last30days-skill — AI Agent 工作流中文教程 是 AI Skill Hub 本期精选Agent工作流之一。在 GitHub 上收获超过 26.3k 颗 Star，综合评分 9.5 分，整体质量较高。我们强烈推荐将其纳入你的 AI 工具库，帮助提升工作效率。
last30days-skill — AI Agent 工作流中文教程 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
last30days-skill — AI Agent 工作流中文教程 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一：pip 安装（推荐）
pip install last30days-skill
# 方式二：虚拟环境安装（推荐生产环境）
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install last30days-skill
# 方式三：从源码安装（获取最新功能）
git clone https://github.com/mvanhorn/last30days-skill
cd last30days-skill
pip install -e .
# 验证安装
python -c "import last30days_skill; print('安装成功')"
# 命令行使用
last30days-skill --help
# 基本用法
last30days-skill input_file -o output_file
# Python 代码中调用
import last30days_skill
# 示例
result = last30days_skill.process("input")
print(result)
# last30days-skill 配置文件示例（config.yml） app: name: "last30days-skill" debug: false log_level: "INFO" # 运行时指定配置文件 last30days-skill --config config.yml # 或通过环境变量配置 export LAST30DAYS_SKILL_API_KEY="your-key" export LAST30DAYS_SKILL_OUTPUT_DIR="./output"
<p align="center"> <a href="https://github.com/mvanhorn/last30days-skill"> <img src="https://img.shields.io/badge/%231-Repository%20Of%20The%20Day-6f42c1?style=for-the-badge&logo=github&label=GITHUB%20TRENDING" alt="GitHub Trending #1 Repository Of The Day" /> </a> <br/> <a href="https://trendshift.io/repositories/21997" target="_blank"> <img src="https://trendshift.io/api/badge/repositories/21997" alt="mvanhorn/last30days-skill | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/> </a> </p>
An AI agent-led search engine scored by upvotes, likes, and real money - not editors.
This README tracks the current v3 pipeline. The runtime skill spec lives in skills/last30days/SKILL.md, which is the source of truth for the latest command and setup behavior.
Claude Code (recommended — auto-updates via marketplace):
/plugin marketplace add mvanhorn/last30days-skill
/plugin install last30daysCodex, Cursor, Copilot, Gemini CLI, or any of 50+ Agent Skills hosts:
npx skills add mvanhorn/last30days-skill -g-g installs globally for your user, available across all projects. Drop it to scope per-project.)
More install options (claude.ai web, OpenClaw, manual) in the Install section below.
Zero config. Reddit, HN, Polymarket, and GitHub work immediately. Run it once and the setup wizard unlocks X, YouTube, TikTok, and more in 30 seconds.
---
Reddit upvotes. X likes. YouTube transcripts. TikTok engagement. Polymarket odds backed by real money and insider information. That's millions of people voting with their attention and their wallets every day. /last30days searches all of it in parallel, scores it by what real people actually engage with, and an AI agent judge synthesizes it into one brief.
Google aggregates editors. /last30days searches people.
You can't get this search anywhere else because no single AI has access to all of it. Google search doesn't touch Reddit comments or X posts. ChatGPT has a deal with Reddit but can't search X or TikTok. Gemini has YouTube but not Reddit. Claude has none of them natively. Each platform is a walled garden with its own API, its own tokens, its own auth. But you can bring your own keys and browser sessions, and suddenly an AI agent can search all of them at once, score them against each other, and tell you what actually matters.
That's the unlock. Not one better search engine. A dozen disconnected platforms, bridged by an agent.
/last30days Peter SteinbergerYou have a meeting tomorrow. You Google them. You get their LinkedIn from 2023. /last30days gives you what they're actually doing this month: joined OpenAI to work on Codex, fighting Anthropic's ban on third-party agents, shipping 23 PRs at 85% merge rate, building "LobsterOS" for cross-device agent control, and r/ClaudeCode hit 569 upvotes debating whether he's a hero or "insufferable." Scattered across X posts, Reddit threads, YouTube transcripts, and GitHub commits. None of it was on Google.
The v3 engine doesn't just search for your topic. It figures out where to search before the search begins. Type "OpenClaw" and the engine resolves @steipete (Peter Steinberger, the creator), r/openclaw, r/ClaudeCode, and the right YouTube channels and TikTok hashtags - all via a new Python pre-research brain built by @j-sperling. The old engine searched keywords. The new engine understands your topic first, then searches the right people and communities.
This is why v3 finds content v2 never could. "Paperclip" resolves @dotta. "Dave Morin" resolves @davemorin plus @OpenClaw plus the TWiST podcast. "Peter Steinberger" resolves @steipete on X and steipete on GitHub. Bidirectional: person to company, product to founder, name to GitHub profile. The right subreddits, the right handles, the right hashtags - resolved before a single API call fires.
| Surface | Install | Updates |
|---|---|---|
| **Claude Code** (recommended) | /plugin marketplace add mvanhorn/last30days-skill | Auto via marketplace, or claude plugin update last30days@last30days-skill |
| **Codex, Cursor, Copilot, Gemini CLI, GitHub Copilot, or any of 50+ [Agent Skills](https://agentskills.io) hosts** | npx skills add mvanhorn/last30days-skill -g | npx skills update last30days -g |
| **claude.ai** (web) | [Download last30days.skill](https://github.com/mvanhorn/last30days-skill/releases/latest/download/last30days.skill) and upload via Settings > Capabilities > Skills > + | Re-download and re-upload |
| **OpenClaw** | clawhub install last30days-official | clawhub update last30days-official |
skills/last30days/scripts/setup-keychain.sh
On macOS you can store keys in the system Keychain instead of a .env file. The skill picks them up automatically as the lowest-priority source — .env files and process environment still win on collision.
```bash
Two things you'll likely want to know on day one:
Where research files are saved. LAST30DAYS_MEMORY_DIR defaults to ~/Documents/Last30Days/ (Windows: C:\Users\<you>\Documents\Last30Days\). Override by setting that env var to any path in your shell, or --save-dir <path> per run. Use --save-suffix=<name> to keep multiple variations of the same topic separate (e.g. per client). Each run produces <slug>-raw[-suffix].md.
Trend monitoring across runs. The default mode produces a fresh markdown snapshot per run. To accumulate findings over time, add --store to persist into a SQLite database, then use scripts/watchlist.py for scheduled runs (with optional Slack / webhook delivery on new findings) and scripts/briefing.py for daily / weekly digests. The full cadence pattern is in CONFIGURATION.md.
Per-client wrapper scripts, custom category-peer subreddits, and the experimental beta channel for in-progress customizations are also documented in CONFIGURATION.md.
"CLI vs MCP" used to run three serial passes (12+ minutes). v3 runs one pass with entity-aware subqueries for both sides simultaneously. Same depth, 3 minutes.
/last30days OpenAI --competitors tells the hosting reasoning model to discover the top 2 peers via WebSearch (Anthropic, xAI), run Step 0.55 per entity, and invoke the engine with "OpenAI vs Anthropic vs xAI" and a per-entity --competitors-plan JSON. The engine fans out 3 full pipelines in parallel, saves a *-raw.md file per entity, and merges them into a 3-way comparison. Same mechanics power /last30days "OpenAI vs Anthropic vs xAI" directly.
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一，可自由商用、修改、分发，仅需保留版权声明。
经综合评估，last30days-skill — AI Agent 工作流中文教程 在Agent工作流赛道中表现稳健，质量优秀。如果你已有明确的使用需求，可以直接上手体验；如果还在评估阶段，建议对比同类工具后再做决策。
| 原始名称 | last30days-skill |
| 原始描述 | AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary |
| Topics | ai-promptsai-skillblueskyclaudeclaude-codeclawhubclaude-skill |
| GitHub | https://github.com/mvanhorn/last30days-skill |
| License | MIT |
| 语言 | Python |
收录时间：2026-05-22 · 更新时间：2026-05-22 · License：MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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