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Install in OpenClaw
/install self-learning-skill
Description
Continuously identify knowledge gaps, proactively learn and apply new skills, regularly review progress, and iteratively improve technical and project abilit...
Usage Guidance
This skill's content mostly matches a 'self-learning' assistant, but it also contains explicit instructions to search for credentials and to perform publishing actions (GitHub/ClawHub) without declaring or explaining required access. Before installing or enabling autonomous use: 1) Ask the author to explicitly state what files, env vars, or commands the skill will access and why. 2) If you run it, prefer user-invocable only (disable autonomous invocation) or run in a sandboxed account that has no sensitive tokens. 3) Inspect or sanitize any referenced token paths (~/.github-token, ~/.openclaw/, env) and remove/rotate secrets you don't want scanned. 4) If you need publishing features, prefer giving minimal, dedicated credentials (least privilege) rather than allowing broad filesystem or environment scanning. 5) If unclear, do not enable always-on/autonomous execution and test in an isolated environment first.
Capability Analysis
Type: OpenClaw Skill
Name: self-learning-skill
Version: 3.0.2
The skill bundle implements a 'self-learning' system that directs the AI agent to act autonomously ('not waiting for instructions') and proactively search for authentication tokens across multiple sensitive filesystem locations (e.g., `~/.github-token`, `~/.openclaw/`) and environment variables. While these behaviors are framed as improvements to the agent's deployment reliability and problem-solving capabilities in SKILL.md and EXAMPLES.md, they establish a pattern of behavior identical to credential harvesting. The combination of autonomous execution directives and specific instructions to locate and use sensitive secrets without direct user oversight represents a significant security risk, although no explicit exfiltration endpoints were identified.
Capability Assessment
Purpose & Capability
The skill claims to be a self-learning/iteration assistant and indeed provides processes for daily/weekly learning, retrospectives, and publishing checks. However, many examples and remediation cases explicitly reference publishing workflows (GitHub/ClawHub), multi-location token searches (~/.github-token, ~/.openclaw/, env), and CLI commands — capabilities that go beyond passive 'learning' and imply access to local credentials and tooling. That capability is not documented as required in the registry metadata.
Instruction Scope
SKILL.md and associated docs instruct behaviors that may lead the agent to read local files and environment variables (e.g., '多位置搜索 (~/.github-token, ~/.openclaw/, env)', 'clawhub login', 'cat learning/progress-tracker.md'), and the skill explicitly endorses proactivity ('不等待指令，主动发现知识盲区'). Those instructions give the agent broad discretion to probe system state and credentials even though no such access is declared or scoped.
Install Mechanism
This is an instruction-only skill with no install spec, no downloaded artifacts, and no code files executed at install time — lowest risk by install mechanism. The repository-like README links are informational only.
Credentials
The registry shows no required env vars or credentials, yet the documentation repeatedly references searching for tokens in common file locations and environment ('~/.github-token', env) and using CLIs for publishing. Asking for or searching credentials is disproportionate to the declared metadata and should be explicitly declared and justified.
Persistence & Privilege
always:false and user-invocable:true (defaults) — good. However the skill's emphasis on autonomous proactivity combined with instructions that could access local credentials increases the risk if the agent is allowed to invoke the skill autonomously. Consider restricting autonomous invocation or clarifying limits.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install self-learning-skill - After installation, invoke the skill by name or use
/self-learning-skill - Provide required inputs per the skill's parameter spec and get structured output
Version History
v3.0.2
清理临时文件，只保留核心功能文档
v3.0.1
修正 SKILL.md 头部格式，确保技能正确加载
v3.0.0
Self-Learning Skill v3.0.0
- Added "举一反三" (analogy-based/generalization) learning system with new thinking models and implementation steps
- Introduced point-line-plane-body, analogy, reverse, and system thinking frameworks
- New checklists, practical examples, and weekly exercises for analogy/generalization capability
- Enhanced knowledge base with problem patterns, general solutions, and knowledge network diagrams
- Updated capability matrix and review templates to include "举一反三" as a key dimension
v2.0.0
Self-Learning Skill v2.0.0 introduces a systematic “never repeat mistakes” error learning and correction framework.
- Added a comprehensive error learning & correction system, including error classification, recording templates, and a 5 Whys analysis method.
- Introduced routine error review processes: post-task, weekly, and monthly error trend analysis.
- Enhanced ability evaluation matrix with new dimensions for error prevention and error-based learning.
- Established standardized preventive checklists and a living error database for tracking and eliminating repeat issues.
- Removed redundant publishing and report files; added centralized error log documentation.
- Updated all guides and learning processes to integrate error-driven self-improvement.
v1.0.0
Self-Learning Skill v1.0.0 – Initial Release
- Introduces a comprehensive self-learning and iteration framework focused on continuous skill improvement for technical projects.
- Provides structured routines for post-task reviews, daily summaries, and weekly/monthly capability assessments.
- Details proactive learning channels, including GitHub, technical sites, official docs, and benchmarking top products.
- Implements mechanisms for identifying skill gaps, collecting user feedback, and quantifying progress.
- Supplies templates and checklists for learning notes, knowledge base organization, and project-driven study.
- Emphasizes user control and regular quality checks to ensure learning is practical, targeted, and adaptive.
Metadata
Frequently Asked Questions
What is Self-Learning Skill?
Continuously identify knowledge gaps, proactively learn and apply new skills, regularly review progress, and iteratively improve technical and project abilit... It is an AI Agent Skill for Claude Code / OpenClaw, with 1572 downloads so far.
How do I install Self-Learning Skill?
Run "/install self-learning-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Self-Learning Skill free?
Yes, Self-Learning Skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Self-Learning Skill support?
Self-Learning Skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Self-Learning Skill?
It is built and maintained by davidme6 (@davidme6); the current version is v3.0.2.
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