MorningAI

What happened in AI today? — An AI news tracking skill that runs inside your coding agent. No Docker, no servers — just invoke /morning-ai in Claude Code, Codex, Cursor, Gemini CLI, or any SKILL.md-compatible tool. Monitors 80+ entities across 9 data sources, generates scored daily reports with optional infographics.

Features

• Skill-Native — Runs inside your AI coding tool (Claude Code, Codex, Cursor, Gemini CLI). No Docker, no servers, no extra infra — just /morning-ai
• Entity-Centric Tracking — 80+ curated entities across AI labs, model infra, coding agents, apps, vision/media, benchmarks, KOLs. Per-entity cross-platform handles (X, GitHub, HF, arXiv, YouTube, Discord), not keyword search
• 9 Concurrent Sources — X/Twitter, Reddit, HN, GitHub, HuggingFace, arXiv, web search, YouTube, Discord. 4 sources free without API keys
• Smart Scoring — 5-dimension weighted scoring: Impact (30%), Differentiation (25%), Breakthrough (20%), Coverage (15%), Timeliness (10%). Score 7+ items auto-verified across multiple independent sources
• Custom Watchlists — Add your own entities via simple markdown files — no code changes needed
• 5 Infographic Styles — classic, dark, glassmorphism, newspaper, tech — ready for social sharing
• Scheduled & Unattended — Idempotent daily runs, no interactive prompts, partial success support

How It Works

SKILL.md (loaded by any AI tool)
    |
    +- Step 1: python3 skills/tracking-list/scripts/collect.py  ->  data_{date}.json
    |           (9 sources, concurrent, score + dedupe)
    |
    +- Step 2: Read skills/tracking-list/SKILL.md  ->  scoring & format spec
    |
    +- Step 3: Write report_{date}.md  ->  structured daily report
    |
    +- Step 4: (optional) Read skills/gen-infographic/SKILL.md  ->  cover image

The Python collector runs 9 sources concurrently (X/Twitter, Reddit, HN, GitHub, HuggingFace, arXiv, web search, YouTube, Discord), then scores, deduplicates, and cross-links results. The AI tool reads the JSON output and generates a formatted Markdown report.

Install

Claude Code

# Step 1: Add marketplace source
marketplace add octo-patch/MorningAI

# Step 2: Install the plugin
/plugin install morning-ai

# Step 3: Restart Claude Code, then use
/morning-ai

Or manual install:

git clone https://github.com/octo-patch/MorningAI.git ~/.claude/skills/morning-ai

ClawHub

clawhub install morning-ai

Gemini CLI

gemini extensions install https://github.com/octo-patch/MorningAI.git

OpenAI Codex

If cloned or forked, Codex auto-discovers the plugin via .codex-plugin/plugin.json and AGENTS.md — no manual setup needed.

Or install as a skill:

git clone https://github.com/octo-patch/MorningAI.git ~/.agents/skills/morning-ai

Other Tools (Cursor, Amp, Jules, etc.)

AGENTS.md at the repo root is an open standard recognized by Codex, Cursor, Amp, Jules, and more. Clone the repo and the tool will auto-discover it.

Manual (any tool)

git clone https://github.com/octo-patch/MorningAI.git
cd MorningAI

Setup

Create a config file at ~/.config/morning-ai/.env:

SCRAPECREATORS_API_KEY=your_key    # X/Twitter (required for X source)
GITHUB_TOKEN=ghp_xxx               # GitHub (optional)
YOUTUBE_API_KEY=your_key            # YouTube (optional)
DISCORD_TOKEN=your_token            # Discord (optional)
BRAVE_API_KEY=your_key              # Web search (optional)

Without any API keys, 4 free sources work out of the box: Reddit, Hacker News, HuggingFace, arXiv.

Custom Entity Watchlist

Track your own entities beyond the built-in 80+ by creating a markdown file:

cp entities/custom-example.md entities/custom/my-watchlist.md

Edit the file with your entities:

## My Startup

| Platform | Value |
|----------|-------|
| X | @my_startup, @founder |
| GitHub | my-startup-org |
| HuggingFace | my-startup |
| Reddit | MyStartup |

Each entity starts with a ## Name heading followed by a | Platform | Value | table. Not all platforms are required — add only what you need. Supported platforms: X, GitHub, HuggingFace, arXiv, Web, Reddit, HN, YouTube, Discord.

Custom entity files are loaded from (in priority order):

1. CUSTOM_ENTITIES_DIR env var
2. ~/.config/morning-ai/entities/
3. entities/custom/ in the project directory

Files in entities/custom/ are gitignored, so your watchlists stay local.

Usage

Invoke the skill in your AI tool:

/morning-ai

Or run the collector standalone:

python3 skills/tracking-list/scripts/collect.py --date 2026-04-08 --output report.json

Infographic Styles

Set IMAGE_STYLE in your .env to choose a visual style for generated infographics:

Style	Description
classic	Clean editorial magazine — off-white background, navy/coral/teal accents (default)
dark	Dark mode — charcoal background, electric blue/violet accents
glassmorphism	Frosted glass cards on soft gradient background — modern SaaS feel
newspaper	Classic newsprint — serif typography, cream/black/crimson, broadsheet layout
tech	Terminal aesthetic — dark background, monospace, cyan/green/amber accents

IMAGE_STYLE=dark
IMAGE_GEN_PROVIDER=gemini

Tracked Entities (80+)

Group	Entities	Count
ai-labs	OpenAI, Anthropic, Google, Meta AI, xAI, Microsoft, Qwen, DeepSeek, Doubao, GLM, Kimi, MiniMax, Kling, InternLM, LongCat, Yi, Baichuan, StepFun, Hunyuan	19
model-infra	NVIDIA, Mistral AI, Cohere, Perplexity AI, AWS, Together AI, Groq, Apple/MLX, vLLM, SGLang, KTransformers	11
coding-agent	Cursor, Cline, OpenCode, Droid, OpenClaw, Windsurf, Augment, Aider, Devin, browser-use, Hermes Agent	11
ai-apps	v0, bolt.new, Lovable, Replit, Lovart, Manus, Genspark, Character.ai	8
vision-media	Midjourney, FLUX, Ideogram, Adobe Firefly, Leonardo AI, Stability AI, Lightricks, Runway, Pika, Luma AI, ElevenLabs, Udio/Suno	12
benchmarks-academic	LMSYS, LMArena, Artificial Analysis, HuggingFace, Scale AI SEAL, OpenCompass, LiveBench, WildBench, Terminal-Bench, Vals AI, Design Arena, Vending-Bench, SimpleBench, Repo Bench, Replicate, 5 paper channels, 2 Reddit communities, 4 industry media	20+
kol	Andrej Karpathy, AK, Andrew Ng, Rowan Cheung, Ben Tossell, Elie Bakouch, Swyx, Simon Willison	8
trending-discovery	GitHub Trending, Product Hunt, Hacker News, Reddit	4 sources

All items are classified into 4 types: Product, Model, Benchmark, Funding.

Deploy to Multiple Tools

bash scripts/sync.sh

Distributes the skill to ~/.claude/skills/, ~/.agents/skills/, and ~/.codex/skills/.

License

MIT