# Send Self-Improving Agent (With Self-Reflection) to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "self-improving",
    "name": "Self-Improving Agent (With Self-Reflection)",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/ivangdavila/self-improving",
    "canonicalUrl": "https://clawhub.ai/ivangdavila/self-improving",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/self-improving",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=self-improving",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "HEARTBEAT.md",
      "SKILL.md",
      "boundaries.md",
      "corrections.md",
      "heartbeat-rules.md",
      "heartbeat-state.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "slug": "self-improving",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-05-03T15:21:19.746Z",
      "expiresAt": "2026-05-10T15:21:19.746Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=self-improving",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=self-improving",
        "contentDisposition": "attachment; filename=\"self-improving-1.2.16.zip\"",
        "redirectLocation": null,
        "bodySnippet": null,
        "slug": "self-improving"
      },
      "scope": "item",
      "summary": "Item download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this item.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/self-improving"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/self-improving",
    "downloadUrl": "https://openagent3.xyz/downloads/self-improving",
    "agentUrl": "https://openagent3.xyz/skills/self-improving/agent",
    "manifestUrl": "https://openagent3.xyz/skills/self-improving/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/self-improving/agent.md"
  }
}
```
## Documentation

### 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.
Workspace setup should add the standard self-improving steering to the workspace AGENTS, SOUL, and HEARTBEAT.md files, with recurring maintenance routed through heartbeat-rules.md.

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

### Quick Reference

TopicFileSetup guidesetup.mdHeartbeat state templateheartbeat-state.mdMemory templatememory-template.mdWorkspace heartbeat snippetHEARTBEAT.mdHeartbeat rulesheartbeat-rules.mdLearning mechanicslearning.mdSecurity boundariesboundaries.mdScaling rulesscaling.mdMemory operationsoperations.mdSelf-reflection logreflections.mdOpenClaw HEARTBEAT seedopenclaw-heartbeat.md

### Requirements

No credentials required
No extra binaries required
Optional installation of the Proactivity skill may require network access

### Learning Signals

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:

Did it meet expectations? — Compare outcome vs intent
What could be better? — Identify improvements for next time
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 saysAction"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

### Common Traps

TrapWhy It FailsBetter MoveLearning from silenceCreates false rulesWait for explicit correction or repeated evidencePromoting too fastPollutes HOT memoryKeep new lessons tentative until repeatedReading every namespaceWastes contextLoad only HOT plus the smallest matching filesCompaction by deletionLoses trust and historyMerge, summarize, or demote instead

### 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

TierLocationSize LimitBehaviorHOTmemory.md≤100 linesAlways loadedWARMprojects/, domains/≤200 lines eachLoad on context matchCOLDarchive/UnlimitedLoad 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:

Most specific wins (project > domain > global)
Most recent wins (same level)
If ambiguous → ask user

### 6. Compaction

When file exceeds limit:

Merge similar corrections into single rule
Archive unused patterns
Summarize verbose entries
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:

Load only memory.md (HOT)
Load relevant namespace on demand
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/)
Maintains heartbeat state in ~/self-improving/heartbeat-state.md when the workspace integrates heartbeat
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
Deletes or blindly rewrites self-improving memory during heartbeat cleanup
Modifies its own SKILL.md

### Data Storage

Local state lives in ~/self-improving/:

memory.md for HOT rules and confirmed preferences
corrections.md for explicit corrections and reusable lessons
projects/ and domains/ for scoped patterns
archive/ for decayed or inactive patterns
heartbeat-state.md for recurring maintenance markers

### 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
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: ivangdavila
- Version: 1.2.16
## Source health
- Status: healthy
- Item download looks usable.
- Yavira can redirect you to the upstream package for this item.
- Health scope: item
- Reason: direct_download_ok
- Checked at: 2026-05-03T15:21:19.746Z
- Expires at: 2026-05-10T15:21:19.746Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/self-improving)
- [Send to Agent page](https://openagent3.xyz/skills/self-improving/agent)
- [JSON manifest](https://openagent3.xyz/skills/self-improving/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/self-improving/agent.md)
- [Download page](https://openagent3.xyz/downloads/self-improving)