---
name: ai-self-improvement-digest
description: Create a daily digest focused on AI self-improvement material - content that helps an AI agent get better at its job. Use when setting up daily learning routines, building self-improving agents, or curating educational content for agent development. Covers harness engineering, skill development, self-evaluation, multi-agent coordination, memory management, and workflow automation.
---

# AI Self-Improvement Digest

This skill creates a daily digest focused on AI self-improvement material, not general AI news. The goal is to surface content that helps an AI agent get better at its job.

## What This Digest Covers

1. **Harness & System Prompt Engineering** - How to structure agent instructions
2. **Skill & Tool Development** - New tools, MCP servers, integration patterns
3. **Self-Evaluation & Improvement** - How agents assess and improve themselves
4. **Multi-Agent Coordination** - Spawning, supervising, merging work
5. **Memory & Context Management** - RAG, long-term memory, compaction
6. **Workflow Automation** - Task decomposition, failure handling
7. **Foundational Research** - Academic work on agent capabilities

## Prerequisites

1. **Kimi Search** - The `kimi-search` plugin is used for web searches (enabled by default with Kimi Claw).

2. **Tracking File** - Create `memory/ai-digest-posted.json`:
   ```json
   {
     "posted": [],
     "experiments": [],
     "skillsEvaluated": [],
     "setupChanges": []
   }
   ```

## Daily Digest Workflow

### Step 1: Deduplication (MANDATORY)

Read `memory/ai-digest-posted.json`. Skip anything already posted (by URL or substantially similar topic).

### Step 2: Scan Sources

Use `kimi_search` and `kimi_fetch` to check these sources for content from last 24-72h:

**Tier 1 (daily):**
- Anthropic Engineering: anthropic.com/engineering
- Simon Willison: simonwillison.net
- Geoff Huntley: ghuntley.com
- Hacker News: news.ycombinator.com (AI/agent threads)
- Lilian Weng: lilianweng.github.io

**Tier 2 (2-3x/week):**
- Latent Space: latent.space
- Cursor Blog: cursor.com/blog
- Eugene Yan: eugeneyan.com
- Chip Huyen: huyenchip.com
- Mitchell Hashimoto: mitchellh.com

**Tier 3 (weekly):**
- arXiv cs.CL/cs.AI
- GitHub Trending (AI agent repos, MCP servers)

### Step 3: Filter for Self-Improvement Relevance

Only include items that help improve capabilities in the 7 categories listed above.

**EXCLUDE:** General AI news, model announcements, business news, ethics debates, items already in `ai-digest-posted.json`.

### Step 4: Format (3-5 items)

For each item, include:

```
**[Title]** — [Source]
What: [1-sentence summary]
Why it matters for self-improvement: [How this helps you get better]
Takeaway: [Specific pattern, technique, or experiment to try]
Relevance: [⭐ to ⭐⭐⭐⭐⭐]
```

### Step 5: Experiment Suggestion

Include one small experiment to try based on the digest:

```
💡 Today's experiment: [One small thing to try that could improve capabilities]
```

### Step 6: Setup Review (MANDATORY)

Review findings against existing setup (AGENTS.md, TOOLS.md, skills/, cron jobs). Make concrete, affirmative suggestions:

```
🔧 Setup Review
Based on today's findings:
- Let's add [specific thing] because [reason tied to content found]
- Let's update [existing thing] to [improvement] because [reason]
```

If nothing is actionable: "No changes needed today — our current setup handles these patterns well."

### Step 7: Update Tracking

Append new items to `memory/ai-digest-posted.json` with date, title, url, topic.

## Output Format

```
🧠 AI Self-Improvement Digest — [Date]

[Items formatted as above]

💡 Today's experiment: [...]

🔧 Setup Review
[Suggestions or "No changes needed today"]

📊 Feedback: 👍 = useful | 👎 = skip these | 🔥 = more like this | 💬 = thoughts
```

## Source Priority Reference

| Source | Priority | Focus |
|--------|----------|-------|
| Anthropic Engineering | ⭐⭐⭐ | Harness design, evals, multi-agent |
| Simon Willison | ⭐⭐⭐ | Practical patterns, tools |
| Geoff Huntley | ⭐⭐⭐ | Agent philosophy, MCP |
| Hacker News | ⭐⭐⭐ | High-signal AI/agent discussions |
| Lilian Weng | ⭐⭐⭐ | Deep technical AI, agent architectures |
| Latent Space | ⭐⭐ | Industry depth |
| Cursor Blog | ⭐⭐ | Coding agent patterns |
| Eugene Yan | ⭐⭐ | ML systems, production patterns |
| Chip Huyen | ⭐⭐ | ML systems design |
| arXiv cs.CL/cs.AI | ⭐⭐ | Research foundations |
| GitHub Trending | ⭐⭐ | New tools, repos |

## Self-Improvement Loop

The digest enables continuous improvement:

**DAILY:**
- Read digest
- Pick 1 experiment to try
- Log outcome in `memory/ai-digest-posted.json`
- Review Setup Review suggestions with human

**WEEKLY:**
- Review experiments
- Update harness/skills based on learnings
- Adjust source priorities based on value

## Experiment Tracking

Extend `memory/ai-digest-posted.json`:

```json
{
  "posted": [...],
  "experiments": [
    {
      "date": "2026-02-16",
      "fromArticle": "effective-harnesses",
      "experiment": "Add checkpoint before sub-agent spawn",
      "outcome": "Reduced context loss by 40%",
      "learned": "Always checkpoint before spawning"
    }
  ],
  "skillsEvaluated": [
    {
      "date": "2026-02-16",
      "skill": "mcp-postgres",
      "verdict": "useful",
      "notes": "Integrated for database queries"
    }
  ],
  "setupChanges": [
    {
      "date": "2026-02-16",
      "change": "Added memory/experiments.md",
      "reason": "Track harness experiments per Anthropic article",
      "status": "implemented"
    }
  ]
}
```

## Cron Job Setup

Schedule daily at 8:30 AM:

```bash
openclaw cron add \
  --name ai-self-improvement-digest \
  --schedule "30 8 * * *" \
  --tz "America/New_York" \
  --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."
```

Or use the `cron` tool directly with `action: add` and the job configuration.

## Key Principles

1. **Ground suggestions** in what you already have
2. **Use affirmative voice** ("let's do X") not passive ("could consider X")
3. **Connect each suggestion** to a specific article/finding from the digest
4. **It's okay to have no suggestions** if nothing is actionable