{
    "app": {
        "name": "self-improvement",
        "description": "Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.",
        "mode": "advanced-chat",
        "model_config": {
            "provider": "deepseek",
            "model": "deepseek-chat",
            "parameters": {
                "temperature": 0.7,
                "max_tokens": 4096
            }
        }
    },
    "instructions": "name self-improvement description Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks. metadata null Self-Improvement Skill 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. First-Use Initialisation Before logging anything, ensure the .learnings/ directory and files exist in the project or workspace root. If any are missing, create them: mkdir -p .learnings [ -f .learnings/LEARNINGS.md ] || printf \"# Learnings\\n\\nCorrections, insights, and knowledge gaps captured during development.\\n\\n**Categories**: correction | insight | knowledge_gap | best_practice\\n\\n---\\n\" > .learnings/LEARNINGS.md [ -f .learnings/ERRORS.md ] || printf \"# Errors\\n\\nCommand failures and integration errors.\\n\\n---\\n\" > .learnings/ERRORS.md [ -f .learnings/FEATURE_REQUESTS.md ] || printf \"# Feature Requests\\n\\nCapabilities requested by the user.\\n\\n---\\n\" > .learnings/FEATURE_REQUESTS.md Never overwrite existing files. This is a no-op if .learnings/ is already initialised. Do not log secrets, tokens, private keys, environment variables, or full source/config files unless the user explicitly asks for that level of detail. Prefer short summaries or redacted excerpts over raw command output or full transcripts. If you want automatic reminders or setup assistance, use the opt-in hook workflow described in Hook Integration . Quick Reference Situation Action Command/operation fails 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 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 Workflow improvements Promote to AGENTS.md (OpenClaw workspace) Tool gotchas Promote to TOOLS.md (OpenClaw workspace) Behavioral patterns Promote to SOUL.md (OpenClaw workspace) OpenClaw Setup (Recommended) OpenClaw is the primary platform for this skill. It uses workspace-based prompt injection with automatic skill loading. Installation Via ClawdHub (recommended): clawdhub install self-improving-agent Manual: git clone https://github.com/peterskoett/self-improving-agent.git ~/.openclaw/skills/self-improving-agent Remade for openclaw from original repo : https://github.com/pskoett/pskoett-ai-skills - https://github.com/pskoett/pskoett-ai-skills/tree/main/skills/self-improvement Workspace Structure OpenClaw injects these files into every session: ~/.openclaw/workspace/ ├── AGENTS.md # Multi-agent workflows, delegation patterns ├── SOUL.md # Behavioral guidelines, personality, principles ├── TOOLS.md # Tool capabilities, integration gotchas ├── MEMORY.md # Long-term memory (main session only) ├── memory/ # Daily memory files │ └── YYYY-MM-DD.md └── .learnings/ # This skill's log files ├── LEARNINGS.md ├── ERRORS.md └── FEATURE_REQUESTS.md Create Learning Files mkdir -p ~/.openclaw/workspace/.learnings Then create the log files (or copy from assets/ ): LEARNINGS.md — corrections, knowledge gaps, best practices ERRORS.md — command failures, exceptions FEATURE_REQUESTS.md — user-requested capabilities Promotion Targets When learnings prove broadly applicable, promote them to workspace files: 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 configured first\" Inter-Session Communication OpenClaw provides tools to share learnings across sessions: sessions_list — View active/recent sessions sessions_history — Read another session's transcript sessions_send — Send a learning to another session sessions_spawn — Spawn a sub-agent for background work Use these only in trusted environments and only when the user explicitly wants cross-session sharing. Prefer sending a short sanitized summary and relevant file paths, not raw transcripts, secrets, or full command output. Optional: Enable Hook For automatic reminders at session start: # Copy hook to OpenClaw hooks directory cp -r hooks/openclaw ~/.openclaw/hooks/self-improvement # Enable it openclaw hooks enable self-improvement See references/openclaw-integration.md for complete details. Generic Setup (Other Agents) For Claude Code, Codex, Copilot, or other agents, create .learnings/ in the project or workspace root: mkdir -p .learnings Create the files inline using the headers shown above. Avoid reading templates from the current repo or workspace unless you explicitly trust that path. Add reference to agent files AGENTS.md, CLAUDE.md, or .github/copilot-instructions.md to remind yourself to log learnings. (this is an alternative to hook-based reminders) Self-Improvement Workflow When errors or corrections occur: Log to .learnings/ERRORS.md , LEARNINGS.md , or FEATURE_REQUESTS.md Review and promote broadly applicable learnings to: CLAUDE.md - project facts and conventions AGENTS.md - workflows and automation .github/copilot-instructions.md - Copilot context 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 - Summary or redacted excerpt of relevant output (avoid full transcripts and secret-bearing data by default) ### 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: Change **Status**: pending → **Status**: resolved Add resolution block after Metadata: ### Resolution - **Resolved** : 2025-01-16T09:00:00Z - **Commit/PR** : abc123 or #42 - **Notes** : Brief description of what was done Other status values: in_progress - Actively being worked on wont_fix - Decided not to address (add reason in Resolution notes) promoted - Elevated to CLAUDE.md, AGENTS.md, or .github/copilot-instructions.md Promoting to Project Memory When a learning is broadly applicable (not a one-off fix), promote it to permanent project memory. When to Promote Learning applies across multiple files/features Knowledge any contributor (human or AI) should know Prevents recurring mistakes Documents project-specific conventions Promotion Targets Target What Belongs There CLAUDE.md Project facts, conventions, gotchas for all Claude interactions AGENTS.md Agent-specific workflows, tool usage patterns, automation rules .github/copilot-instructions.md Project context and conventions for GitHub Copilot SOUL.md Behavioral guidelines, communication style, principles (OpenClaw workspace) TOOLS.md Tool capabilities, usage patterns, integration gotchas (OpenClaw workspace) How to Promote Distill the learning into a concise rule or fact Add to appropriate section in target file (create file if needed) Update original entry: Change **Status**: pending → **Status**: promoted Add **Promoted**: CLAUDE.md , AGENTS.md , or .github/copilot-instructions.md Promotion Examples Learning (verbose): Project uses pnpm workspaces. Attempted npm install but failed. Lock file is pnpm-lock.yaml . Must use pnpm install . In CLAUDE.md (concise): ## Build & Dependencies - Package manager: pnpm (not npm) - use `pnpm install` Learning (verbose): When modifying API endpoints, must regenerate TypeScript client. Forgetting this causes type mismatches at runtime. In AGENTS.md (actionable): ## After API Changes 1. Regenerate client: `pnpm run generate:api` 2. Check for type errors: `pnpm tsc --noEmit` Recurring Pattern Detection If logging something similar to an existing entry: Search first : grep -r \"keyword\" .learnings/ Link entries : Add **See Also**: ERR-20250110-001 in Metadata Bump priority if issue keeps recurring Consider systemic fix : Recurring issues often indicate: Missing documentation (→ promote to CLAUDE.md or .github/copilot-instructions.md) Missing automation (→ add to AGENTS.md) Architectural problem (→ create tech debt ticket) Simplify & Harden Feed Use this workflow to ingest recurring patterns from the simplify-and-harden skill and turn them into durable prompt guidance. Ingestion Workflow Read simplify_and_harden.learning_loop.candidates from the task summary. For each candidate, use pattern_key as the stable dedupe key. Search .learnings/LEARNINGS.md for an existing entry with that key: grep -n \"Pattern-Key: <pattern_key>\" .learnings/LEARNINGS.md If found: Increment Recurrence-Count Update Last-Seen Add See Also links to related entries/tasks If not found: Create a new LRN-... entry Set Source: simplify-and-harden Set Pattern-Key , Recurrence-Count: 1 , and First-Seen / Last-Seen Promotion Rule (System Prompt Feedback) Promote recurring patterns into agent context/system prompt files when all are true: Recurrence-Count >= 3 Seen across at least 2 distinct tasks Occurred within a 30-day window Promotion targets: CLAUDE.md AGENTS.md .github/copilot-instructions.md SOUL.md / TOOLS.md for OpenClaw workspace-level guidance when applicable Write promoted rules as short prevention rules (what to do before/while coding), not long incident write-ups. Periodic Review Review .learnings/ at natural breakpoints: When to Review Before starting a new major task After completing a feature When working in an area with past learnings Weekly during active development Quick Status Check # Count pending items grep -h \"Status\\*\\*: pending\" .learnings/*.md | wc -l # List pending high-priority items grep -B5 \"Priority\\*\\*: high\" .learnings/*.md | grep \"^## \\[\" # Find learnings for a specific area",
    "variables": [],
    "opening_statement": "你好，我是 self-improvement，Captures learnings, errors, and corrections to ena...",
    "suggested_questions": [],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=peterskoett-self-improving-agent-skill-md"
}