Agent skill · Data & Analytics

daily-brief

Operational knowledge for the daily-brief digest pipeline (this project). RSS/API fetchers, pluggable LLM enrichment (default claude CLI on Max; also anthropic/openai/deepseek/minimax API), trading section, HTML rendering, cross-platform scheduler integration (Windows Task Scheduler / macOS launchd / Linux cron). Load when the user asks about running daily / regenerating sections / debugging a failed run / adding or disabling sources / LLM quota / scheduler / why a tab shows wrong data / why a source failed / switching LLM backend. Always prefer the documented npm commands over re-implementing

leiting-ericgithub.com/leiting-ericGitHub ↗
claude-codeMIT
Install
npx skills add leiting-eric/DailyBrief --skill daily-brief --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 12 KB
Bundled scripts: none
Path: .claude/skills/daily-brief/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 311
Language: TypeScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# daily-brief — Operational Skill This project generates a single-page HTML daily digest covering tech / finance / politics / market data / community discussion. The pipeline runs locally via the OS scheduler (Windows Task Scheduler / macOS launchd / Linux cron, default 08:00 local time) and emits `daily_reports/<YYYY-MM-DD>/<YYYY-MM-DD>.html` + sidecar files (each date gets its own subdir). The date label uses the system local timezone by default — set `REPORT_TZ` (e.g. `Asia/Shanghai`, `UTC`) in `.env.local` to override. Detailed architecture lives in code; this skill is a cheat sheet for **operating** and **diagnosing**, not a re-explanation of the system. ## Project root assumption All paths in this skill are **relative to the project root** (the directory that contains `package.json`, `lib/`, `scripts/`). **Before any command, ensure the working directory is the project root.** Two cases: 1. **Claude Code session opened inside the project** — already there, no action needed 2. **Session opened elsewhere** — read the config file and `cd`: ```bash # Cross-platform Node one-liner (prints the project root path): node -e "const fs=require('fs'),os=require('os'),path=require('path')

What's inside
Steps it walks through
  1. Project root assumption
  2. Quick command reference
  3. File map — where to change what
  4. How LLM enrichment works (mental model)
  5. Diagnostic flow
  6. "今天日报没出来" / "Chrome 没弹"
  7. "某个源数据不对 / 0 条"
  8. "LLM 调用炸 / 中文摘要缺失"
  9. "UI 出错 / 某个 tab 显示异常"
  10. Recurring failure patterns (institutional knowledge)
  11. LinuxDo / Cloudflare WAF
  12. Run-daily.mjs wrapper notes
  13. "X 推文 出现非英文"
  14. "社区讨论 tab 偶发空白"
About this skill
What does the daily-brief skill do?

Operational knowledge for the daily-brief digest pipeline (this project). RSS/API fetchers, pluggable LLM enrichment (default claude CLI on Max; also anthropic/openai/deepseek/minimax API), trading section, HTML rendering, cross-platform scheduler integration (Windows Task Scheduler / macOS launchd / Linux cron). Load when the user asks about running daily / regenerating sections / debugging a failed run / adding or disabling sources / LLM quota / scheduler / why a tab shows wrong data / why a source failed / switching LLM backend. Always prefer the documented npm commands over re-implementing

How do I install it?

Run `npx skills add leiting-eric/DailyBrief --skill daily-brief --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From leiting-eric/DailyBrief, a repository with 311 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going