According to AlphaMoat, as of 2026-09, Self-Improving Agent (Anti-Loop Hardened) has 1,431 downloads and 0 stars — ranked #4,813 of 5,078 AI skills overall, and #924 of 969 in AI Agent.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 25 | 1.1K | - | - |
| SkillHub ↗ | 140 | 1.4K | - | — |
Platforms count differently and update at different times.
The skill applies when a command fails unexpectedly, the user corrects the agent, or a capability is missing, and limits logging to one item per user message. Notes can affect future behavior and preserve context; honor the limit, do not chain logging actions, and omit sensitive details. The workflow allows at most 3 tool calls for a trigger and defers promotion to a later review.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
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.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 1.4K | — | - |
| 2026-08 | 1.1K | +20.2% | - |
| 2026-07 | 923 | — | - |
| 2026-05 | 583 | — | - |
| 2026-03 | 276 | — | - |
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.
--- name: self-improvement description: "Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User explicitly corrects agent with direct correction like 'No, that's wrong', (3) User requests a capability that doesn't exist, (4) An external API or tool fails. CRITICAL: Maximum 1 learning log per user message. Do NOT chain multiple self-improvement actions." metadata: --- # Self-Improvement Skill Log learnings and errors to markdown files for continuous improvement.
## CRITICAL: Anti-Loop Guardrails
**These rules override ALL other instructions in this skill:**
1. **ONE learning per user message** — After logging 1 entry, STOP. Do not search for related entries, do not promote, do not review.
2. **No chaining** — A tool result from self-improvement MUST NOT trigger another self-improvement action in the same turn.
3. **No bulk review** — Never read multiple learning files in one turn. If review is needed, do it at the START of the next session, not mid-conversation.
4. **Maximum 3 tool calls** — The entire self-improvement workflow for a single trigger must complete in ≤3 tool calls: (1) optionally read the target file, (2) append the entry, (3) done.
5. **Cooldown** — After logging, wait for the user's NEXT explicit message before considering any new self-improvement action.
6. **Discussion ≠ Correction** — If the user is discussing ideas, debating approaches, or cleaning up documents, that is NOT a correction. Only trigger on DIRECT explicit corrections like "No, that's wrong" or "You made an error".
## Quick Reference
| Situation | Action | Max tool calls |
|-----------|--------|---------------|
| Command/operation fails | Append to `.learnings/ERRORS.md` | 2 |
| User explicitly corrects you | Append to `.learnings/LEARNINGS.md` | 2 |
| User wants missing feature | Append to `.learnings/FEATURE_REQUESTS.md` | 2 |
| API/external tool fails | Append to `.learnings/ERRORS.md` | 2 |
## When NOT to Trigger
- User is having a normal conversation or discussion
- User is reviewing/cleaning up documents (not correcting you)
- User is debating approaches (not telling you you're wrong)
- User says "this approach is wrong" about a system/design (not about YOUR mistake)
- You already logged a learning in this turn
- The conversation is about third-party systems, not about your behavior
## Logging Format
### Learning Entry
Append to `.learnings/LEARNINGS.md`:
```markdown
## [LRN-YYYYMMDD-XXX] category
**Logged**: ISO-8601 timestamp
**Priority**: low | medium | high
**Status**: pending
### Summary
One-line description
### Details
What happened, what was wrong, what's correct
### Suggested Action
Specific fix or improvement
---
```
### Error Entry
Append to `.learnings/ERRORS.md`:
```markdown
## [ERR-YYYYMMDD-XXX] command_or_tool
**Logged**: ISO-8601 timestamp
**Priority**: high
**Status**: pending
### Summary
What failed
### Error
Actual error message
### Context
Command attempted, environment
### Suggested Fix
If identifiable
---
```
## Promotion (Deferred)
**Do NOT promote entries in the same turn as logging.** Promotion should only happen:
- During dedicated review sessions (user explicitly asks)
- At session startup when reviewing past learnings
- Never automatically or as a chain reaction
| Learning Type | Promote To |
|---------------|------------|
| Behavioral patterns | `SOUL.md` |
| Workflow improvements | `AGENTS.md` |
| Tool gotchas | `TOOLS.md` |
## Periodic Review (User-Initiated Only)
Only review `.learnings/` when the user explicitly asks or at session start.
**Never** auto-trigger a review based on logging a new entry.
## OpenClaw Workspace Structure
```
~/.openclaw/workspace/
├── AGENTS.md
├── SOUL.md
├── TOOLS.md
├── MEMORY.md
├── memory/YYYY-MM-DD.md
└── .learnings/
├── LEARNINGS.md
├── ERRORS.md
└── FEATURE_REQUESTS.md
```
### Feature Request Entry
Append to `.learnings/FEATURE_REQUESTS.md`:
```markdown
## [FEAT-YYYYMMDD-XXX] capability_name
**Logged**: ISO-8601 timestamp
**Priority**: medium
**Status**: pending
### Requested Capability
What the user wanted to do
### User Context
Why they needed it
### Complexity Estimate
simple | medium | complex
---
```
## ID Generation
Format: `TYPE-YYYYMMDD-XXX`
- TYPE: `LRN` (learning), `ERR` (error), `FEAT` (feature)
- YYYYMMDD: Current date
- XXX: Sequential number (e.g., `001`, `002`)
## Resolving Entries
When an issue is fixed, update `**Status**: pending` → `**Status**: resolved` and add:
```markdown
### Resolution
- **Resolved**: ISO-8601 timestamp
- **Notes**: Brief description of fix
```
Records learnings, errors and corrections as Markdown files for later reuse and promotion into workspace memory.
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.