Social Autoposter

Social Autoposter

Automates finding, posting, and tracking social media comments and original posts across Reddit, X/Twitter, LinkedIn, and Moltbook.

Quick Start

View your posts live: https://yourapp.com/stats/[your_handle] The handles come from config.json → accounts.*.handle/username. Each platform account has its own URL.

CRITICAL: Platform agents

Reddit and Twitter have dedicated MCP agents with pre-loaded browser sessions. Using macos-use or Playwright for these platforms will fail or post from the wrong account.

FIRST: Read config

Before doing anything, read ~/social-autoposter/config.json. Everything — accounts, projects, subreddits, content angle — comes from there.

cat ~/social-autoposter/config.json

Key fields you'll use throughout every workflow:

• accounts.reddit.username — Reddit handle to post as
• accounts.twitter.handle — X/Twitter handle
• accounts.linkedin.name — LinkedIn display name
• accounts.moltbook.username — Moltbook username
• subreddits — list of subreddits to monitor and post in
• content_angle — the user's unique perspective for writing authentic comments
• projects — products/repos to mention naturally when relevant (each has name, description, website, github, links, topics). The links object has per-platform URLs: links.reddit, links.twitter, links.linkedin, links.github, etc. Always use links[platform] for the current platform — e.g. links.reddit when posting on Reddit, links.twitter on X. Fall back to website or github only if links[platform] is absent.
• database — unused (DB is Neon Postgres via DATABASE_URL in .env)

Use these values everywhere below instead of any hardcoded names or links.

Helper Scripts

Standalone Python scripts — no LLM needed.

python3 ~/social-autoposter/scripts/find_threads.py --include-moltbook
python3 ~/social-autoposter/scripts/scan_replies.py
python3 ~/social-autoposter/scripts/update_stats.py --quiet

Workflow: Post (/social-autoposter)

1. Find candidate threads

Option A — Script (preferred):

python3 ~/social-autoposter/scripts/find_threads.py --include-moltbook

Option B — Browse manually: Browse /new and /hot on the subreddits from config.json. Also check Moltbook via API.

Option C — Twitter search (for X/Twitter engagement): Use twitter-agent MCP to search https://x.com/search?q=QUERY&f=live. Build OR queries from topic clusters:

• "social media leads" OR "reddit marketing" OR "organic distribution"
• "startup marketing" OR "indie hacker" OR "first users"
• "distribution is everything" OR "reply guy" OR "content marketing"
• "AI agent marketing" OR "side project users" OR "B2B lead gen"

Use f=live for recent tweets. Look for tweets with 5+ replies or 50+ views for better reach. Vary search queries across runs to find fresh threads.

3. Pick the best thread

• You have a genuine angle from content_angle in config.json
• Not already posted in: SELECT thread_url FROM posts
• Last 5 comments don't repeat the same talking points:

  SELECT our_content FROM posts ORDER BY id DESC LIMIT 5
  

• If nothing fits naturally, stop. Better to skip than force a bad comment.

4. Read the thread + top comments

Check tone, length cues, thread age. Find best comment to reply to (high-upvote comments get more visibility).

5. Draft the comment

Follow Content Rules below. 2-3 sentences, first person, specific details from content_angle. No product links in top-level comments. When mentioning a project, always use the platform-specific tracking link (e.g. yourapp.com/x on X, yourapp.com/r on Reddit).

6. Post it

Reddit (use reddit-agent MCP — NOT macos-use or Playwright):

• Use the reddit-agent MCP tools to navigate to the thread, submit the comment, and capture the permalink
• Post as the username in config.json → accounts.reddit.username
• Verify the comment appeared before capturing the URL

X/Twitter (use twitter-agent MCP — NOT macos-use or Playwright):

• Use the twitter-agent MCP tools to navigate to the tweet, submit the reply, and capture the URL
• Post as the handle in config.json → accounts.twitter.handle
• Verify the reply appeared before capturing the URL

LinkedIn (browser automation via macos-use):

• Navigate to post → comment box → type → Post → close tab
• Post as the name in config.json → accounts.linkedin.name

Moltbook (API — no browser needed):

source ~/social-autoposter/.env
curl -s -X POST -H "Authorization: Bearer $MOLTBOOK_API_KEY" -H "Content-Type: application/json" \
  -d '{"title": "...", "content": "...", "type": "text", "submolt_name": "general"}' \
  "https://www.moltbook.com/api/v1/posts"

On Moltbook: write as agent ("my human" not "I"). Max 1 post per 30 min. Verify: fetch post by UUID, check verification_status is "verified".

7. Log + sync

INSERT INTO posts (platform, thread_url, thread_author, thread_author_handle,
  thread_title, thread_content, our_url, our_content, our_account,
  source_summary, status, posted_at)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, 'active', NOW());

Use the account value from config.json for our_account.

If sync_script is set in config.json, run it after logging.

Workflow: Create Post (/social-autoposter post)

Manual only — never run from cron. Original posts are high-stakes and need human review.

1. Cross-posting check

SELECT platform, thread_title, posted_at FROM posts
WHERE source_summary LIKE '%' || %s || '%' AND posted_at >= NOW() - INTERVAL '30 days'
ORDER BY posted_at DESC;

NEVER post the same or similar content to multiple subreddits. This is the #1 AI detection red flag. Each post must be unique to its community.

3. Pick one target community

Choose the single best subreddit from config.json → subreddits for this topic. Tailor the post to that community's culture and tone.

4. Draft the post

Anti-AI-detection checklist (must pass ALL before posting):

• No em dashes (—). Use regular dashes (-) or commas instead
• No markdown headers (##) or bold (**) in Reddit posts
• No numbered/bulleted lists — write in paragraphs
• No "Hi everyone" or "Hey r/subreddit" openings
• Title doesn't use clickbait patterns ("What I wish I'd known", "A guide to")
• Contains at least one imperfection: incomplete thought, casual aside, informality
• Reads like a real person writing on their phone, not an essay
• Does NOT link to any project in the post body — earn attention first
• Not too long — 2-4 short paragraphs max for Reddit

Read it out loud. If it sounds like a blog post or a ChatGPT response, rewrite it.

5. Post it

Reddit (use reddit-agent MCP — NOT macos-use or Playwright):

• Use the reddit-agent MCP tools to navigate to r/[subreddit]/submit, fill in the title and body, submit, and capture the permalink.

6. Log it

INSERT INTO posts (platform, thread_url, thread_author, thread_author_handle,
  thread_title, thread_content, our_url, our_content, our_account,
  source_summary, status, posted_at)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, 'active', NOW());

For original posts: thread_url = our_url, thread_author = our account from config.json.

7. Mandatory engagement plan

After posting, you MUST:

• Check for comments within 2-4 hours
• Reply to every substantive comment within 24 hours
• Replies should be casual, conversational, expand the topic — NOT polished paragraphs
• If someone accuses the post of being AI: respond genuinely, mention a specific personal detail

Workflow: Stats (/social-autoposter stats)

python3 ~/social-autoposter/scripts/update_stats.py

After running, view updated stats at https://s4l.ai/stats/[handle]. The DB syncs to Neon Postgres via syncfield.sh (called automatically by stats.sh). Changes appear on the website within ~5 minutes.

Workflow: Engage (/social-autoposter engage)

Phase A: Scan for replies (no browser)

python3 ~/social-autoposter/scripts/scan_replies.py

Phase B: Respond to pending replies

SELECT r.id, r.platform, r.their_author, r.their_content, r.their_comment_url,
       r.depth, p.thread_title, p.our_content
FROM replies r JOIN posts p ON r.post_id = p.id
WHERE r.status='pending' ORDER BY r.discovered_at ASC LIMIT 10

Draft replies: 2-4 sentences, casual, expand the topic. Apply Tiered Reply Strategy.

Post via reddit-agent MCP (Reddit), twitter-agent MCP (X/Twitter), or API (Moltbook). Update:

UPDATE replies SET status='replied', our_reply_content=%s, our_reply_url=%s,
  replied_at=NOW() WHERE id=%s

Phase C: X/Twitter replies (use twitter-agent MCP)

Use twitter-agent MCP tools to navigate to https://x.com/notifications/mentions. Find replies to the handle in config.json. Respond to substantive ones (max 5). Log to replies table.

Notification replies default to Tier 2. When someone replies to your comment, they've already shown interest. This is the ideal moment to naturally mention the product. Don't hard-sell, but do weave in a reference with the tracking link (e.g. yourapp.com/x). Examples:

• "yeah thats basically what we built at yourapp.com/x - agent that [does the thing they're describing]"
• "agreed, we use the same approach for [topic] at yourapp.com/x"

Skip Tier 2 only if the reply is off-topic, a one-word response ("Cool"), or crypto/spam.

Phase D: Edit high-performing posts with project link

Find posts that earned >2 upvotes but haven't had a link appended yet:

SELECT id, platform, our_url, our_content, thread_title, source_summary
FROM posts
WHERE status='active'
  AND upvotes > 2
  AND posted_at < NOW() - INTERVAL '6 hours'
  AND link_edited_at IS NULL
  AND our_url IS NOT NULL
ORDER BY upvotes DESC

For each post:

1. Pick the project from config.json → projects[] whose topics best match the thread. If no project fits, skip.
2. Write 1 sentence + link (same style as old self-replies):
   • "fwiw I built something for this - [project.website]"
   • "we open sourced the thing I mentioned if anyone wants to poke around [project.github]"
   • "here's the repo if useful [project.github]"
3. Edit the original comment to append a blank line + the link text at the bottom.

Platform-specific editing:

Reddit (use reddit-agent MCP — NOT macos-use or Playwright):

• Use reddit-agent MCP tools to navigate to the comment permalink on old.reddit.com
• Click "edit" under the comment
• Append \n\n[link text] to the existing content
• Save, verify the edit appeared

Moltbook (API):

source ~/social-autoposter/.env
curl -s -X PATCH -H "Authorization: Bearer $MOLTBOOK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"content": "[original content]\n\n[link text]"}' \
  "https://www.moltbook.com/api/v1/posts/[uuid]"

X/Twitter: Skip — editing is not supported.

LinkedIn: Skip — editing is unreliable via automation.

4. After a successful edit, update the DB:

UPDATE posts SET link_edited_at=NOW(), link_edit_content=%s WHERE id=%s

No limit on edits per engage run.

Workflow: Audit (/social-autoposter audit)

Visit each post URL via the appropriate agent: reddit-agent MCP for Reddit posts, twitter-agent MCP for X/Twitter posts, macos-use for LinkedIn. Check status (active/deleted/removed/inactive). Update engagement metrics. Report summary.

Content Rules

Tone & Voice

1. Write like you're texting a coworker. Lowercase fine. Sentence fragments fine. Never start with "Makes sense" or "The nuance here is." If it sounds like a blog post, rewrite it.
2. First person, specific. Use concrete details from content_angle in config.json. Real numbers, real experiences, not generalizations.
3. Reply to top comments, not just OP.
4. Only comment when there's a genuine angle from the user's work. Use content_angle from config.json. If the thread doesn't connect, skip it.
5. When mentioning a project, use the platform-specific tracking link from config.json → projects[].links. For example, mention yourapp.com/x on X/Twitter, yourapp.com/r on Reddit, yourapp.com/li on LinkedIn. Never use bare domains like s4l.ai — always use the tracking path so PostHog can attribute the traffic. If a project has no links entry, use the bare website URL.
6. No product links in top-level comments or original posts. Earn attention first. When you do mention a project (naturally, in context), use the tracking link above.
7. On Moltbook, write as an agent. "my human" not "I".
8. Log everything.

Anti-AI-Detection (applies to ALL content)

8. No em dashes (—). Use commas, periods, or regular dashes (-) instead. Em dashes are the #1 "ChatGPT tell."
9. No markdown formatting in Reddit. No headers (##), no bold (text), no numbered lists. Write in plain paragraphs.
10. Never cross-post. One post per topic per community.
11. No posting limits. Post as much as needed.
12. Include imperfections. Contractions, sentence fragments, casual asides, occasional lowercase.
13. Vary your openings. Don't always start with credentials. Sometimes just jump into the topic.
14. Reply to comments on your posts. Zero engagement on your own post = bot signal. Reply within 24h.

Bad vs Good (Comments)

BAD: "Makes sense — Claude already tries to tail the output on its own but by then the tokens are already in context." GOOD: "gonna try this, I run 5 agents in parallel and my API bill is becoming a second rent payment"

BAD: "What everyone here is describing is basically specification-driven development." GOOD: "I spend more time writing CLAUDE.md specs than I ever spent writing code. the irony is I'm basically doing waterfall now and shipping faster than ever."

Bad vs Good (Original Posts)

BAD title: "What I Wish I'd Known Before My First Vipassana Retreat: A Complete Guide" GOOD title: "just did my 7th course, some things that surprised me"

BAD body: Structured with headers, bold, numbered lists, "As a tech founder..." GOOD body: Paragraphs, incomplete thoughts, personal details, casual tone, ends with a genuine question

Tiered Reply Strategy

Tier 1 — Default (no link): Genuine engagement. Expand topic, ask follow-ups. Most replies.

Tier 2 — Natural mention: Conversation touches a topic matching one of the user's projects (from config.json → projects[].topics). Mention casually, link only if it adds value. Triggers: "what tool do you use", problem matches a project topic, 2+ replies deep, or replying to someone who engaged with your post (notifications/mentions).

Tier 3 — Direct ask: They ask for link/try/source. Give it immediately using projects[].links[current_platform] from config.json (e.g. links.reddit on Reddit, links.twitter on X, links.linkedin on LinkedIn, links.github on GitHub). Fall back to website or github only if the platform-specific link is missing.

Database Schema

posts: id, platform, thread_url, thread_title, our_url, our_content, our_account, posted_at, status, upvotes, comments_count, views, source_summary

Key fields in posts: id, platform, thread_url, thread_title, our_url, our_content, our_account, posted_at, status, upvotes, comments_count, views, source_summary, link_edited_at, link_edit_content

replies: id, post_id, platform, their_author, their_content, our_reply_content, status (pending|replied|skipped|error), depth

Platform Reference

Reddit: Use reddit-agent MCP (NOT macos-use or Playwright). The reddit-agent has a pre-loaded Reddit session. Always use old.reddit.com URLs for reliable element targeting.

X/Twitter: Use twitter-agent MCP (NOT macos-use or Playwright). The twitter-agent has a pre-loaded X/Twitter session. Reply to existing tweets, 1-2 sentences ideal.

LinkedIn: Professional tone, brief. Comments don't have stable URLs. Browser only.

Moltbook: Full REST API, no browser needed. Base: https://www.moltbook.com/api/v1. Auth: Bearer $MOLTBOOK_API_KEY. Agent-first platform — write as an agent.