| name | social-autoposter |
| description | Automate social media posting across Reddit, X/Twitter, LinkedIn, and Moltbook. Find threads, post comments, create original posts, track engagement stats. Use when: 'post to social', 'social autoposter', 'find threads to comment on', 'create a post', 'audit social posts', 'update post stats'. |
| user_invocable | true |
Social Autoposter
Automates finding, posting, and tracking social media comments and original posts across Reddit, X/Twitter, LinkedIn, and Moltbook.
Quick Start
| Command | What it does |
|---|
/social-autoposter | Comment run — find threads + post comment + log (cron-safe) |
/social-autoposter post | Create an original post/thread (manual or cron-driven for Reddit threads) |
/social-autoposter stats | Update engagement stats via API |
/social-autoposter engage | Scan and reply to responses on our posts |
/social-autoposter audit | Full browser audit of all posts |
View your posts live: https://s4l.ai/stats/[your_handle]
— e.g. https://s4l.ai/stats/m13v_ (Twitter handle without @), https://s4l.ai/stats/Deep_Ad1959 (Reddit), https://s4l.ai/stats/matthew-autoposter (Moltbook).
The handles come from config.json → accounts.*.handle/username. Each platform account has its own URL.
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, topics)
database — unused (DB is 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_reddit_replies.py
python3 ~/social-autoposter/scripts/scan_moltbook_replies.py
python3 ~/social-autoposter/scripts/update_stats.py --quiet
Workflow: Post (/social-autoposter)
There is NO posting rate limit. Do not add one, do not enforce one, do not invent one. Post as many times as needed.
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.
2. Pick the best thread
3. Read the thread + top comments
Check tone, length cues, thread age. Find best comment to reply to (high-upvote comments get more visibility).
4. Draft the comment
Follow Content Rules below. 2-3 sentences, first person, specific details from content_angle. No product links in top-level comments.
5. Post it
Reddit (browser automation):
- Navigate to
old.reddit.com thread URL
- Reply box → type comment → submit → wait 2-3s → verify comment appeared → capture permalink → close tab
- Post as the username in
config.json → accounts.reddit.username
X/Twitter (browser automation):
- Navigate to tweet → reply box → type → Reply → verify → capture URL
- Post as the handle in
config.json → accounts.twitter.handle
LinkedIn (browser automation):
- 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").
Verify: fetch post by UUID, check verification_status is "verified".
6. 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, project_name, engagement_style, feedback_report_used, status, posted_at)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, TRUE, 'active', NOW());
Set project_name to the matching project name from config.json (e.g., 'Fazm', 'Cyrano', 'Terminator'). Every post/comment MUST be labeled with its target project. If engagement is general/unrelated to any project, use 'general'.
Set engagement_style to the style you chose for this post (e.g., 'critic', 'storyteller', 'pattern_recognizer', 'curious_probe', 'contrarian', 'data_point_drop', 'snarky_oneliner'). Every post MUST have an engagement_style.
Use the account value from config.json for our_account.
Posts are written directly to the Postgres database. No separate post-sync step is required.
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. Duplicate cross-posts read as spam and get removed. Each post must be unique to its community.
2. 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.
3. Draft the post
Pre-post checklist (must pass ALL before posting):
Read it out loud. If it sounds like a blog post or generic AI copy, rewrite it.
4. Post it
Reddit: old.reddit.com → Submit new text post → paste title + body → submit → verify → capture permalink.
5. 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, project_name, engagement_style, feedback_report_used, status, posted_at)
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, TRUE, 'active', NOW());
Set engagement_style to the style you chose (e.g., 'critic', 'storyteller', 'pattern_recognizer'). Every post MUST have an engagement_style.
Set project_name to the matching project name from config.json. For original posts: thread_url = our_url, thread_author = our account from config.json.
6. 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 asks whether the post is AI or a bot: acknowledge it briefly, do not argue, do not pitch, and prefer disengaging (same policy as the engage pipeline's meta-callout handling)
Workflow: Cron-driven Reddit Threads (run-reddit-threads.sh)
Daily-cadence original Reddit threads across all products, automated via launchd.
Config lives per-project under projects[].threads:
enabled: true/false
own_community: {subreddit, cadence, floor_days} (optional). Defaults to 1-day floor.
external_subreddits: list of external subs (default 3-day floor, override via external_floor_days)
topic_angles: discussion-starter ideas the agent picks from
- Voice guidance comes from
projects[].voice (tone, never)
content_sources.guide_dir / link_base: optional source paths/URLs
dynamic_context.day_counter / static_facts: live-calculated facts injected into the prompt
Source research uses landing_pages.repo + landing_pages.product_source[] (same schema as the SEO pipeline). The agent is told to read README + product source before drafting so posts ground in real details.
Picker (scripts/pick_thread_target.py): weighted project selection with:
- Per-sub floor-days filter (queries
posts table for this account's last original thread)
subreddit_bans filter: banned (can't post or comment) + skip_threads (threads blocked, comments OK)
- Own-community candidates always picked first when eligible
Schedule: com.m13v.social-reddit-threads.plist fires 4x/day at 00:15, 06:15, 12:15, 18:15.
Lock: the runner calls acquire_lock reddit-threads to serialize against the comment pipeline.
Workflow: Stats (/social-autoposter stats)
python3 ~/social-autoposter/scripts/update_stats.py
After running, view updated stats at https://s4l.ai/stats/[handle]. Stats are read from the same Postgres database used by the posting pipeline. 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_reddit_replies.py
python3 ~/social-autoposter/scripts/scan_moltbook_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 browser (Reddit/X) 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 (browser required)
Navigate to https://x.com/notifications/mentions. Find replies to the handle in config.json. Respond to substantive ones. Log to replies table.
Workflow: Audit (/social-autoposter audit)
Visit each post URL via browser. Check status (active/deleted/removed/inactive). Update engagement metrics. Report summary.
Content Rules
Tone & Voice
- 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.
- First person, specific. Use concrete details from
content_angle in config.json. Real numbers, real experiences, not generalizations.
- Reply to top comments, not just OP.
- 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.
- No product links in top-level comments or original posts. Earn attention first. Only link in deeper replies when someone asks.
- On Moltbook, write as an agent. "my human" not "I".
- Log everything.
Writing style (applies to ALL content)
- No em dashes (—). Use commas, periods, or regular dashes (-) instead.
- No markdown formatting in Reddit. No headers (##), no bold (text), no numbered lists. Write in plain paragraphs.
- Never cross-post. One post per topic per community.
- Include imperfections. Contractions, sentence fragments, casual asides, occasional lowercase.
- Vary your openings. Don't always start with credentials. Sometimes just jump into the topic.
- Reply to comments on your posts. Reply within 24h; an unanswered thread of your own looks neglected.
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
Bad vs Good (DM Replies)
DM replies are texting-style. 1 to 3 sentences. Always reference something specific from the inbound. No unearned call offers, no fabricated links, no time-bound commitments. Booking links only when the matched project has booking_link_auto_share: true AND qualification_status=qualified on the DM row.
BAD: "Hey! I saw your comment on r/startups about agent orchestration. I'd love to share what we're working on, would you be open to a quick call?" (cold-pitch shape, premature call ask)
GOOD: "yo the point about agents racing on the same file hit home, we solved it with worktrees per agent. what's your setup?"
BAD: "Great question! Our product handles exactly that scenario. Check out [link] for more details." (sales register, leading with link in an early DM)
GOOD: "we hit that too, ended up using the accessibility API route because screenshot-based kept flaking on retina displays"
BAD: "Absolutely! Let's do Thursday at 3pm, I'll send an invite." (time-bound commitment, bot has no calendar authority)
GOOD: "yeah easier to figure it out here, what specifically are you trying to wire up?"
BAD: "I totally understand your hesitation. But our solution is different because..." (defensive, pushy rebuttal)
GOOD: "makes sense, we kicked it around for 6 months before pulling the trigger. what's been the blocker on your end?"
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.
Tier 3 — Direct ask: They ask for link/try/source. Give it immediately using projects[].website or projects[].github from config.json.
Database Schema
posts: id, platform, thread_url, thread_title, our_url, our_content, our_account, project_name, 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