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Oct 19, 2025 8 tweets 7 min read Read on X
everyone's arguing about whether ChatGPT or Claude is "smarter."

nobody noticed Anthropic just dropped something that makes the model debate irrelevant.

it's called Skills. and it's the first AI feature that actually solves the problem everyone complains about:

"why do I have to explain the same thing to AI every single time?"

here's what's different:

- you know how you've explained your brand guidelines to ChatGPT 47 times?
- or how you keep telling it "structure reports like this" over and over?
- or how every new chat means re-uploading context and re-explaining your process?

Skills ends that cycle.

you teach Claude your workflow once.

it applies it automatically. everywhere. forever.

but the real story isn't memory. it's how this changes what's possible with AI at work.Image
here's the technical unlock that makes this actually work:

Skills use "progressive disclosure" instead of dumping everything into context.

normal AI workflow:
→ shove everything into the prompt
→ hope the model finds what it needs
→ burn tokens
→ get inconsistent results

Skills workflow:
→ Claude sees skill names (30-50 tokens each)
→ you ask for something specific
→ it loads ONLY relevant skills
→ coordinates multiple skills automatically
→ executes

example: you ask for a quarterly investor deck

Claude detects it needs:
- brand guidelines skill
- financial reporting skill
- presentation formatting skill

loads all three. coordinates them. outputs a deck that's on-brand, accurate, and properly formatted.

you didn't specify which skills to use.
you didn't explain how they work together.
Claude figured it out.

this is why it scales where prompting doesn't.Image
let me show you what this looks like in real workflows.

Scenario 1: Brand-Consistent Content (Marketing Team)

❌ old way:
- designer makes deck
- brand team reviews: "wrong fonts, logo placement off, colors don't match"
- designer fixes
- brand team reviews again: "footer format is wrong"
- 3 rounds, 4 hours wasted

✅ Skills way:
create "Brand_Guidelines" skill with:

• color codes (#FF6B35 coral, #004E89 navy)
• font rules (Montserrat headers, Open Sans body)
• logo placement rules (0.5" minimum spacing)
• template files

prompt: "create 10-slide deck for Q4 product launch"

- Claude auto-applies brand skill
- output matches guidelines first try
- 30 seconds instead of 4 hours

Rakuten (Japanese e-commerce giant) is already doing this.

finance workflows that took a full day? now 1 hour.Image
Scenario 2: Sales Workflow Automation (Revenue Team)

the repetitive nightmare:
- new lead comes in
- manually create CRM contact
- fill in 12 fields following "the naming convention"
- update opportunity stage
- log activity notes in specific format
- set follow-up reminder
- 8 minutes per lead × 30 leads/week = 4 hours gone

Skills implementation:
create "CRM_Automation" skill that knows:
- your naming conventions (FirstName_LastName_Company format)
- required fields and validation rules
- opportunity stages and when to use them
- note formatting structure
- follow-up timing rules

now: paste lead info → Claude structures everything correctly → done

time per lead: 30 seconds
weekly savings: 3.75 hours
monthly savings: 15 hours (almost 2 full workdays)

at $50/hour, that's $750/month saved per sales rep.
team of 10 reps? $90k/year in recovered time.

youtu.be/kS1MJFZWMq4
Scenario 3: Legal Contract Review (In-House Counsel)

the manual process:
- receive vendor contract
- review against standard terms checklist (24 items)
- identify deviations and risks
- draft redline suggestions
- write internal memo
- 45-60 minutes per contract

Skills setup:
create "Contract_Review" skill containing:
- your standard terms library
- risk classification framework
- approved clause variations
- redline language templates
- memo format structure

execution:
upload contract PDF
prompt: "review this against our standard terms"

Claude outputs:
• flagged risky clauses with severity ratings
• suggested protective language
• formatted redline document
• internal memo for stakeholders

time: 8 minutes instead of 60 minutes

for teams reviewing 50+ contracts/month:
→ saves 43 hours monthly
→ $8,600/month at $200/hour legal rates
→ $103k annually

that's a junior attorney's salary in recovered partner time.
ok but how do you actually BUILD one?

for one, you can simply prompt claude: "create a [name of skill] skill, ask me all the necessary questions for context."

you can also create it manually. here's the exact structure of a SKILL.md file:

1/ YAML Frontmatter (metadata):
---
name: Brand Guidelines
description: Apply Acme Corp brand guidelines to presentations and documents
version: 1.0.0
---

this is what Claude reads first to decide IF it should load your skill.

keep description specific (200 char max) or Claude won't know when to use it.

2/ Markdown Body (the actual instructions)

---
## Overview
This Skill provides Acme Corp's official brand guidelines.
Apply these standards to ensure all outputs match our visual identity.

## Brand Colors
- Primary: #FF6B35 (Coral)
- Secondary: #004E89 (Navy Blue)
- Accent: #F7B801 (Gold)

## Typography
Headers: Montserrat Bold
Body text: Open Sans Regular
Size guidelines:
- H1: 32pt
- H2: 24pt
- Body: 11pt

## Logo Usage
Always use full-color logo on light backgrounds.
White logo on dark backgrounds.
Minimum spacing: 0.5 inches around logo.

## When to Apply
Apply these guidelines when creating:
- PowerPoint presentations
- Word documents for external sharing
- Marketing materials

## Resources
See resources/ folder for logo files and fonts.
---

the markdown body is where Claude gets the DETAILS.
it only reads this after deciding the skill is relevant.

this two-level system (metadata → full content) is why Skills scale without burning tokens.Image
now package it correctly (this trips everyone up):

Step 1: Create folder structure

---
Brand_Guidelines/
├── SKILL.md (contains the YAML + markdown body above)
└── resources/
├── logo.png
└── fonts/
---

Step 2: ZIP it properly
✅ CORRECT structure:
---
Brand_Guidelines.zip
└── Brand_Guidelines/
├── SKILL.md
└── resources/
---

❌ WRONG structure:
---
Brand_Guidelines.zip
├── SKILL.md (loose in root)
└── resources/
---

the FOLDER must be inside the zip, not files directly.

Mac: right-click folder → "Compress" Windows: right-click folder → "Send to" → "Compressed folder"

Step 3: Upload to Claude
Settings → Capabilities → enable "Code execution"
upload your .zip under Skills

test with: "create a presentation following brand guidelines"

pro tip: use the "skill-creator" skill just say "help me create a brand guidelines skill" and Claude interviews you, generates the folder structure, and formats everything automatically.

the companies dominating with AI aren't using better prompts.

they're building systems that codify how they work.

explore real examples you can clone: github.com/anthropics/ski…Image
Claude made simple: grab my free guide

→ Learn fast with mini-course
→ 10+ prompts included
→ Practical use cases

Start here ↓
godofprompt.ai/claude-mastery…

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More from @godofprompt

Feb 10
I've written 500 articles, 23 whitepapers, and 3 ebooks using Claude over 2 years, and these 10 prompts are the ONLY ones I actually use anymore because they handle 90% of professional writing better than any human editor I've worked with and cost me $0.02 per 1000 words: 👇 Image
1. The 5-Minute First Draft

Prompt:

"Turn these rough notes into an article:

[paste your brain dump]

Target length: [800/1500/3000] words
Audience: [describe reader]
Goal: [inform/persuade/teach]

Keep my ideas and examples. Fix structure and flow."
2. Headline Machine (Steal This)

Prompt:

"Topic: [your topic]

Write 20 headlines using these formulas:
- How to [benefit] without [pain point]
- [Number] ways [audience] can [outcome]
- The [adjective] guide to [topic]
- Why [common belief] is wrong about [topic]
- [Do something] like [authority figure]
- I [did thing] and here's what happened
- What [success case] knows about [topic] that you don't

Rank top 3 by click-through potential."
Read 13 tweets
Feb 9
RIP "act as an expert" and basic prompting.

A former OpenAI engineer just exposed "Prompt Contract" - the internal technique that makes LLMs actually obey you.

Works on ChatGPT, Claude, Gemini, everything.

Here's how to use it right now: Image
Here's why your prompts suck:

You: "Write a professional email"
AI: *writes generic corporate bullshit*

You: "Be more creative"
AI: *adds exclamation marks*

You're giving vibes, not instructions.

The AI is guessing what you want. Guessing = garbage output. Image
Prompt Contracts change everything.

Instead of "write X," you define 4 things:

1. Goal (exact success metric)
2. Constraints (hard boundaries)
3. Output format (specific structure)
4. Failure conditions (what breaks it)

Think legal contract, not creative brief. Image
Read 14 tweets
Feb 6
Claude Opus 4.6 is a monster.

I just used it for:

- automating marketing tasks
- building full websites and apps
- writing viral X threads, LinkedIn posts, and YouTube scripts

And it did all this in minutes.

Here are 10 prompts you can steal to unlock its full potential: Image
1. THE CAMPAIGN STRATEGIST

Opus 4.6's 200K context window means it remembers your entire brand voice across all campaigns.

Prompt:

"You are my senior marketing strategist with 10 years of experience in [your industry]. First, analyze my brand voice by reviewing these materials: [paste 3-5 previous posts, your about page, and any brand guidelines].

Then create a comprehensive 30-day content calendar that includes: daily post ideas with specific angles, optimal posting times based on my audience timezone [specify timezone], platform-specific adaptations (Twitter, LinkedIn, Instagram), CTAs tailored to each post's goal, and content themes organized by week.

For the top 5 highest-potential posts, create A/B test variations testing different: hooks, CTAs, content formats (thread vs single post vs carousel), and emotional angles. Include your reasoning for why each variation might outperform.

Finally, identify 3 content gaps my competitors are filling that I'm currently missing."

Opus maintains perfect consistency across 200K tokens. Other models lose your voice after 3-4 posts.Image
2. THE SPY MACHINE

Opus 4.6 processes competitor data 3x faster than GPT-4 and catches patterns humans miss.

Prompt:

"Act as a competitive intelligence analyst. I need you to reverse-engineer my competitors' entire marketing strategy.

Analyze these 10 competitor assets: [paste competitor landing pages, ad copy, email sequences, social posts, or URLs].

For each competitor, extract and document:
1. Core value proposition and positioning angle
2. Specific CTAs used and where they're placed
3. Social proof tactics (testimonials, logos, stats, case studies)
4. Pricing psychology (anchoring, tiering, urgency tactics)
5. Content strategy patterns (topics, frequency, formats)
6. Unique differentiators they emphasize

Then give me:

- 5 strategies they're ALL using that I'm missing (ranked by potential revenue impact)
- 3 positioning gaps in the market none of them are addressing
- 2 specific weaknesses in their approach I can exploit
- 1 bold contrarian strategy that goes against what everyone's doing

Present findings in a strategic brief format with implementation difficulty and expected timeline for each tactic."

Opus reads entire competitor websites in one shot. No "context too long" errors.Image
Read 13 tweets
Feb 6
Stop telling LLMs like Claude and ChatGPT what to do.

Start asking them questions instead.

I replaced all my instruction prompts with question prompts.

Output quality: 6.2/10 → 9.1/10

This is called "Socratic prompting" and here's how it works: Image
Most people prompt like this:

"Write a blog post about AI productivity tools"
"Create a marketing strategy for my SaaS"
"Analyze this data and give me insights"

LLMs treat these like tasks to complete.
They optimize for speed, not depth.

You get surface-level garbage.
Socratic prompting flips this.

Instead of telling the AI what to produce, you ask questions that force it to think through the problem.

LLMs are trained on billions of reasoning examples.
Questions activate that reasoning mode.

Instructions don't.
Read 13 tweets
Feb 5
I reverse-engineered the actual prompting frameworks that top AI labs use internally.

Not the fluff you see on Twitter.

The real shit that turns vague inputs into precise, structured outputs.

Spent 3 weeks reading OpenAI's model cards, Anthropic's constitutional AI papers, and leaked internal prompt libraries.

Here's what actually moves the needle:Image
Framework 1: Constitutional Constraints (Anthropic's secret sauce)

Don't just say "be helpful."

Define explicit boundaries BEFORE the task:

"You must: [X]
You must not: [Y]
If conflicted: [Z]"

Claude uses this internally for every single request.

It's why Claude feels more "principled" than other models.Image
Framework 2: Structured Output Schemas (OpenAI's internal standard)

Stop asking for "a summary."

Define the exact structure:

"Return JSON:
{
"main_point": string,
"evidence": array[3],
"confidence": 0-100
}"

GPT-5 function calling was built for this.

You're just not using it.Image
Read 13 tweets
Feb 3
ChatGPT's custom instructions feature is insanely powerful.

But 99% of people write garbage instructions.

I tested 200+ custom instruction sets.

These 5 patterns increased output quality by 3.4x: Image
PATTERN 1: Tell ChatGPT what NOT to do

Bad: "Be concise"

Good: "Never use: delve, landscape, robust, utilize, leverage, it's important to note, in conclusion"

Why it works: Negative instructions are specific. Positive instructions are vague.

Output quality jumped 2.1x with this alone.Image
Image
PATTERN 2: Context over identity

Bad: "I'm a software engineer"

Good: "I build B2B SaaS with React, Node.js, PostgreSQL. My audience is technical founders who need production-ready code, not tutorials."

Same prompt. 10x better output.

The difference? AI knows your environment.Image
Image
Read 10 tweets

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