EasyPlatform copywriting

[Content] Create high-converting copy for marketing materials, social media, landing pages, email campaigns, and product descriptions. Triggers on: copywriting, marketing copy, social media post, landing page copy, email campaign, product description.

install
source · Clone the upstream repo
git clone https://github.com/duc01226/EasyPlatform
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/duc01226/EasyPlatform "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/copywriting" ~/.claude/skills/duc01226-easyplatform-copywriting && rm -rf "$T"
manifest: .claude/skills/copywriting/SKILL.md
source content

[IMPORTANT] Use

TaskCreate
to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

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Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

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AI Mistake Prevention — Failure modes to avoid on every task:

  • Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal.
  • Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing.
  • Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain.
  • Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path.
  • When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site.
  • Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code.
  • Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks.
  • Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis.
  • Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly.
  • Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.
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Quick Summary

Goal: Create engagement-driven copy that captures attention and drives action.

Workflow:

  1. Context — Read project README + docs to align with business goals and audience
  2. Research — Check competitor copy, trending formats, platform best practices
  3. Write — Lead with hook, use pattern interrupts, end with clear CTA
  4. Deliver — Primary version + 2-3 alternatives + rationale + A/B test suggestions

Key Rules:

  • Brutal honesty over hype — no corporate jargon
  • Specificity wins ("47% increase" beats "boost results")
  • Hook first — first 5 words determine if they read 50
  • Every word must earn its place — read aloud, pass the "so what?" test

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Writing Principles

  1. User-Centric: Write for the reader's benefit, not the brand's ego
  2. Conversational: Write like texting a smart friend, not a press release
  3. Scannable: Headline → Subheadline → Body → CTA. Each layer works standalone.
  4. Evidence-Based: Leverage social proof — numbers, testimonials, case studies

Copy Frameworks

  • AIDA: Attention → Interest → Desire → Action
  • PAS: Problem → Agitate → Solution
  • BAB: Before → After → Bridge
  • 4 Ps: Promise, Picture, Proof, Push

Platform Guidelines

PlatformKey Rule
Twitter/XFirst 140 chars critical. Avoid hashtags. Thread for stories.
LinkedInProfessional but not boring. Story-driven. First 2 lines hook.
Landing PagesHero = promise outcome. Bullets = benefits not features.
EmailSubject = curiosity/urgency. Body = scannable. P.S. = reinforce CTA.

Output Format

  1. Primary Version — Strongest recommendation
  2. Alternative Versions — 2-3 variations testing different angles
  3. Rationale — Why this approach works
  4. A/B Test Suggestions — What to test if running experiments

Closing Reminders

  • MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using
    TaskCreate
    BEFORE starting
  • MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • MANDATORY IMPORTANT MUST ATTENTION cite
    file:line
    evidence for every claim (confidence >80% to act)
  • MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality <!-- SYNC:critical-thinking-mindset:reminder -->
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact. <!-- /SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction. <!-- /SYNC:ai-mistake-prevention:reminder -->