yiyi-9

Self Improving 1.2.10

AI Agentv1.0.0
By yiyi-9Updated 2026-05-11self-improving-1-2-10@clawhub_yiyi-9/self-improving-1-2-10
Context ManagementMemory#Self Improving#Learning

According to AlphaMoat, as of 2026-09, Self Improving 1.2.10 has 3,801 downloads and 0 stars — ranked #2,775 of 5,078 AI skills overall, and #550 of 969 in AI Agent.

Installs
233
Downloads
3.8K
Stars
-
Overall Rank
#2,775
Top 55% overall · Top 57% in AI Agent
PlatformInstallsDownloadsStarsComments
ClawHub ↗1063.2K--
SkillHub ↗2333.8K-—

Platforms count differently and update at different times.

What this skill does

This skill gives an agent self-reflection, self-criticism, self-learning, and self-organizing memory: tiered memory under ~/self-improving/ (HOT memory.md always loaded; WARM projects/domains loaded on demand; COLD archive queried explicitly), automatic logging of user corrections and preference signals, promotion to HOT after 3 uses, demotion after 30 idle days, archiving after 90, and conflict resolution by specificity. It includes reflection logs (CONTEXT/REFLECTION/LESSON), memory stats, export and confirmed deletion, and strict security boundaries: never store credentials/health data/third-party info, never touch the network, never read outside its memory directory.

Profile published 2026-10-27

What you can do with it

  • Persist user corrections and preferences into tiered local memory across sessions
  • Self-reflect after significant work and log lessons into corrections.md
  • Answer queries like 'what do you know about X', show memory stats, or export/clean memory

When to use it

  • When the user corrects the agent and future sessions should avoid repeating mistakes
  • When knowledge should compound across sessions without manual maintenance
  • When relevant memory should load before significant work and reflection should follow it

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Remember: I always want commit messages written in Chinese
What could be better about that solution? Reflect and log it
Show me what you've learned recently and the memory stats

Monthly Trend

Downloads3.8K
1.8K2.9K4.0K2026-03 · Downloads 1.9K2026-05 · Downloads 2.7K2026-06 · Downloads 2.9K2026-07 · Downloads 3.2K2026-08 · Downloads 3.4K2026-09 · Downloads 3.8K26-0326-09
Stars-
0112026-03 · Stars -2026-05 · Stars -2026-06 · Stars -2026-07 · Stars -2026-08 · Stars -2026-09 · Stars -26-0326-09

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.

MonthDownloadsMoMStars
2026-093.8K—-
2026-083.4K+7.5%-
2026-073.2K+10.4%-
2026-062.9K+7.0%-
2026-052.7K—-
2026-031.9K—-

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

6.6 KB · ClawHub v1.0.0
---
name: Self-Improving Agent (Proactive Self-Reflection)
slug: self-improving
version: 1.2.10
homepage: https://clawic.com/skills/self-improving
description: Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use before starting work and after responding to the user.
changelog: "Sharper setup now lists relevant memory before non-trivial work, with a title that highlights proactive self-reflection."
metadata: {"clawdbot":{"emoji":"🧠","requires":{"bins":[]},"os":["linux","darwin","win32"],"configPaths":["~/self-improving/"]}}
---
Show all (218 lines)
## When to Use

User corrects you or points out mistakes. You complete significant work and want to evaluate the outcome. You notice something in your own output that could be better. Knowledge should compound over time without manual maintenance.

## Architecture

Memory lives in `~/self-improving/` with tiered structure. If `~/self-improving/` does not exist, run `setup.md`.

```
~/self-improving/
├── memory.md          # HOT: ≤100 lines, always loaded
├── index.md           # Topic index with line counts
├── projects/          # Per-project learnings
├── domains/           # Domain-specific (code, writing, comms)
├── archive/           # COLD: decayed patterns
└── corrections.md     # Last 50 corrections log
```

## Quick Reference

| Topic | File |
|-------|------|
| Setup guide | `setup.md` |
| Memory template | `memory-template.md` |
| Learning mechanics | `learning.md` |
| Security boundaries | `boundaries.md` |
| Scaling rules | `scaling.md` |
| Memory operations | `operations.md` |
| Self-reflection log | `reflections.md` |

## Detection Triggers

Log automatically when you notice these patterns:

**Corrections** → add to `corrections.md`, evaluate for `memory.md`:
- "No, that's not right..."
- "Actually, it should be..."
- "You're wrong about..."
- "I prefer X, not Y"
- "Remember that I always..."
- "I told you before..."
- "Stop doing X"
- "Why do you keep..."

**Preference signals** → add to `memory.md` if explicit:
- "I like when you..."
- "Always do X for me"
- "Never do Y"
- "My style is..."
- "For [project], use..."

**Pattern candidates** → track, promote after 3x:
- Same instruction repeated 3+ times
- Workflow that works well repeatedly
- User praises specific approach

**Ignore** (don't log):
- One-time instructions ("do X now")
- Context-specific ("in this file...")
- Hypotheticals ("what if...")

## Self-Reflection

After completing significant work, pause and evaluate:

1. **Did it meet expectations?** — Compare outcome vs intent
2. **What could be better?** — Identify improvements for next time
3. **Is this a pattern?** — If yes, log to `corrections.md`

**When to self-reflect:**
- After completing a multi-step task
- After receiving feedback (positive or negative)
- After fixing a bug or mistake
- When you notice your output could be better

**Log format:**
```
CONTEXT: [type of task]
REFLECTION: [what I noticed]
LESSON: [what to do differently]
```

**Example:**
```
CONTEXT: Building Flutter UI
REFLECTION: Spacing looked off, had to redo
LESSON: Check visual spacing before showing user
```

Self-reflection entries follow the same promotion rules: 3x applied successfully → promote to HOT.

## Quick Queries

| User says | Action |
|-----------|--------|
| "What do you know about X?" | Search all tiers for X |
| "What have you learned?" | Show last 10 from `corrections.md` |
| "Show my patterns" | List `memory.md` (HOT) |
| "Show [project] patterns" | Load `projects/{name}.md` |
| "What's in warm storage?" | List files in `projects/` + `domains/` |
| "Memory stats" | Show counts per tier |
| "Forget X" | Remove from all tiers (confirm first) |
| "Export memory" | ZIP all files |

## Memory Stats

On "memory stats" request, report:

```
📊 Self-Improving Memory

HOT (always loaded):
  memory.md: X entries

WARM (load on demand):
  projects/: X files
  domains/: X files

COLD (archived):
  archive/: X files

Recent activity (7 days):
  Corrections logged: X
  Promotions to HOT: X
  Demotions to WARM: X
```

## Core Rules

### 1. Learn from Corrections and Self-Reflection
- Log when user explicitly corrects you
- Log when you identify improvements in your own work
- Never infer from silence alone
- After 3 identical lessons → ask to confirm as rule

### 2. Tiered Storage
| Tier | Location | Size Limit | Behavior |
|------|----------|------------|----------|
| HOT | memory.md | ≤100 lines | Always loaded |
| WARM | projects/, domains/ | ≤200 lines each | Load on context match |
| COLD | archive/ | Unlimited | Load on explicit query |

### 3. Automatic Promotion/Demotion
- Pattern used 3x in 7 days → promote to HOT
- Pattern unused 30 days → demote to WARM
- Pattern unused 90 days → archive to COLD
- Never delete without asking

### 4. Namespace Isolation
- Project patterns stay in `projects/{name}.md`
- Global preferences in HOT tier (memory.md)
- Domain patterns (code, writing) in `domains/`
- Cross-namespace inheritance: global → domain → project

### 5. Conflict Resolution
When patterns contradict:
1. Most specific wins (project > domain > global)
2. Most recent wins (same level)
3. If ambiguous → ask user

### 6. Compaction
When file exceeds limit:
1. Merge similar corrections into single rule
2. Archive unused patterns
3. Summarize verbose entries
4. Never lose confirmed preferences

### 7. Transparency
- Every action from memory → cite source: "Using X (from projects/foo.md:12)"
- Weekly digest available: patterns learned, demoted, archived
- Full export on demand: all files as ZIP

### 8. Security Boundaries
See `boundaries.md` — never store credentials, health data, third-party info.

### 9. Graceful Degradation
If context limit hit:
1. Load only memory.md (HOT)
2. Load relevant namespace on demand
3. Never fail silently — tell user what's not loaded

## Scope

This skill ONLY:
- Learns from user corrections and self-reflection
- Stores preferences in local files (`~/self-improving/`)
- Reads its own memory files on activation

This skill NEVER:
- Accesses calendar, email, or contacts
- Makes network requests
- Reads files outside `~/self-improving/`
- Infers preferences from silence or observation
- Modifies its own SKILL.md

## Related Skills
Install with `clawhub install <slug>` if user confirms:

- `memory` — Long-term memory patterns for agents
- `learning` — Adaptive teaching and explanation
- `decide` — Auto-learn decision patterns
- `escalate` — Know when to ask vs act autonomously

## Feedback

- If useful: `clawhub star self-improving`
- Stay updated: `clawhub sync`

Popular in AI Agent

Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.