docs: add README with quick start guide
- Overview of AI Self-Improvement Digest - Quick start installation instructions - Daily workflow explanation - Source tiers and frequencies - Output format examples - Experiment tracking guidance - Key principles for suggestions
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# AI Self-Improvement Digest
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Daily curated digest focused on AI self-improvement — content that helps AI agents get better at their job.
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## Overview
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This skill generates a daily digest covering:
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- **Harness & System Prompt Engineering** — Structuring agent instructions
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- **Skill & Tool Development** — New tools, MCP servers, integration patterns
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- **Self-Evaluation & Improvement** — How agents assess and improve themselves
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- **Multi-Agent Coordination** — Spawning, supervising, merging work
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- **Memory & Context Management** — RAG, long-term memory, compaction
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- **Workflow Automation** — Task decomposition, failure handling
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- **Foundational Research** — Academic work on agent capabilities
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## Quick Start
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### 1. Install the Skill
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```bash
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# Clone to your OpenClaw skills directory
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git clone https://git.terraphim.cloud/kimie05c34be198a20b9/ai-self-improvement-digest.git
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# Or add as submodule
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git submodule add https://git.terraphim.cloud/kimie05c34be198a20b9/ai-self-improvement-digest.git skills/ai-self-improvement-digest
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```
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### 2. Create Tracking File
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```bash
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mkdir -p memory
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cat > memory/ai-digest-posted.json << 'EOF'
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{
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"posted": [],
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"experiments": [],
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"skillsEvaluated": [],
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"setupChanges": []
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}
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EOF
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```
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### 3. Set Up Cron Job
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```bash
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openclaw cron add \
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--name ai-self-improvement-digest \
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--schedule "30 8 * * *" \
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--tz "Asia/Shanghai" \
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--message "Generate today's AI Self-Improvement Digest following the workflow in the ai-self-improvement-digest skill. Read memory/ai-digest-posted.json first for deduplication."
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```
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## Daily Workflow
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1. **Deduplication** — Read `memory/ai-digest-posted.json`, skip already posted
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2. **Scan Sources** — Check Tier 1-3 sources for last 24-72h content
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3. **Filter** — Only include self-improvement relevant items
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4. **Format** — 3-5 items with summary, relevance, takeaway
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5. **Experiment** — Suggest one small experiment to try
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6. **Setup Review** — Compare findings against existing setup, suggest updates
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7. **Track** — Append to `memory/ai-digest-posted.json`
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## Sources
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| Tier | Sources | Frequency |
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|------|---------|-----------|
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| **1** | Anthropic Engineering, Simon Willison, Geoff Huntley, Hacker News, Lilian Weng | Daily |
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| **2** | Latent Space, Cursor Blog, Eugene Yan, Chip Huyen, Mitchell Hashimoto | 2-3x/week |
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| **3** | arXiv cs.CL/cs.AI, GitHub Trending | Weekly |
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## Output Format
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```
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🧠 AI Self-Improvement Digest — 2026-02-26
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**[Article Title]** — Source
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What: One-sentence summary
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Why it matters: How this helps you improve
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Takeaway: Specific pattern to try
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Relevance: ⭐⭐⭐⭐⭐
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💡 Today's experiment: [One small thing to try]
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🔧 Setup Review
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- Let's add [X] because [reason from article]
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- Let's update [Y] to [improvement]
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📊 Feedback: 👍 useful | 👎 skip | 🔥 more | 💬 thoughts
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```
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## Experiment Tracking
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Log experiments and outcomes in `memory/ai-digest-posted.json`:
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```json
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{
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"experiments": [
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{
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"date": "2026-02-26",
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"fromArticle": "meta-learning-loops",
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"experiment": "Implement regressions list",
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"outcome": "Prevents repeated mistakes",
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"learned": "Structural feedback loops > RAG"
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}
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]
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}
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```
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## Key Principles
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1. **Ground suggestions** in existing setup (AGENTS.md, TOOLS.md, skills/)
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2. **Use affirmative voice** — "let's do X" not "could consider X"
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3. **Connect to sources** — Each suggestion tied to specific finding
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4. **It's okay to have no suggestions** — Quality over quantity
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## Dependencies
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- `kimi_search` — Web search (via Kimi Claw plugin)
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- `kimi_fetch` — Content extraction
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- `cron` — Scheduled execution
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## License
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MIT — See LICENSE file
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## Author
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Kimiko (Terraphim instance) for Alexander Mikhalev
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---
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*Part of the Terraphim ecosystem: git.terraphim.cloud*
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