tiktok-replier

# TikTok Comment Replier Two-stage pipeline for managing TikTok comments on @codewithtyler: - **Read side**: Apify (`clockworks/tiktok-comments-scraper`) — clean structured JSON, $0.001/comment - **Write side**: Playwright with persistent Chromium profile — needed because TikTok has no official reply API ## Files - `auth.py` — one-time login, saves persistent profile to `data/profile/` - `apify_fetch.py` — pulls comments via Apify, writes `data/unreplied.json` - `reply.py` — reads `data/replies_queue.json`, posts each reply, tracks done in `data/posted.json` - `data/replies_queue.json` — the queue of {cid, author, comment_text, video_url, reply_text} - `data/posted.json` — comment IDs already replied to (prevents double-posting) ## The hourly cron + manual draft workflow (PRIMARY pattern) A cron runs `monitor.py` every hour at :05. It produces three artifacts in `data/`: - **`inbox.json`** — comments needing your manual reply (with full metadata: cid, author, text, video_url, etc). This is what you ask Claude to help draft. - **`drafts_queue.json`** — auto-drafted Skool-link replies for keyword CTAs (System / Plan / Skill / Email / Routine / Tools / VFX / schedule / video / workflow). Already ready to post. - **`drafts.md`** — human-readable running log. ### When the user says "any new comments?" / "check my tiktok inbox" 1. Read `data/inbox.json` (manual-needed) AND `data/drafts_queue.json` (auto-drafts pending). 2. Show the user the breakdown — count of each plus the actual text of inbox items. 3. He picks one or all to draft replies for. ### When the user asks "draft a reply for the @username one" 1. Read the inbox entry for that comment. 2. Compose a reply that fits your tone (casual, helpful, drives to skool.com/the-ai-agency when relevant). Use `/harut` for conversion-sensitive wording. 3. Show the user the draft, get approval. 4. When approved, run: ``` python3 ~/.claude/skills/tiktok-replier/queue_draft.py --cid <cid> --reply "<text>" ``` This appends to `replies_queue.json` AND removes from `inbox.json`. ### When the user says "post them" ``` python3 ~/.claude/skills/tiktok-replier/reply.py --post --headless ``` For auto-drafted Skool-link CTAs: ``` python3 ~/.claude/skills/tiktok-replier/reply.py --post --headless --queue ~/.claude/skills/tiktok-replier/data/drafts_queue.json ``` ## Standard workflow (manual / first-time) ### 1. Fetch unreplied comments Use Apify via MCP (recommended — no token maintenance needed): ``` mcp__apify__call-actor with actor=clockworks/tiktok-comments-scraper input: {"profiles": ["codewithtyler"], "resultsPerPage": 30, "commentsPerPost": 50, "maxRepliesPerComment": 10, "profileSorting": "latest"} ``` Then `mcp__apify__get-actor-output` with the dataset ID, fields=`cid,uniqueId,text,diggCount,replyCommentTotal,likedByAuthor,repliesToId,createTimeISO,videoWebUrl`. Filter: top-level (repliesToId is null) AND no reply from @codewithtyler in same thread AND author != codewithtyler. OR run the local script (needs APIFY_API_TOKEN in `~/.claude/.env`): ``` python3 ~/.claude/skills/tiktok-replier/apify_fetch.py --videos 30 --per 100 ``` ### 2. Build reply queue Show the user the unreplied list, confirm wording, and write `data/replies_queue.json`. Each entry needs: - `cid` — comment ID (used to skip already-posted) - `author` — TikTok username (used to find the row) - `comment_text` — original comment text (used to verify the right row) - `video_url` — full video URL - `reply_text` — what to reply with For keyword-style CTAs (System / Plan / Skill / Email / Routine / Tools / VFX / schedule), the standard reply is: ``` https://www.skool.com/the-ai-agency is the link! It is in the Social Media Classroom (free of course!) ``` ### 3. Post the replies Login first if `data/profile/` is empty: `python3 auth.py` (interactive, opens browser, auto-detects sessionid cookie). **Always test on 1 first, then batch:** ``` python3 reply.py --post --limit 1 --headless # smoke test python3 reply.py --post --headless # batch (30s pause between each) ``` For first run or debugging, drop `--headless` so the browser is visible. Default to `--headless` once the flow is confirmed working. `--post` is required to actually publish. Without it the script does dry-run (composes but doesn't click submit). ## Critical implementation notes (so future sessions don't re-debug TikTok's DOM) - **Auth** must use `launch_persistent_context(user_data_dir=...)`, NOT `storage_state`. TikTok's session is bound to fingerprint + localStorage + IndexedDB; cookies alone aren't enough. - **Comment-icon click** opens the proper comments view: `[data-e2e="comment-icon"]` on the video player. The right-side "Comments" tab is a different sidebar preview that doesn't expose proper Reply controls. - **Per-comment Reply button** is `div[class*="DivReplyTriggerWrapper"]` inside `div[class*="DivCommentItemWrapper"]`. Click it via real Playwright `page.mouse.click(x, y)` at its center — JS `.click()` does NOT trigger TikTok's React handler. - **Reply composer** is a contenteditable Draft.js editor where the placeholder div intercepts pointer events. Focus it via JS (`el.focus()`), then `page.keyboard.type()`. Don't use Playwright's `.click()` on the contenteditable. - **Submit button** is `[data-e2e="comment-post"]` (an arrow icon, NOT text "Post"). Same trick: real mouse click at pixel coords. - **Verification**: composer disappearing OR clearing OR reply text appearing in DOM = success. Don't trust any single signal. - **First-time tutorial**: TikTok shows an "Introducing keyboard shortcuts" modal that overlays the comments panel. Strip it surgically — DON'T blanket-remove all `[class*="Modal"]` elements (that nukes the legitimate panel). ## Safety rules - **Default to `--limit 1` on first run** of any new queue - **Always show drafts to you** before bulk posting (matches your memory: "Always confirm before scheduling, even if approved earlier in session") - **30s spacing between posts** to stay under TikTok's spam threshold - **`posted.json` tracks done IDs** so re-runs after a crash skip what already worked - **No automatic re-fetch + re-post loops** — you initiate each batch ## "Keep checking" - the recurring use case Two paths you can pick: 1. **Apify scheduler** (recommended): set up in their web console, runs in their cloud, emails him the dataset link. No local laptop dependency. 2. **Local cron** via `/schedule` skill: re-runs `apify_fetch.py` on a schedule, then prompts to review unreplied list. Both options drop the post step into manual review — you approve before any reply gets published.