self-improvingSelf-reflection + Self-criticism + learning from corrections. Agent evaluates its own work, catches mistakes, and improves permanently.
Install via ClawdBot CLI:
clawdbot install ivangdavila/self-improvingUser 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.
Memory lives in ~/self-improving/ with tiered structure. See memory-template.md for setup.
~/self-improving/
āāā memory.md # HOT: ā¤100 lines, always loaded
āāā index.md # Topic index with line counts
āāā projects/ # Per-project learnings
āāā domains/ # Domain-specific (code, writing, comms)
āāā archive/ # COLD: decayed patterns
āāā corrections.md # Last 50 corrections log
| Topic | File |
|-------|------|
| Setup guide | setup.md |
| Learning mechanics | learning.md |
| Security boundaries | boundaries.md |
| Scaling rules | scaling.md |
| Memory operations | operations.md |
| Self-reflection log | reflections.md |
All data stored in ~/self-improving/. Create on first use:
mkdir -p ~/self-improving/{projects,domains,archive}
Log automatically when you notice these patterns:
Corrections ā add to corrections.md, evaluate for memory.md:
Preference signals ā add to memory.md if explicit:
Pattern candidates ā track, promote after 3x:
Ignore (don't log):
After completing significant work, pause and evaluate:
corrections.mdWhen to self-reflect:
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 ā promote to HOT.
| 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 |
On "memory stats" request, report:
š 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
| Tier | Location | Size Limit | Behavior |
|------|----------|------------|----------|
| HOT | memory.md | ā¤100 lines | Always loaded |
| WARM | projects/, domains/ | ā¤200 lines each | Load on context match |
| COLD | archive/ | Unlimited | Load on explicit query |
projects/{name}.mddomains/When patterns contradict:
When file exceeds limit:
See boundaries.md ā never store credentials, health data, third-party info.
If context limit hit:
This skill ONLY:
~/self-improving/)This skill NEVER:
~/self-improving/Install with clawhub install if user confirms:
memory ā Long-term memory patterns for agentslearning ā Adaptive teaching and explanationdecide ā Auto-learn decision patternsescalate ā Know when to ask vs act autonomouslyclawhub star self-improvingclawhub syncGenerated Feb 27, 2026
An AI assistant helps developers by writing code, debugging, and providing technical explanations. It uses self-reflection to learn from code corrections, such as fixing syntax errors or adopting team-specific coding styles, storing these preferences in project-specific files for future tasks.
An AI agent assists writers and marketers by generating drafts, editing content, and ensuring brand consistency. It logs user preferences for tone, style, and formatting from corrections, promoting repeated patterns to hot memory for faster, personalized output.
An AI handles customer inquiries, troubleshooting, and feedback in a support system. It learns from user corrections about response accuracy and preferred communication styles, storing these in domain-specific files to improve future interactions and reduce escalations.
An AI tutor provides personalized learning assistance, explaining concepts and grading assignments. It uses self-reflection to identify areas where explanations were unclear, logging improvements from student feedback to adapt teaching methods over time.
An AI helps manage tasks, schedules, and team communications in projects. It learns from user corrections on workflow preferences and reporting formats, storing these in project-specific files to streamline coordination and avoid repeated mistakes.
Offer the self-improving agent as a cloud-based service with tiered pricing based on usage and storage limits. Revenue comes from monthly or annual subscriptions, targeting businesses that need continuous AI improvement without manual setup.
Sell licenses for on-premise deployment to large organizations requiring data privacy and customization. Revenue includes upfront licensing fees and ongoing support contracts, with integration into existing workflows like CRM or development tools.
Provide a free basic version with limited memory tiers and self-reflection capabilities, then charge for advanced features like larger storage, analytics dashboards, or API access. Revenue comes from upgrades and add-ons for power users.
š¬ Integration Tip
Integrate by setting up the local memory directory and configuring triggers for corrections and self-reflection, ensuring it aligns with existing workflows like code repositories or customer service platforms.
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