twitter-monitor
Twitter Monitor
Workflow
Use this skill as an execution workflow, not as a long-running daemon. First complete a one-shot fetch, then offer optional Feishu sync and scheduling only when useful.
- Ask for X/Twitter account ids when missing. Accept handles such as
sama,@sama, profile URLs, or multiple comma-separated ids. - Ask the user to provide or configure a
twitterapi.ioAPI key whenTWITTER_API_KEYis unavailable. Do not write API keys into files committed to a repository. - Confirm pagination depth. Default to
--pages 1; use a larger number only when the user asks for more history or accepts higher API usage. - Run
scripts/twitter_monitor.pyand generate JSON or CSV output. - If the user wants Feishu/Lark Bitable output, follow
references/feishu-output.md. - After the one-shot command works, ask whether they want recurring execution. If yes, follow
references/scheduling.md, including OpenClaw when appropriate.
Quick Start
From this skill directory:
export TWITTER_API_KEY="..."
python scripts/twitter_monitor.py --accounts sama --pages 1 --format json
For multiple accounts:
python scripts/twitter_monitor.py --accounts sama,elonmusk,OpenAI --pages 1 --format csv
For a JSON account list:
python scripts/twitter_monitor.py --accounts-file assets/accounts.example.json --pages 1
Read references/twitterapi-setup.md when the user needs API key setup, account input examples, or command variants.
Output Schema
The script writes one record per tweet with these fields:
推文内容日期推文链接推文ID作者作者ID阅读量点赞数转发数评论数收藏数是否回复抓取时间
Deduplicate by 推文ID before appending to any durable destination.
Feishu
Do not require Feishu configuration for normal fetches. Only enter the Feishu workflow when the user asks to write, append, or sync records to Feishu/Lark Bitable.
Prefer feishu-cli over hard-coded Feishu app credentials. If feishu-cli is missing, ask whether to install and configure it. See references/feishu-output.md for the field mapping and sync rules.
Scheduling
Offer scheduling only after a successful one-shot fetch or when the user explicitly asks for ongoing monitoring.
Prefer OpenClaw when the user wants an agent-managed recurring job or already uses OpenClaw. Otherwise choose Codex automations, cron, or launchd based on the runtime environment. See references/scheduling.md.
Safety
Never commit real API keys, Feishu tokens, output files containing private monitoring data, or local status caches. Keep secrets in environment variables, secret managers, or the user's existing CLI auth.
More from kangarooking/kangarooking-skills
task-harness
将需求拆解为结构化任务清单,生成长时运行 Agent 的任务管理系统(基于 Anthropic Effective harnesses 方法论)。当用户需要管理多会话开发任务、跟踪功能完成进度、或要求"拆解任务""任务管理""项目规划"时自动触发
54harness-engineering
Initialize a Harness Engineering framework in the current project. Use when user says 'harness', 'init harness', 'initialize framework', 'setup harness engineering', '/harness', or wants to set up a Plan-Build-Verify development workflow with specialized agents (planner, generator, evaluator). Creates CLAUDE.md, agent definitions, command templates, hooks, and documentation structure for autonomous AI-driven development.
54book-illustration-workflow
用于处理写书过程中的章节截图与插图工作流。适用于:梳理某一章需要哪些截图、逐步给出 Claude Code 实操提示词、规定截图文件名与图号映射、回填本地 Markdown 中的图片位置、清理作者备注为读者版正文、以及把章节和图片按正确位置同步到 Feishu 文档。用户如果提到“书的截图”“章节配图”“图号对应”“放到原文里”“上传飞书文档”“按刚才那套流程来”,应触发此 skill。
54reshape-your-life
帮助用户从NLP理解层次的顶层重新规划人生;当用户感到迷茫、深陷日复一日的执行循环、不知如何突破现状时使用
53multi-agent-image
Standalone multi-agent image generation skill for Hermes. Includes an internal design compiler, GPT-Image-2 generation via apimart.ai, case library reuse, interactive reference selection, batch workflows, and style-consistent series generation.
53