Analyze A/B test results for statistical significance with ship, extend, or kill recommendations
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Extract and codify brand voice from existing content for consistent messaging
中文简介正在准备中。当前显示原文说明。
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Extracts the agency's brand voice from existing content samples, codifies it into a reusable voice guide, and generates config updates for agency.config.json. The output ensures consistent tone across all outreach channels: cold emails, LinkedIn messages, Instagram DMs, proposals, and website copy.
agency.config.json in the project rootagency.config.json from the project root.outreach.tone -- the current tone setting (e.g., "professional-friendly").outreach.banned_phrases -- phrases already flagged as off-limits.agency_name and services[].name for context.CURRENT VOICE CONFIG:
Tone: [tone value]
Banned phrases: [list]
Ready to analyze your content samples to build a complete voice guide.
Ask the user for 3-5 pieces of existing content. Prioritize content that performed well:
I need 3-5 samples of your best content. Prioritize:
1. A cold email that got a reply (paste the full email)
2. A LinkedIn post that got good engagement (paste the text)
3. A proposal intro or cover letter (paste the opening section)
4. Website copy (paste homepage or about page text)
5. An Instagram caption or DM that worked (paste the text)
The more variety, the better. Paste them in any order.
For each sample, tag:
Across all samples, analyze:
Sentence structure:
Vocabulary level:
Humor and personality:
Pronoun analysis:
Power words inventory:
Emotional register:
Opening patterns:
CTA patterns:
BRAND VOICE GUIDE: [Agency Name]
===
VOICE IN 3 WORDS: [word], [word], [word]
Example: "Direct, Helpful, Expert" or "Warm, Data-Driven, Bold"
---
WE ARE:
1. [attribute] -- [one-sentence example of how this shows up in writing]
2. [attribute] -- [example]
3. [attribute] -- [example]
4. [attribute] -- [example]
5. [attribute] -- [example]
WE ARE NOT:
1. [anti-attribute] -- [what to avoid]
2. [anti-attribute] -- [what to avoid]
3. [anti-attribute] -- [what to avoid]
4. [anti-attribute] -- [what to avoid]
5. [anti-attribute] -- [what to avoid]
---
TONE SPECTRUM:
Formal ---|---[X]------- Casual
Serious --|------[X]---- Playful
Technical -|--[X]-------- Simple
Reserved --|-------[X]--- Bold
Corporate -|--------[X]-- Personal
(X marks where the agency falls on each spectrum)
---
VOCABULARY:
ALWAYS USE:
- [word/phrase] -- [why it fits the voice]
- [word/phrase] -- [why]
- [word/phrase] -- [why]
- [word/phrase] -- [why]
- [word/phrase] -- [why]
NEVER USE:
- [word/phrase] -- [why it clashes]
- [word/phrase] -- [why]
- [word/phrase] -- [why]
- [word/phrase] -- [why]
- [word/phrase] -- [why]
(Include existing banned_phrases + newly identified ones)
---
SENTENCE PATTERNS:
Structure rules:
- [rule derived from analysis, e.g., "Lead with value, not credentials"]
- [rule, e.g., "Max 2 sentences before a line break in emails"]
- [rule, e.g., "Use questions to open, not statements"]
- [rule, e.g., "One idea per paragraph"]
Opening formulas (by performance):
1. [pattern] -- used in [sample], got [result]
2. [pattern] -- used in [sample], got [result]
CTA formulas (by performance):
1. [pattern] -- used in [sample], got [result]
2. [pattern] -- used in [sample], got [result]
---
BY CHANNEL:
Email:
- Tone adjustment: [how voice shifts for cold email]
- Max length: [words]
- Structure: [e.g., "hook -> pain -> proof -> CTA"]
- Signature style: [formal/casual]
LinkedIn:
- Tone adjustment: [how voice shifts for LinkedIn]
- Post format: [short-form, carousel narration, long-form]
- Connection note style: [approach]
- Comment style: [approach]
Instagram:
- Tone adjustment: [how voice shifts for IG]
- Caption style: [length, emoji usage, hashtag approach]
- DM style: [casual vs professional]
Proposals:
- Tone adjustment: [how voice shifts for proposals]
- Formality level: [higher/same/lower than email]
- Structure markers: [headers, bullets, data presentation]
Produce updated config values for agency.config.json:
{
"outreach": {
"tone": "[2-3 word tone description derived from analysis]",
"banned_phrases": [
"existing_banned_1",
"existing_banned_2",
"newly_identified_1",
"newly_identified_2",
"newly_identified_3"
],
"voice_attributes": [
"attribute_1",
"attribute_2",
"attribute_3"
],
"preferred_words": [
"word_1",
"word_2",
"word_3"
],
"sentence_max_length": 20,
"paragraph_max_sentences": 2,
"pronoun_target": {
"you_ratio": 0.5,
"we_ratio": 0.3,
"i_ratio": 0.2
}
}
}
Present the diff between current and proposed config.
Return the complete brand voice package:
agency.config.jsonVOICE CHEAT SHEET: [Agency Name]
Voice: [3 words]
Open with: [formula]
Close with: [formula]
Always: [top rule]
Never: [top anti-rule]
message-generator templates to reflect voice guidebrand-voice quarterly or after significant pivotIf the user confirms, write the config updates directly into agency.config.json.
Trigger phrases:
User: Define our brand voice
Assistant: [asks for content samples, analyzes patterns, builds voice guide, generates config updates]
User: Our cold emails sound too formal compared to our LinkedIn posts. Fix the voice.
Assistant: [analyzes both channels, identifies inconsistencies, updates voice guide with channel-specific adjustments]
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中文简介正在准备中。当前显示原文说明。