/self-improvement

name: self-improvement
description: "Captures learnings, errors, corrections, and feature requests to enable continuous improvement. Use when: (1) User corrects Claude ('No, that's wrong...', 'Actually...'), (2) User requests a capability that doesn't exist, (3) Claude realizes its knowledge is outdated or incorrect, (4) A better approach is discovered for a recurring task, (5) Receiving a Handoff block from self-healing (a recurring verified heal with Recurrence-Count at least 3) to distill into a memory file or new skill. For ACTIVE runtime failures where the agent needs to apply and verify a fix mid-task, use `self-healing` instead (it files HEAL- entries with proof; self-improvement promotes accumulated patterns). Also review learnings before major tasks. For CI-only/headless learning capture, use self-improvement-ci."

Self-Improvement Skill

Install

gh skill install pskoett/pskoett-skills self-improvement

For CI-only execution, use:

gh skill install pskoett/pskoett-skills self-improvement-ci

Fallback using the Agent Skills CLI:

npx skills add pskoett/pskoett-skills/skills/self-improvement
npx skills add pskoett/pskoett-skills/skills/self-improvement-ci

Log learnings and errors to markdown files for continuous improvement. Coding agents can later process these into fixes, and important learnings get promoted to project memory.

**Pair with [`self-healing`](../self-healing/SKILL.md):** self-healing is the active runtime recovery primitive — it diagnoses, patches, verifies, and files `HEAL-` entries to `.learnings/HEALS.md` when something breaks mid-task. Self-improvement (this skill) is the passive accumulation and promotion layer — it logs corrections, knowledge gaps, and feature requests, and promotes recurring heal handoffs to permanent memory. They share `.learnings/` but write to different files; verify discipline lives in self-healing, promotion logic lives here.

Quick Reference

| Situation | Action | |-----------|--------| | Active failure mid-task — agent needs to fix it now | **Use `self-healing` instead** (files verified HEAL- to `.learnings/HEALS.md`) | | Command/operation failed in the past (not actively healing) | Log to `.learnings/ERRORS.md` | | User corrects you | Log to `.learnings/LEARNINGS.md` with category `correction` | | User wants missing feature | Log to `.learnings/FEATURE_REQUESTS.md` | | API/external tool fails | Log to `.learnings/ERRORS.md` with integration details | | Self-healing Handoff block meets promotion rule (see Promotion Rule below) | Promote the Distilled Rule to `CLAUDE.md` / `AGENTS.md` / new skill | | Knowledge was outdated | Log to `.learnings/LEARNINGS.md` with category `knowledge_gap` | | Found better approach | Log to `.learnings/LEARNINGS.md` with category `best_practice` | | Simplify/Harden recurring patterns | Log/update `.learnings/LEARNINGS.md` with `Source: simplify-and-harden` and a stable `Pattern-Key` | | Similar to existing entry | Link with `**See Also**`, consider priority bump | | Broadly applicable learning | Promote to `CLAUDE.md`, `AGENTS.md`, and/or `.github/copilot-instructions.md` | | OpenClaw workspace targets (SOUL.md, TOOLS.md) | See `references/openclaw-integration.md` |

Setup

Create `.learnings/` directory in project root if it doesn't exist:

mkdir -p .learnings

Copy the file templates from `assets/` (`LEARNINGS.md`, `ERRORS.md`, `FEATURE_REQUESTS.md`) or create files with headers.

Logging Format

Learning Entry

Append to `.learnings/LEARNINGS.md`:

## [LRN-YYYYMMDD-XXX] category

**Logged**: ISO-8601 timestamp
**Priority**: low | medium | high | critical
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Summary
One-line description of what was learned

### Details
Full context: what happened, what was wrong, what's correct

### Suggested Action
Specific fix or improvement to make

### Metadata
- Source: conversation | error | user_feedback
- Related Files: path/to/file.ext
- Tags: tag1, tag2
- See Also: LRN-20250110-001 (if related to existing entry)
- Pattern-Key: simplify.dead_code | harden.input_validation (optional, for recurring-pattern tracking)
- Recurrence-Count: 1 (optional)
- First-Seen: 2025-01-15 (optional)
- Last-Seen: 2025-01-15 (optional)

---

Error Entry

Append to `.learnings/ERRORS.md`:

## [ERR-YYYYMMDD-XXX] skill_or_command_name

**Logged**: ISO-8601 timestamp
**Priority**: high
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Summary
Brief description of what failed

### Error

Actual error message or output

### Context
- Command/operation attempted
- Input or parameters used
- Environment details if relevant

### Suggested Fix
If identifiable, what might resolve this

### Metadata
- Reproducible: yes | no | unknown
- Related Files: path/to/file.ext
- See Also: ERR-20250110-001 (if recurring)

---

Feature Request Entry

Append to `.learnings/FEATURE_REQUESTS.md`:

## [FEAT-YYYYMMDD-XXX] capability_name

**Logged**: ISO-8601 timestamp
**Priority**: medium
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Requested Capability
What the user wanted to do

### User Context
Why they needed it, what problem they're solving

### Complexity Estimate
simple | medium | complex

### Suggested Implementation
How this could be built, what it might extend

### Metadata
- Frequency: first_time | recurring
- Related Features: existing_feature_name

---

ID Generation

Format: `TYPE-YYYYMMDD-XXX`

• TYPE: `LRN` (learning), `ERR` (error), `FEAT` (feature)
• YYYYMMDD: Current date
• XXX: Sequential number or random 3 chars (e.g., `001`, `A7B`)

Examples: `LRN-20250115-001`, `ERR-20250115-A3F`, `FEAT-20250115-002`

Resolving Entries

When an issue is fixed, update the entry:

1. Change `**Status**: pending` → `**Status**: resolved` 2. Add resolution