending. Top 10% = your winners.
    ↓
Step 3: Analyze the Winners
    → What patterns emerge across your best copy?
    ↓
Step 4: Codify the Patterns
    → Turn patterns into reusable frameworks
    ↓
Step 5: Test Against New Copy
    → Use pattern-based copy in new campaigns. Measure.
    ↓
Step 6: Update the Playbook
    → Add new winners. Remove copy that stopped working.

Step 1: Define "Winning" Copy

Before extracting patterns, define your threshold:

MetricWinning ThresholdMinimum Sample
Positive reply rateTop 20% of all campaigns200+ sends
Reply-to-meeting rate> 40%10+ replies
Step 1 reply rate> 5%200+ sends on Step 1
Follow-up reply rate> 3% (Step 2-4)150+ sends per step

Why positive reply rate, not total reply rate? Total reply rate includes "not interested" and "remove me." Positive reply rate measures genuine demand. A campaign with a 15% total reply rate and 1% positive reply rate is worse than a campaign with 8% total and 5% positive.


Step 2: The Copy Anatomy Framework

For every winning email, break it down into its atomic components:

ComponentWhat to CaptureExample
Subject lineExact text, word count, formatacme + outbound (3 words, lowercase)
Opening typeHow the first line worksSignal-based observation
Opening lineExact first sentence"Noticed you're hiring 3 SDRs in Austin"
Pain articulationHow the problem is framedProblem/cost framing: "Most teams at your stage..."
Value propositionHow the solution is positionedOutcome-focused: "Our clients see 3x pipeline in 90 days"
Social proof typeWhat credibility is usedMetric from similar company
CTA typeHow the ask is structuredLow-friction question: "Worth exploring?"
CTA textExact CTA"Would it help to see how {{similar_company}} handled this?"
ToneOverall voiceConversational, peer-to-peer
LengthWord count87 words
Personalization levelHow tailored it feelsLevel 4: Business event signal
ArchetypeWhich copy archetype it matchesThe Observation (Archetype 1)

Step 3: Pattern Recognition

After analyzing 10-20 winning emails, look for patterns across these dimensions:

Subject Line Patterns
PatternExampleWin Rate
{{company}} + topic"acme + outbound"__%
quick [role] question"quick vp sales question"__%
re: [trigger] (real, not faked)"re: your series b"__%
[topic] idea"pipeline idea"__%
[mutual element]"fellow YC founder"__%

Track which patterns your audience responds to. Different personas respond to different subject formulas.

Opening Line Patterns
PatternExampleWhen It Works
Signal observation"Saw you just raised..."When you have a specific, timely signal
Problem statement"Most VP Sales at Series B companies..."When the pain is universal and well-known
Compliment + pivot"Your post about X was great — we're seeing..."When they've published relevant content
Shared context"Fellow [industry/stage/community] member here"When you have a genuine shared experience
Direct value"We helped [similar company] achieve [result]"When your proof point is strong enough to lead
CTA Patterns
PatternExampleWhen It Works
Low-friction question"Worth a look?"Default. Works almost everywhere.
Resource offer"Want me to send the playbook?"When you have a valuable resource
Relevance check"Is this something you're thinking about?"When you're unsure about timing
Social proof question"Want to see how {{company}} handled this?"When you have a strong case study
Direct ask"Open to a quick conversation?"When signals are very strong
Length Patterns

Analyze the word count distribution of your winning emails:

Winning email length distribution:
< 60 words:    __% of winners  → Very concise, works for senior executives
60-90 words:   __% of winners  → Sweet spot for most audiences
90-120 words:  __% of winners  → Acceptable for complex value props
120-150 words: __% of winners  → Getting long, but can work with strong copy
> 150 words:   __% of winners  → Rarely wins. If it does, the content was exceptional.

Step 4: Build the Copy Playbook

Turn patterns into a document your team can reference:

The Winning Copy Playbook Structure
COPY PLAYBOOK: {{Company/Product Name}}
Last Updated: {{date}}
Based on: {{number}} campaigns, {{number}} emails analyzed

--- SUBJECT LINES ---
Top 3 formulas:
1. {{formula}} — avg open rate: __%
2. {{formula}} — avg open rate: __%
3. {{formula}} — avg open rate: __%

Avoid: {{patterns that consistently underperform}}

--- OPENING LINES ---
Top 3 patterns:
1. {{pattern}} — used in __% of winning emails
2. {{pattern}} — used in __% of winning emails
3. {{pattern}} — used in __% of winning emails

--- BODY COPY ---
Winning archetypes (ranked):
1. {{archetype}} — avg positive reply rate: __%
2. {{archetype}} — avg positive reply rate: __%
3. {{archetype}} — avg positive reply rate: __%

--- CTAs ---
Top 3 CTAs:
1. "{{exact CTA}}" — conversion: __%
2. "{{exact CTA}}" — conversion: __%
3. "{{exact CTA}}" — conversion: __%

--- PROOF POINTS ---
Most effective:
1. {{proof point}} — used in campaign: {{name}}
2. {{proof point}} — used in campaign: {{name}}

--- TONE GUIDELINES ---
Voice: {{description}}
Do: {{list of tone elements that work}}
Don't: {{list of tone elements that fail}}

--- EMAIL LENGTH ---
Target: {{X-Y}} words
Never exceed: {{max}} words

Step 5: Copy Decay Detection

Even winning copy stops working eventually. Monitor for these decay signals:

IndicatorWhat It MeansAction
Positive reply rate dropped 30%+ from peakCopy fatigue or market shiftTest new variants
Same copy performing well for 3+ monthsUnusual — validate the dataEnjoy it while it lasts
Step 1 replies declining but Step 2-3 stableSubject line fatigueRotate subjects, keep body
All steps declining simultaneouslyLarger issue — list quality, deliverability, or marketFull diagnosis needed
New competitor emerged in the spaceMarket dynamics changedUpdate positioning and proof points

Copy refresh cadence:

  • Subject lines: rotate every 4-6 weeks
  • Body copy: refresh every 8-12 weeks
  • Full sequence: rebuild every quarter

Step 6: Competitive Copy Analysis

Analyze the cold emails YOU receive to learn from competitors:

What to TrackWhy
Subject line formulaSee what competitors test
Opening approachHow are they personalizing?
Value propositionWhat outcomes are they claiming?
CTA styleDirect vs. soft ask
Sequence lengthHow many touches before they stop?
ToneProfessional vs. casual
Unique anglesWhat are they saying that you aren't?

Build a swipe file: Save every cold email you receive (good and bad). Annotate what worked, what didn't, and why. This becomes a creative resource for your team.


Cross-Campaign Copy Intelligence

The most powerful analysis comes from comparing across campaigns:

By Persona
Which copy patterns work best for:
- VP Sales: {{patterns}}
- Founders: {{patterns}}
- RevOps: {{patterns}}
- Marketing: {{patterns}}
By Industry
Which angles resonate with:
- B2B SaaS: {{angles}}
- Agencies: {{angles}}
- E-commerce: {{angles}}
- Professional services: {{angles}}
By Company Stage
Which proof points convert at:
- Seed-Series A: {{proof_points}}
- Series B-C: {{proof_points}}
- Enterprise: {{proof_points}}

This cross-analysis is where the compounding happens. Every campaign you run makes every future campaign better — but only if you extract and codify the learnings.

Templates

Copy Analysis Worksheet

Campaign: {{name}}
Positive Reply Rate: __%
Sample Size: __ sends

Subject: {{exact subject}}
Subject Pattern: {{formula used}}

Opening Line: "{{exact text}}"
Opening Pattern: {{type}}

Body Archetype: {{archetype name}}
Key Pain Referenced: {{pain}}
Proof Point Used: {{proof}}
CTA: "{{exact CTA}}"
CTA Pattern: {{type}}

Word Count: __
Personalization Level: __/5

What made this work: ___
What could be improved: ___
Reusable for other campaigns? Y/N — Which: ___

Tips

  • Your top 5 campaigns contain 80% of the insights you need. Start there. Don't try to analyze 100 campaigns at once.
  • The best copy extraction happens when you have at least 30 campaigns with 200+ sends each. Below that threshold, you're working with anecdotes, not patterns.
  • Don't just copy your winning emails verbatim into new campaigns. Extract the PATTERN and apply it to the new context. "Saw you're hiring SDRs" isn't a template — "reference a specific hiring signal that indicates their investment in your category" is a template.
  • Keep a running "quote bank" of exact phrases prospects use in positive replies. Their language for saying "yes" is your most valuable copy resource — use it in future emails.
  • The fastest way to improve copy: write 10 variants of Step 1, send 200 of each, and let the data pick the winner. Your intuition about what works is often wrong. The data isn't.

Progressive disclosure: load platform-specific data extraction guides and AI copy generation prompts only when actively analyzing campaign data from a specific sending tool.

Frequently asked questions

What does the Winning Copy Extraction AI skill do?

Extract, analyze, and replicate the patterns behind your highest-performing email copy. Turn individual campaign wins into repeatable copy frameworks your team can deploy across every campaign.

Why use Winning Copy Extraction on TypingMind?

Because you install it once and use it with any model. Winning Copy Extraction is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Winning Copy Extraction in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kenny589/gtm-flywheel/tree/main/campaign-analytics/winning-copy-extraction. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Winning Copy Extraction?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Winning Copy Extraction?

As many as you like. As long as a model supports skills, you can use Winning Copy Extraction with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Winning Copy Extraction AI skill free?

Yes. It is published on GitHub by kenny589 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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