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tiktok-warmup抖音预热

Agent Skill

tiktok-warmup 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

494

周安装

20

GitHub Stars

公开资料未说明

下载量

155
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tiktok-warmup(抖音预热)
来源仓库:https://github.com/frahman5/fstack
仓库路径:skills/tiktok-warmup
安装命令:
npx skills add https://github.com/frahman5/fstack --skill tiktok-warmup
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/frahman5/fstack --skill tiktok-warmup

简介

用于抖音账号或内容的预热准备,适合在新品发布、直播活动等场景前进行信息收集。

  • 可根据关键词或时间节点检索相关素材、策略或历史数据,辅助运营规划。
  • 通过 GitHub 仓库安装,使用 npx 命令添加技能,需结合原始 README 验证具体用法。
  • 使用前请核实权限配置、数据访问限制,避免触发敏感操作或外部系统调用。
  • tiktok-warmup 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

TikTok Warmup Skill

Warms up TikTok accounts for Flooently + Blaze using Multilogin browser profiles. Targets Spanish learners across Latin America.

This is now a semi-manual system. Faiyam runs /execute-warmups (see prompts/execute-warmups.md) when ready to warm up. The agent plans today's sessions, runs them in parallel across accounts, and relies on Faiyam for manual debugging (CAPTCHAs, re-logins, weird modals). No background scheduler, no cron — just a slash command.

Pre-flight — run this immediately on skill load

First, update the skill to the latest version from fstack:

npx skills update

Then run the checks below and report health status for each activity. Do not block — just show the user what's ready and what isn't.

source .env.cli 2>/dev/null || true

# 1Password — TikTok vault
OP_VAULT_STATUS="❌ OP_SERVICE_ACCOUNT_TOKEN not set"
if [ -n "$OP_SERVICE_ACCOUNT_TOKEN" ]; then
  VAULTS=$(OP_SERVICE_ACCOUNT_TOKEN=$OP_SERVICE_ACCOUNT_TOKEN op vault list --format=json 2>&1)
  if echo "$VAULTS" | python3 -c "import json,sys; names=[v['name'] for v in json.load(sys.stdin)]; assert 'Tiktok' in names" 2>/dev/null; then
    OP_VAULT_STATUS="✅ 1Password Tiktok vault accessible"
  else
    OP_VAULT_STATUS="❌ Tiktok vault not found (wrong OP token, or vault not shared with this service account)"
  fi
fi

# MLX token
MLX_STATUS="❌ MLX_AUTOMATION_TOKEN not set"
[ -n "$MLX_AUTOMATION_TOKEN" ] && MLX_STATUS="✅ MLX_AUTOMATION_TOKEN set"

# AgentMail
AM_STATUS="❌ AGENTMAIL_KEY not set"
[ -n "$AGENTMAIL_KEY" ] && AM_STATUS="✅ AGENTMAIL_KEY set"

# Airtable — token must be present AND resolver must find a matching base
AT_STATUS="❌ AIRTABLE_ACCESS_TOKEN not set"
if [ -n "$AIRTABLE_ACCESS_TOKEN" ]; then
  RESOLVER_OUT=$(python3 .agents/skills/tiktok-warmup/resolve_airtable_schema.py 2>&1)
  if [ $? -eq 0 ]; then
    AT_STATUS="✅ $(echo "$RESOLVER_OUT" | head -1)"
  else
    AT_STATUS="❌ Airtable resolver failed: $(echo "$RESOLVER_OUT" | tail -2 | head -1)"
  fi
fi

echo ""
echo "🔍 Environment Health"
echo ""
echo "  Account Warmup:"
echo "    $MLX_STATUS"
echo "    $OP_VAULT_STATUS"
echo "    $AM_STATUS"
echo "    $AT_STATUS"
echo ""
echo "  Account Creation:"
echo "    $OP_VAULT_STATUS (needs read+write)"
echo "    $AM_STATUS"
echo "    $AT_STATUS"
echo ""

Report the output to the user before proceeding. If warmup prerequisites (MLX + OP vault) are missing, tell the user warmup won't work and ask if they want to fix it first.


Reference Files

FilePurpose
multiloginRef.mdMultilogin X API reference — auth, workspace IDs, profile IDs, how to start/stop profiles, Playwright connection.
browserWarmupRef.mdBrowser warmup protocol — humanized Playwright sessions on tiktok.com via Multilogin browser profiles. Preferred approach.
loginRef.mdTikTok login procedure — do this yourself agentically, never delegate to ensure_login.py. Covers where creds live (1Password Claude-Accessible vault), OTP retrieval (AgentMail), captcha handling, and the visual login-verification checklist.
sessionDesignRef.mdHow to compose the per-account task queue. Target 50%+ niche-explicit time in early weeks. Recommended task mixes by week, anti-patterns, working example for Sofia. Read this when building a queue for any /execute-warmups run.
accountsRef.mdAccount registry auto-refresh protocol. Accounts live in Airtable; scripts read from scripts/warmup/accounts.json. The agent refreshes the cache at step 2 of every /execute-warmups run so new/removed accounts propagate automatically with no code edits.
airtableRef.mdAirtable base/table/field IDs - Accounts + Session Log are the two tables we use.
computerUseRef.mdMobile cloud phone warmup - computer-use based. Used only for late-stage weeks or special cases.
peekabooRef.mdPeekaboo CLI fallback - used when request_access fails for cloud phone sessions.
runtimeLearnings.mdOperational learnings from live sessions - read before every execution.
accountCreationRef.mdHow to create TikTok accounts and store credentials in 1Password.
createTiktokRef.mdFull interactive protocol for /create-tiktok — step-by-step account creation walkthrough.
adoptAccountRef.mdWalkthrough for integrating a TikTok account created by someone else (e.g. a Fiverr freelancer) — credential takeover, Multilogin setup, Airtable registration, Postiz connection, Search Term generation.
executeWarmupsRef.mdFull protocol for /execute-warmups — plans and runs warmup sessions across all active accounts.

Protocols

  • Run today's warmups (the main thing): trigger /execute-warmups. Full protocol in executeWarmupsRef.md.
  • Run a one-off browser warmup session: read multiloginRef.md + browserWarmupRef.md + runtimeLearnings.md, then invoke scripts/tiktok-warmup-poc.py.
  • Run a mobile warmup session (rare): read multiloginRef.md + computerUseRef.md + runtimeLearnings.md.
  • Create a new TikTok account: trigger /create-tiktok. Full protocol in createTiktokRef.md.
  • Adopt an externally-created account (e.g. from Fiverr): read adoptAccountRef.md and walk the user through it step-by-step.
  • Multilogin API operations: read multiloginRef.md.

Design philosophy

Target 30-90 min of warmup per account per day, split into 2-4 sessions of 15-30 min each. Rest days in weeks 1-2 are natural (deterministic per account). The Scheduled Sessions Airtable table is deprecated - we log results directly to Session Log.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

39.03%
按下载量换算60

Claude

29.65%
按下载量换算46

Cursor

17.35%
按下载量换算27

Gemini CLI

9.71%
按下载量换算15

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

未通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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