m13v/fazm/bundledskills
Claude Code and agent skill by m13v/fazm
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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', or after completing any task (mandatory per CLAUDE.md).
Install
npx vskill@latest install m13v/fazm/bundledskillsSKILL.md
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 only, never cron) | |
/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.
Key fields you'll use throughout every workflow:
accounts.reddit.username— Reddit handle to post asaccounts.twitter.handle— X/Twitter handleaccounts.linkedin.name— LinkedIn display nameaccounts.moltbook.username— Moltbook usernamesubreddits— list of subreddits to monitor and post incontent_angle— the user's unique perspective for writing authentic commentsprojects— products/repos to mention naturally when relevant (each hasname,description,website,github,topics)database— unused (DB is Neon Postgres viaDATABASE_URLin.env)
Use these values everywhere below instead of any hardcoded names or links.
Helper Scripts
Standalone Python scripts — no LLM needed.
Workflow: Post (/social-autoposter)
1. Rate limit check
Max 40 posts per 24 hours. Stop if at limit.
2. Find candidate threads
Option A — Script (preferred):
Option B — Browse manually: Browse /new and /hot on the subreddits from config.json. Also check Moltbook via API.
3. Pick the best thread
- You have a genuine angle from
content_anglein config.json - Not already posted in:
SELECT thread_url FROM posts - Last 5 comments don't repeat the same talking points:
``sql 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.
6. Post it
Reddit (browser automation):
- Navigate to
old.reddit.comthread 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):
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
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. Rate limit check
Max 1 original post per 24 hours. Max 3 per week.
2. Cross-posting check
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: old.reddit.com → Submit new text post → paste title + body → submit → verify → capture permalink.
6. Log it
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)
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)
Phase B: Respond to pending replies
Draft replies: 2-4 sentences, casual, expand the topic. Apply Tiered Reply Strategy. Max 5 replies per run.
Post via browser (Reddit/X) or API (Moltbook). Update:
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 (max 5). 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_anglein 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_anglefrom 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.
Anti-AI-Detection (applies to ALL content)
- No em dashes (—). Use commas, periods, or regular dashes (-) instead. Em dashes are the #1 "ChatGPT tell."
- 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.
- Space posts out. Max 1 original post per day, max 3 per week. Don't spam.
- 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. 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.
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, posted_at, status, upvotes, comments_count, views, source_summary
replies: id, post_id, platform, their_author, their_content, our_reply_content, status (pending|replied|skipped|error), depth
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingDesktop/Sources/BundledSkills/social-autoposter.skill.md
Popularity
- Repository stars
- 87
- Repository forks
- 9
- 7-day trend score
- 22
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 26 Mar 2026, 7 months ago.
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