Content Distribution SOP

Step 1: Receive Source Content

Take the source content (blog post, article, tutorial, etc.) and identify:

• Core message: the single main takeaway in one sentence
• Key insights: 5-8 distinct points or data points worth highlighting
• Target audience: who this is for (same audience, different platform behavior)
• Links: all URLs that need UTM tracking added

If source content doesn't exist yet, STOP and invoke content-create first.

Step 2: Adapt for Each Platform

NEVER copy-paste the same content across platforms. Each adaptation must feel native to its platform.

Dev.to / Hashnode

• Add canonical_url pointing to the original blog post (critical for SEO)
• Reformat code blocks to use platform syntax highlighting (triple backticks with language)
• Add a series tag if part of a content series
• Add 3-5 relevant tags from the platform's tag list
• Include a brief author bio at the end with one relevant link
• Use Playwright MCP to navigate to the editor, fill fields, and publish

Medium

• Import using Medium's import tool (preserves formatting) OR reformat manually
• Set canonical URL to original post
• Add to relevant Medium publication if available
• Select 3-5 topic tags
• Use Playwright MCP to publish via the web editor

Twitter/X Thread

• Extract 5-8 key insights as a numbered thread
• Tweet 1: hook — the most surprising or contrarian point (no links)
• Tweets 2-N: one insight per tweet, concrete and specific
• Final tweet: summary + link to full article with UTM
• Each tweet must stand alone — valuable even without context
• Use Playwright MCP to post the thread

LinkedIn

• Rewrite as a professional reflection with a personal angle
• Open with a hook line (question or bold statement)
• Use short paragraphs (1-2 sentences each) — LinkedIn mobile formatting
• End with a question to drive comments
• Add link to full article in first comment, NOT in the post body (LinkedIn suppresses posts with links)
• Use Playwright MCP to post

Reddit

• NEVER automate posting. Draft content only; user posts manually.
• Identify 2-3 relevant subreddits by searching for related discussions
• Read each subreddit's rules before drafting — some ban self-promotion entirely
• Write as an answer to a question that already exists in the subreddit
• Format: helpful context first, link to article only if the subreddit allows it
• Output: draft text + target subreddit + relevant existing thread (if replying)

Hacker News

• NEVER automate. User must submit manually.
• Only submit if it's a Show HN with a working product or genuinely novel technical content
• Write a factual, non-promotional title (no superlatives, no marketing language)
• Output: suggested title + URL to submit

Step 3: Platform Rules Compliance

Automation permissions:

For any platform not listed: default to manual posting (draft only).

Step 4: UTM Tracking

Add UTM parameters to ALL links back to owned properties:

?utm_source={platform}&utm_medium=social&utm_campaign={content-slug}

Examples:

• ?utm_source=devto&utm_medium=social&utm_campaign=how-to-deploy-nextjs
• ?utm_source=twitter&utm_medium=social&utm_campaign=how-to-deploy-nextjs
• ?utm_source=linkedin&utm_medium=social&utm_campaign=how-to-deploy-nextjs

Never use UTM on links to third-party sites — only on links to YOUR properties.

Step 5: Stagger Publishing Schedule

Do NOT publish everywhere simultaneously. Stagger over 3-5 days:

Adjust based on audience and time zones. Post during each platform's peak hours.

Step 6: Track Performance

After publishing on each platform, store in auto memory (memory/content_log.md):

• Platform name
• Published URL
• Date and time published
• Views (check at 24h, 72h, 7d)
• Engagement (likes, comments, shares, upvotes)
• Click-throughs (from UTM data in analytics)
• Conversions (signups, trials, purchases attributed)

Step 7: Post-Distribution Review

After 7 days, review performance across all platforms:

• Which platform drove the most traffic?
• Which platform drove the most conversions (not just views)?
• What was the engagement rate (engagement / views) per platform?
• Were there comments or questions that suggest follow-up content?
• Update auto memory (memory/content_log.md) with findings to inform future distribution decisions.

Next Steps

Report to user: "Distributed to [N] platforms. URLs: [list]"

Suggested next steps (user decides):

• Distributed → "Run growth-track to measure performance"
• Need deeper engagement → "Run community-engage"