douyin-comment-auto-reply（抖音评论自动回复）

Douyin Comment Auto Reply / 抖音评论自动回复

Use this skill to turn messy Douyin comment handling into a repeatable operating workflow.

Recommended display name: Douyin Comment Auto Reply / 抖音评论自动回复.

Default goal:

• reply faster
• keep tone consistent
• filter leads from noise
• reduce manual repetition

Default scope:

• your own Douyin account / your own video comments
• not mass spam
• not fake engagement

Core workflow

Follow this sequence unless the user asks for only one piece.

1. Clarify the business context

Identify: - account type - content niche - offer or product - target audience - desired tone - whether replies are draft-only, review-first, or auto-send

1. Choose the operating mode

- Draft mode: produce reply drafts only - Review mode: classify comments and draft priority replies - Semi-auto mode: generate replies plus execution checklist - Playbook mode: build reusable SOP, intent tags, reply library

1. Classify comments before replying

Tag each comment into one primary bucket: - 咨询 / inquiry - 成交意向 / buying intent - 价格异议 / price objection - 质疑 / skepticism - 催更 / engagement - 售后 / support - 无效 / noise or troll

1. Generate replies by bucket

Return short, natural, platform-native replies. Prefer one-line or two-line answers. Keep the reply feeling human, not robotic.

1. Escalate when needed

Recommend manual handling when comments involve: - refunds or disputes - sensitive policy topics - legal risk - obvious harassment - high-value leads needing custom conversion

Reply rules

General style

• sound like the creator or brand account, not customer support boilerplate
• keep replies short
• avoid over-explaining in public comment threads
• move high-intent leads toward DM or next action when appropriate
• do not argue with trolls unless the user explicitly wants a public stance

Good reply patterns

Use these patterns often:

• 轻回应: acknowledge + short answer
• 引导私信: answer briefly + move to DM
• 社交放大: turn praise into momentum
• 异议拆解: soften objection + give one concrete clarification
• 筛选客户: invite only relevant users to continue

Avoid

• long essay replies
• emotionally defensive tone
• promises you cannot fulfill
• copy-paste repetition across every comment
• suspiciously identical AI-style replies

Recommended output format

1. 账号与目标 / Account Context

• Niche:
• Offer:
• Tone:
• Reply mode:

2. 评论分类 / Comment Classification

For each comment:

• Comment:
• Intent tag:
• Priority: high / medium / low
• Suggested action:

3. 回复建议 / Reply Suggestions

• Public reply:
• Optional DM follow-up:
• Why this works:

4. 规则与SOP / Rules and SOP

• Safe to auto-reply:
• Must review manually:
• Keywords to escalate:
• Conversion triggers:

Lead-handling guidance

When comments show buying intent, prefer this public flow:

1. answer one key concern
2. keep trust high
3. invite next step privately or via clear CTA

For example:

• 想了解具体方案可以私信我，我把适合你的版本发你。
• If you want the detailed version, DM me and I’ll send the suitable option.

Use with batches

When the user provides many comments, do not answer blindly one by one first.

Instead:

1. cluster similar comments
2. produce reusable reply patterns
3. then draft per-comment variants only where needed

Safety guardrails

• do not facilitate harassment, brigading, or spam
• do not impersonate a real human user outside the owner account voice
• do not fake testimonials or fabricated customer experience
• do not auto-reply to sensitive disputes without review
• clearly separate public reply copy from DM conversion copy

Batch processing script

Use scripts/batch_comment_drafts.py when the user provides exported comments in CSV form.

Expected CSV columns:

• comment
• video_topic (optional)
• intent_hint (optional)
• priority_hint (optional)
• notes (optional)

Run:

python3 scripts/batch_comment_drafts.py ./comments.csv
python3 scripts/batch_comment_drafts.py ./comments.csv ./comments.drafts.json

The script outputs one JSON item per comment with:

• detected intent
• priority
• suggested action
• public reply draft
• optional DM follow-up draft

Browser execution script

Use scripts/browser_reply_runner.py when the user wants browser-based execution against the Douyin comment management page.

Recommended workflow:

1. Generate draft JSON first.
2. Open Douyin comment management page and identify stable selectors for the reply box and submit button.
3. Run the browser execution script in --dry-run first.
4. Only then run the real send flow.

Example:

python3 scripts/browser_reply_runner.py ./comments.drafts.json \
  --url "https://creator.douyin.com/creator-micro/content/manage" \
  --reply-box-selector "textarea" \
  --submit-selector "button[type=submit]" \
  --dry-run

Then real send:

python3 scripts/browser_reply_runner.py ./comments.drafts.json \
  --url "https://creator.douyin.com/creator-micro/content/manage" \
  --reply-box-selector "textarea" \
  --submit-selector "button[type=submit]"

This executor defaults to npx -y agent-browser, so it can work even if agent-browser is not installed globally yet.

References

Read references/playbook.md for comment buckets, reply templates, escalation rules, and automation design notes.

Read references/douyin-lead-gen-template.md when the user is using Douyin comments to convert AI services, training, deployment, consulting, or other lead-gen offers.

Read references/automation-roadmap.md when the user wants to move from draft generation into semi-automatic or controlled automatic execution.