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content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

content-engine 是什麼?

content-engine is a Claude Code agent skill that create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/content-engine

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說明文件

Content Engine

Build platform-native content without flattening the author's real voice into platform slop.

When to Activate

  • writing X posts or threads
  • drafting LinkedIn posts or launch updates
  • scripting short-form video or YouTube explainers
  • repurposing articles, podcasts, demos, docs, or internal notes into public content
  • building a launch sequence or ongoing content system around a product, insight, or narrative

Non-Negotiables

  1. Start from source material, not generic post formulas.
  2. Adapt the format for the platform, not the persona.
  3. One post should carry one actual claim.
  4. Specificity beats adjectives.
  5. No engagement bait unless the user explicitly asks for it.

Source-First Workflow

Before drafting, identify the source set:

  • published articles
  • notes or internal memos
  • product demos
  • docs or changelogs
  • transcripts
  • screenshots
  • prior posts from the same author

If the user wants a specific voice, build a voice profile from real examples before writing. Use brand-voice as the canonical workflow when voice consistency matters across more than one output.

Voice Handling

brand-voice is the canonical voice layer.

Run it first when:

  • there are multiple downstream outputs
  • the user explicitly cares about writing style
  • the content is launch, outreach, or reputation-sensitive

Reuse the resulting VOICE PROFILE here instead of rebuilding a second voice model. If the user wants Affaan / ECC voice specifically, still treat brand-voice as the source of truth and feed it the best live or source-derived material available.

Hard Bans

Delete and rewrite any of these:

  • "In today's rapidly evolving landscape"
  • "game-changer", "revolutionary", "cutting-edge"
  • "here's why this matters" unless it is followed immediately by something concrete
  • ending with a LinkedIn-style question just to farm replies
  • forced casualness on LinkedIn
  • fake engagement padding that was not present in the source material

Platform Adaptation Rules

X

  • open with the strongest claim, artifact, or tension
  • keep the compression if the source voice is compressed
  • if writing a thread, each post must advance the argument
  • do not pad with context the audience does not need

LinkedIn

  • expand only enough for people outside the immediate niche to follow
  • do not turn it into a fake lesson post unless the source material actually is reflective
  • no corporate inspiration cadence
  • no praise-stacking, no "journey" filler

Short Video

  • script around the visual sequence and proof points
  • first seconds should show the result, problem, or punch
  • do not write narration that sounds better on paper than on screen

YouTube

  • show the result or tension early
  • organize by argument or progression, not filler sections
  • use chaptering only when it helps clarity

Newsletter

  • open with the point, conflict, or artifact
  • do not spend the first paragraph warming up
  • every section needs to add something new

Repurposing Flow

  1. Pick the anchor asset.
  2. Extract 3 to 7 atomic claims or scenes.
  3. Rank them by sharpness, novelty, and proof.
  4. Assign one strong idea per output.
  5. Adapt structure for each platform.
  6. Strip platform-shaped filler.
  7. Run the quality gate.

Deliverables

When asked for a campaign, return:

  • a short voice profile if voice matching matters
  • the core angle
  • platform-native drafts
  • posting order only if it helps execution
  • gaps that must be filled before publishing

Quality Gate

Before delivering:

  • every draft sounds like the intended author, not the platform stereotype
  • every draft contains a real claim, proof point, or concrete observation
  • no generic hype language remains
  • no fake engagement bait remains
  • no duplicated copy across platforms unless requested
  • any CTA is earned and user-approved

Related Skills

  • brand-voice for source-derived voice profiles
  • crosspost for platform-specific distribution
  • x-api for sourcing recent posts and publishing approved X output

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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