copywriting

name	copywriting
version	1.0.0
description	[Content] Use when you need to create high-converting copy for marketing materials, social media, landing pages, email campaigns, and product descriptions.

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, and channel 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

Channel Guidelines

Channel	Key Rule
Twitter/X	First 140 chars critical. Avoid hashtags. Thread for stories.
LinkedIn	Professional but not boring. Story-driven. First 2 lines hook.
Landing Pages	Hero = promise outcome. Bullets = benefits not features.
Email	Subject = 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

---

[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.

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

Re-read files after context changes. Context compaction, resume, or long-running work can make memory stale; verify current files before acting. Verify generated content against source evidence. AI hallucinates APIs, names, claims, and document facts. Check the relevant source before documenting or referencing. Check downstream references before deleting or renaming. Removing an artifact can stale docs, generated mirrors, configs, and callers; map references first. Trace the full impact chain after edits. Changing a definition can miss derived outputs and consumers. Follow the affected chain before declaring done. Verify ALL affected outputs, not just the first. One green check is not all green checks; validate every output surface the change can affect. Assume existing values are intentional — ask WHY before changing. Before changing a constant, limit, flag, wording, or pattern, read nearby context and history. Surface ambiguity before acting — don't pick silently. Multiple valid interpretations require an explicit question or stated assumption with risk. Keep shared guidance role-relevant. Universal guidance must help every receiving skill or agent; code-specific obligations belong only in code-specific protocols.

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.

MUST ATTENTION apply critical + sequential thinking — every claim needs appropriate traced evidence (file:line for repo/code claims; source URL or artifact section for research, product, content, and docs claims); confidence >80% to act, <60% DO NOT recommend. Anti-hallucination: never present guess as fact, admit uncertainty freely, cross-reference independently, stay skeptical of own confidence.

MUST ATTENTION apply AI mistake prevention — verify generated content against evidence, trace downstream references before deleting or renaming, verify all affected outputs, re-read files after context loss, and surface ambiguity before acting.

Closing Reminders

Protocols in force (concise digest of the SYNC/shared blocks this skill carries):

• AI Mistake Prevention: verify generated content against evidence, trace downstream references, verify all affected outputs, re-read after context loss, surface ambiguity.

• Critical Thinking: traced proof per claim, confidence >80% to act, never guess.

• 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

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.