content-engine
affaan-m/everything-claude-code
Create platform-native content for X, LinkedIn, TikTok, YouTube, and newsletters from source material without generic fluff.
What is content-engine?
Adapts source material into platform-specific content while preserving the author's real voice. Use when you need social posts, threads, video scripts, content calendars, or multi-platform campaigns built from articles, demos, docs, or internal notes.
- Converts source material (articles, demos, docs, transcripts) into platform-native posts
- Builds voice profiles to maintain consistency across multiple outputs
- Structures short-form video and YouTube scripts around visual proof points
- Repurposes single assets into atomic claims ranked by sharpness and novelty
- Enforces quality gates: removes hype language, engagement bait, and platform stereotypes
- Generates launch sequences and ongoing content systems around products or narratives
How to install content-engine
npx skills add https://github.com/affaan-m/everything-claude-code --skill content-engineHow to use content-engine
- 1.Identify your source material (articles, demos, docs, transcripts, screenshots, or prior posts)
- 2.If voice consistency matters across outputs, run `brand-voice` first to create a voice profile
- 3.Extract 3–7 atomic claims or scenes from the source material
- 4.Rank claims by sharpness, novelty, and proof
- 5.Request platform-native drafts, assigning one strong idea per platform
- 6.Review drafts against the quality gate: real claims, no hype language, no fake engagement bait, authentic voice
Use cases
- Turning a product demo or changelog into coordinated X thread, LinkedIn post, and YouTube script
- Repurposing a published article into a newsletter, TikTok script, and LinkedIn update
- Building a launch campaign with consistent voice across multiple platforms
- Converting internal notes or podcasts into public-facing content without losing authenticity
- Creating an ongoing content calendar from a single core insight or narrative
- Founders and product leaders launching or promoting products
- Content creators and writers managing multi-platform presence
- Marketing teams building coordinated campaigns
- Technical authors adapting documentation into public content
- Anyone prioritizing authentic voice over platform-optimized generic posts
content-engine FAQ
No. Use it when you have source material to adapt or when voice consistency matters across multiple platforms. For single quick posts, it may be overkill.
Run `brand-voice` first with real examples of your writing. Feed the resulting voice profile to content-engine to maintain consistency across all outputs.
Not recommended. This skill adapts structure and format for each platform while keeping the core claim. Duplicated copy across platforms is flagged in the quality gate unless you explicitly request it.
Published articles, internal memos, product demos, docs, changelogs, transcripts, screenshots, or your prior posts. Start from something concrete, not generic post formulas.
Check the quality gate: Does it sound like the real author, not a platform stereotype? Does it contain a real claim or proof point? Is all generic hype language and fake engagement bait removed?
Full instructions (SKILL.md)
Source of truth, from affaan-m/everything-claude-code.
name: content-engine description: 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. metadata: origin: ECC
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
- Start from source material, not generic post formulas.
- Adapt the format for the platform, not the persona.
- One post should carry one actual claim.
- Specificity beats adjectives.
- 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
- 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
- Pick the anchor asset.
- Extract 3 to 7 atomic claims or scenes.
- Rank them by sharpness, novelty, and proof.
- Assign one strong idea per output.
- Adapt structure for each platform.
- Strip platform-shaped filler.
- 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-voicefor source-derived voice profilescrosspostfor platform-specific distributionx-apifor sourcing recent posts and publishing approved X output
Related skills
More from affaan-m/everything-claude-code and the wider catalog.
security-review
Security checklist and patterns for authentication, input validation, secrets, and sensitive features.
golang-patterns
Idiomatic Go patterns, best practices, and conventions for building robust, efficient, and maintainable applications.
coding-standards
Baseline coding conventions for naming, readability, immutability, and quality across projects.
frontend-patterns
React and Next.js patterns for components, state management, performance, and modern frontend practices.
backend-patterns
REST/GraphQL API design, database optimization, and server-side patterns for Node.js, Express, and Next.js.
golang-testing
Go testing patterns: table-driven tests, subtests, benchmarks, fuzzing, and TDD methodology.