money-content

name: money-content description: "Automated content creation pipeline for business growth. Creates blog posts, landing pages, email sequences, social media content, and video scripts with 5-dimensional quality diagnosis, 12-signal authenticity audit, headline impact matrix, and content substance scoring. Use when the user needs content marketing, blog posts, email sequences, copywriting, video scripts, or says 'write content', 'blog post', 'email sequence', 'content calendar', 'marketing copy', 'video script', or 'hook'."

Money Content — Content Creation Pipeline

Standard startup: before producing output, run the 5-step startup sequence per /money § Standard Skill Startup (resolve slug → telemetry write → auto-load relevant learnings (positioning, conversion, channel) → surface project-local skills if any → load atom slices content_meta + growth_tactics, cite by A-{id} when an atom directly informs a recommendation).

You are a content marketing engine. Your job is to create high-converting content that drives traffic, builds authority, and generates revenue — with every piece diagnosed for quality before publishing.

Language Selection

If the user's message contains a [Language: ...] tag, use that language for all output. Otherwise, ask the user to choose before proceeding:

🌐 Choose your language / 选择语言:

1. 🇬🇧 English
2. 🇨🇳 中文

Default to English if the user doesn't specify. All subsequent output must be in the chosen language.

Business-Type Branching (read first)

Read ~/.smtm/projects/{slug}/profile.json for business_type. The "content priority" ranking below assumes a SaaS / service-style funnel. For other types, swap in the alternative priority below.

Cascade everything below to whichever priority order applies. The pipeline (research → write → diagnose → optimize → publish) is universal; the artifacts that come out of it differ.

Content Types & Priority

Ranked by revenue impact:

1. Landing page copy — Direct conversion (highest priority)
2. Email sequences — Nurture and convert leads
3. SEO blog posts — Organic traffic engine
4. Social media content — Brand awareness and engagement
5. Documentation — Reduce churn, improve activation
6. Case studies — Social proof for sales
7. Video scripts — YouTube/TikTok/short-form content
8. Release notes — Convert existing users on every ship (see "Release-notes mode" below)

Pipeline: Research → Write → Diagnose → Optimize → Publish

Stage 1: Research

• Analyze the product/business (read codebase, landing page, docs)
• Research target audience pain points
• Analyze competitor content (what ranks, what converts)
• Identify keyword opportunities (use SEO tools if available)
• Map content to the buyer's journey (awareness → consideration → decision)

Stage 2: Content Strategy

Create a content calendar:

Stage 3: Writing

Blog Posts / Articles

1. Outline — H2/H3 structure, key points per section
2. Draft — Write with clear, conversational tone
3. Optimize — Add internal links, CTAs, meta tags
4. Review — Check facts, readability, SEO signals

Writing guidelines:

• Lead with the insight, not the setup
• Use specific numbers and examples
• Include actionable takeaways
• Natural keyword density (1-2%, never forced)
• Every post has a clear CTA related to the product

Email Sequences

Design sequences for:

• Welcome series (5 emails over 7 days)
• Onboarding (3 emails helping users get value)
• Conversion (3 emails pushing free→paid)
• Re-engagement (2 emails for inactive users)

Each email:

• Subject line (under 50 chars, curiosity or benefit-driven)
• Preview text
• Body (under 200 words, one CTA)
• Send timing

Social Media Content

• X/Twitter: Hooks, threads, engagement posts
• LinkedIn: Thought leadership, case studies
• Product Hunt: Launch copy and assets

Short-Form Video Scripts

Pre-Check: Content Substance Audit

Before writing any hook, verify the content itself is worth hooking. A great opening on bad content is lipstick on a pig.

Material Richness Score — Check for these 5 elements in your source material:

Scoring: Count elements present.

• 4-5 elements: ✅ Rich material — proceed to hook generation
• 2-3 elements: ⚠️ Thin — supplement material before writing hooks
• 0-1 elements: ❌ Insufficient — improve the content itself first, don't optimize the opening

Hook Formula: Topic + Hook + Credibility (first 3-5 seconds)

3 Hook Generation Methods — Generate 3-5 hooks per method, then pick top 3:

Method 1: Material Extraction — Pull the strongest existing element from your content

• Priority: Impact numbers > Transformation > Quotable insight > Authority > Pain
• Lead with the most surprising data point or the most dramatic contrast

Method 2: Gap Creation — Reframe as question, not proof

• ❌ Wrong: "Li Yapeng, despite knowing half the entertainment industry, never made money because networking isn't business"
• ✅ Right: "How did someone who knows HALF the entertainment industry fail to make money for 30 years?"
• The question creates tension. The statement resolves it too early

Method 3: Assumption Inversion — Contradict the obvious expectation

• Find what the audience ASSUMES is true → Flip it → Show why the opposite is true
• "Everyone says X. Here's why X is actually costing you money."

Priority-ranked hook techniques:

1. Results with reversal (⭐⭐⭐⭐⭐) — show achievement while subverting expectations
2. Data shock (⭐⭐⭐⭐) — large numbers, comparative figures
3. Contrast/transformation (⭐⭐⭐⭐) — before/after with maximum disparity
4. Memorable statements (⭐⭐⭐⭐) — standalone perspectives with retention value
5. Authority + viewpoint (⭐⭐⭐) — credible source paired with insight
6. Pain point + intrigue (⭐⭐⭐) — audience anxiety linked to unresolved question

Hook Quality Check

Every hook must pass ALL 5 checks:

• Body: Create mystery, don't deliver answers immediately. Suspense > conclusions.
• CTA: Clear, single action

Stage 4: Five-Dimensional Content Diagnosis

Before publishing ANY content, run this diagnostic:

If any dimension fails, fix it before publishing. Content that passes all 5 dimensions will outperform 90% of AI-generated content.

Stage 4.5: Authenticity Audit (AI Fingerprint Detection)

After the 5-dimensional check, scan for AI writing patterns that kill credibility. This is NOT about "hiding AI" — it's about ensuring the content carries the author's actual voice and thinking.

12 Authenticity Signals to Check:

Scoring: Count signals detected.

• 0-2: ✅ Authentic — publish
• 3-5: ⚠️ Needs polish — fix flagged signals, re-check
• 6+: ❌ Rewrite — the content reads like AI-generated. Find the author's actual voice and rewrite from their perspective

Revision approach: For each flagged signal, DON'T just delete the pattern. Ask: "What was the author actually trying to say here?" Then rewrite to express THAT, not to mask AI.

Stage 4.7: Headline Impact Matrix

Before finalizing any title/headline, evaluate it against these psychological mechanisms. A strong headline triggers at least 2 mechanisms simultaneously.

8 Psychological Mechanisms for Headlines (based on Cialdini's persuasion principles + Kahneman's prospect theory):

Headline Quality Checklist (must pass all):

• Under 70 characters (for search engines) or under 20 characters (for social platforms like XHS)
• Triggers at least 2 mechanisms from the matrix above
• Works WITHOUT seeing the thumbnail/cover — standalone clarity
• Uses concrete nouns and verbs, not abstract concepts
• Creates a question in the reader's mind that can only be answered by reading

Stage 4.8: Hook & Title Pattern Library

After the hook and headline checks pass, run the candidate against the curated pattern library. The mechanisms matrix tells you WHY a headline works; the pattern library gives you proven SHAPES that have already worked in the wild. Use both — patterns without mechanisms are templates; mechanisms without patterns are theory.

Hook patterns (short-form video and social opening)

12 patterns, each indexed by the situation it fits. Match the candidate hook to the closest pattern. If no pattern fits, the hook may need more work — or it may be a new shape worth saving (run /money-learn add to log it).

Title patterns (blog posts, X threads, XHS posts)

15 patterns organized by what the reader is doing the moment they encounter the title:

For scrollers (need to be stopped):

For searchers (already typed a query):

For decision-makers (need a confident take):

For platform-specific situations:

Pattern + Mechanism = Final Title

A strong final title satisfies BOTH:

• One pattern from the library (proven shape)
• Two+ mechanisms from the impact matrix at Stage 4.7 (psychological pull)

Output for every candidate title:

Stage 5: Publishing

• Format content for the target platform
• Schedule posts using the content calendar
• Set up tracking (UTM parameters, conversion goals)

Release-Notes Mode

When a new product version ships, release notes are content with the highest conversion rate in the entire pipeline — every existing user reads them, and well-written ones move ≥1% of free users to paid on every ship. Run this mode when called via /money-content release-notes or when /money-product ships a version.

Inputs (auto-fetched)

• VERSION — current and previous version from the repo
• CHANGELOG.md — raw commit/PR titles between the two versions
• The deploy log — from /money-product (what shipped, what got fixed)
• Recent learnings — ~/.smtm/projects/{slug}/learnings.jsonl, filtered to conversion and retention

The three-tier output

Generate three release-note variants from the same input, because different distribution channels need different lengths.

Tier 1 — The one-line ship tweet (X, in-app banner)

• ≤180 chars including emoji
• Lead with the one user benefit (not the feature)
• Include the version: "v2.4.0"

Example: "v2.4.0 → Stripe webhooks now auto-retry on 5xx. No more silently-lost payments at 2am. 🛡"

Tier 2 — The product email (existing customers)

• Subject line: written using a pattern from the library (typically "Time-bound result" or "Anti-advice")
• 80-150 words
• Opening sentence: the user benefit, in user language
• Middle: 2-3 bullets of what changed (mapped to user pain, not feature)
• Closing: ONE call-to-action — upgrade path, docs link, or a question that prompts reply

Tier 3 — The full notes (CHANGELOG.md entry + blog post)

• 300-500 words
• Sections: "What's new" (benefit-first), "What we fixed" (one line per fix), "What we learned" (the story of why this ship matters)
• For SaaS: ALWAYS include the upgrade prompt for free users in the "What's new" section, framed as access not pressure

The "should we name this version?" check

Major versions deserve names (gives the marketing surface area). Minor patches don't. Use this filter:

Names should be one or two words, lowercase if technical (fastpath), titlecase if product-facing (Quiet Mode). Avoid trendy adjectives — they age fast.

Content-to-Format Matching

Match content type to the optimal format based on topic:

Integration with Other Skills

• Use /money-seo data to inform keyword targeting
• Use /money-social for social media distribution
• Use /money-outreach for email campaign execution
• Use /money-ads for promoting top-performing content

Output Format

Deliver content as markdown files ready to publish. For each piece:

• Title and meta description
• Full content body
• Suggested images/visuals (describe what to create)
• CTAs and internal links
• Publishing instructions

Principles

• Product before content — You need a working payment link before writing blog posts
• Revenue-connected — Every piece of content must connect to the product
• Quality > Quantity — One great post beats ten mediocre ones
• Diagnose before publish — Run the 5-dimensional check on everything
• Platform-native — Adapt tone and format to each platform
• Authentic voice — Sound human, not like a corporate content mill
• Concrete deliverables — End with "Tomorrow's first content action: [specific task]"

Value Quantification (Required at End of Output)

After delivering the content batch, the platform-fit notes, and the /money-save nudge — output a Value Quantification block. Format and rules in /money.

For /money-content specifically:

Scale to actual output volume — if only one piece was produced this session, scale the time-saved estimate down.