new-self-improving

name	new-self-improving
description	Log corrections, errors, feature requests, and recurring patterns into structured workspace learning files, then promote stable patterns into tiered memory and OpenClaw workspace files (AGENTS.md, SOUL.md, TOOLS.md, MEMORY.md). Use when: (1) user corrects you or points out mistakes, (2) a command or tool fails, (3) user requests a missing capability, (4) you notice a recurring pattern worth remembering, (5) reviewing learnings during heartbeat or maintenance, (6) promoting lessons to permanent workspace memory. Designed for OpenClaw personal-assistant and coding workflows with heartbeat integration.
metadata	{"openclaw":{"emoji":"🧠","homepage":"https://github.com/muhamadbasim/oktoclaw"}}

Self-Improving OpenClaw

Structured learning loop for OpenClaw agents: capture → review → promote → maintain.

Quick Start

On first activation, run the init script to create workspace directories:

bash scripts/init-workspace.sh

This creates .learnings/ and .self-improving/ in the workspace root.

Core Workflow

1. Capture

When a learning signal fires, log it to the right file in .learnings/:

Signal	Target file	Category
User corrects you	LEARNINGS.md	correction
User says "always/never do X"	LEARNINGS.md	preference
You discover something non-obvious	LEARNINGS.md	insight
Your knowledge was outdated	LEARNINGS.md	knowledge_gap
Found a better approach	LEARNINGS.md	best_practice
Command returns non-zero	ERRORS.md	—
Tool/API fails unexpectedly	ERRORS.md	—
User wants missing capability	FEATURE_REQUESTS.md	—

Use the entry format defined in references/logging-format.md.

2. Review

During heartbeat or manual review, scan .learnings/ and evaluate each pending item:

1. Check recurrence — search for similar entries.
2. If related entry exists: bump Recurrence-Count, link with See Also.
3. If Recurrence-Count >= 3 within 30 days: add to .learnings/REVIEW_QUEUE.md.
4. Update .self-improving/heartbeat-state.md with review timestamp.

See references/heartbeat-review.md for the full review procedure.

3. Promote

Move validated patterns up the memory tiers:

Condition	Promote to	Example
Pattern used 2x, context-specific	.self-improving/domains/*.md or projects/*.md	"This repo uses pnpm"
Pattern used 3x in 7-30 days, cross-task	.self-improving/HOT.md	"User prefers concise answers"
Stable, long-term applicable	SOUL.md / AGENTS.md / TOOLS.md / MEMORY.md	"Never force push"

See references/promotion-rules.md for the full promotion/demotion rules.

4. Maintain

Periodically (every 1-2 weeks during heartbeat):

• Demote HOT entries unused for 30 days → domain/project memory.
• Archive domain/project entries unused for 90 days → .self-improving/archive/.
• Compact files exceeding size limits: merge similar entries, summarize verbose ones.
• Never delete without explicit user confirmation. Prefer archive over delete.

Detection Triggers

Log automatically when you notice these signals:

Corrections (→ LEARNINGS.md, category: correction):

• "No, that's not right..."
• "Actually, it should be..."
• "You're wrong about..."
• "I told you before..."
• "Stop doing X"

Preferences (→ LEARNINGS.md, category: preference):

• "I like when you..."
• "Always do X for me"
• "Never do Y"
• "My style is..."

Feature requests (→ FEATURE_REQUESTS.md):

• "Can you also..."
• "I wish you could..."
• "Is there a way to..."

Errors (→ ERRORS.md):

• Non-zero exit codes
• Exceptions or stack traces
• Timeout or connection failure

Ignore (don't log):

• One-time instructions ("do X now")
• Pure context ("in this file...")
• Hypotheticals ("what if...")

Memory Tiers

Tier	Location	Size limit	Behavior
RAW	.learnings/	Unlimited	Intake only, not auto-loaded
HOT	.self-improving/HOT.md	≤80 lines	Always loaded at session start
WARM	.self-improving/domains/, projects/	≤200 lines each	Load on context match
COLD	.self-improving/archive/	Unlimited	Load on explicit query

Conflict Resolution

When patterns contradict:

1. Most specific wins: project > domain > HOT/global.
2. Same level: most recent wins.
3. If ambiguous: ask user.

Promotion Targets

When a learning is stable enough for permanent workspace memory:

Learning type	Promote to	Example
Behavioral patterns	SOUL.md	"Be concise, avoid disclaimers"
Workflow improvements	AGENTS.md	"Spawn sub-agents for long tasks"
Tool gotchas	TOOLS.md	"Git push needs auth first"
User preferences/decisions	MEMORY.md	"Basim prefers Indonesian for casual chat"

Mark promoted entries as Status: promoted with Promoted-To: <file>.

Transparency

• When applying a learned pattern, cite the source: (from HOT.md) or (from domains/coding.md:15).
• On "memory stats" request, report entry counts per tier.
• On "what have you learned?" request, show recent corrections and HOT entries.

Security Boundaries

• Never store credentials, API keys, tokens, or passwords.
• Never store health data or sensitive personal information.
• Never store third-party private data.
• Redact secrets in error logs — use [REDACTED] placeholders.
• Only write to memory files in private/local workspace sessions.

Workspace Layout

See references/workspace-layout.md for the complete directory structure and file descriptions.

Resources

scripts/

• init-workspace.sh — Create .learnings/ and .self-improving/ directories with template files.

references/

• logging-format.md — Entry format for learnings, errors, and feature requests.
• promotion-rules.md — Full promotion, demotion, and archival rules.
• heartbeat-review.md — Heartbeat review procedure and state tracking.
• workspace-layout.md — Complete directory structure reference.

assets/

• Template files copied by init-workspace.sh into the workspace.