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Self Improvement Tianjin
作者
tianjin-ren
· GitHub ↗
· v1.0.1
· MIT-0
198
总下载
0
收藏
1
当前安装
2
版本数
在 OpenClaw 中安装
/install self-improvement-tianjin
功能描述
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
安全使用建议
This skill appears to do what it claims: collect and promote learnings via local files and optional hooks. Before enabling hooks or running scripts, review the shipped scripts (activator.sh, error-detector.sh, extract-skill.sh, handler.js/ts) to confirm you’re comfortable with them running in your environment. Pay attention to: (1) Naming inconsistencies in docs/paths (e.g., 'self-improving-agent' vs 'self-improvement-tianjin') — ensure you copy to the intended directory; (2) Hooks run with the agent's filesystem permissions and error-detector reads CLAUDE_TOOL_OUTPUT (which can contain command output that may be sensitive) — only enable if you’re okay with that local data being processed; (3) extract-skill.sh will create files under the current workspace (it contains checks to avoid absolute/parent dirs — still review intended output dir). If you plan to install from the referenced GitHub repo, verify the repository URL and contents match the packaged files. If you prefer minimal risk, use the manual workflow (create .learnings/ and copy templates) without enabling the automatic hooks.
功能分析
Type: OpenClaw Skill
Name: self-improvement-tianjin
Version: 1.0.1
The bundle implements a 'self-improvement' workflow that allows AI agents to log errors, corrections, and learnings to local markdown files within a `.learnings/` directory. The included bash scripts (scripts/activator.sh, scripts/error-detector.sh, and scripts/extract-skill.sh) are standard utilities for context injection and file scaffolding; notably, extract-skill.sh includes basic security checks to prevent path traversal. The OpenClaw hooks (hooks/openclaw/handler.js/ts) are used legitimately to inject reminders into the agent's bootstrap process, and no evidence of data exfiltration, malicious execution, or harmful prompt injection was found.
能力评估
Purpose & Capability
The skill's name/description (capture learnings, errors, promote to workspace) match the included artifacts: logging templates, hook handler, activator/error-detector scripts, and an extraction helper. The presence of hook scripts and a skill-extraction script is expected for this purpose. Minor naming inconsistencies exist (registry slug/version vs SKILL.md name vs example install paths: 'self-improvement-tianjin' / 'self-improvement' / 'self-improving-agent'), which are likely bookkeeping inconsistencies but not functionally harmful.
Instruction Scope
SKILL.md instructs creating .learnings files, copying/enabling an OpenClaw hook, and optionally registering scripts as hooks. The scripts only read local tool output (error-detector reads CLAUDE_TOOL_OUTPUT) and append virtual bootstrap files via the hook handler; they do not transmit data externally. The instructions do reference workspace paths (e.g., ~/.openclaw) and recommend copying files to those locations — expected for integration but requires user action/consent.
Install Mechanism
There is no automatic install spec; installation is manual (git clone or clawdhub). All shipped scripts are plain shell/TS/JS files and use local filesystem operations. No remote downloads or opaque installers are used. This is low-to-moderate risk but appropriate for a local integration skill.
Credentials
The skill declares no required env vars or credentials. The error-detector script reads CLAUDE_TOOL_OUTPUT (an agent-provided runtime variable) — that is appropriate for detecting command failures. No unrelated secrets or cloud credentials are requested.
Persistence & Privilege
always:false and disable-model-invocation:false (normal). Hooks are optional and must be enabled by the user; enabling them will cause the scripts to run with the same permissions as the agent process. This is expected for hooks, but users should be aware that hook scripts run locally with agent permissions.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install self-improvement-tianjin - 安装完成后，直接呼叫该 Skill 的名称或使用
/self-improvement-tianjin触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.1
- Metadata updated in _meta.json; no changes made to functionality or documentation.
- Version incremented to 1.0.1.
v1.0.0
Initial release of the self-improvement skill for OpenClaw and generic coding agents.
- Provides a structured workflow for logging errors, learnings, and feature requests to markdown files for continuous improvement.
- Outlines clear logging formats and promotion targets for broadly applicable learnings (e.g., SOUL.md, AGENTS.md, TOOLS.md).
- Includes detailed setup instructions for both OpenClaw and agent-agnostic environments.
- Introduces standardized log entry formats with ID generation and resolution tracking.
- Supports inter-session communication and hook-based reminders within OpenClaw.
元数据
常见问题
Self Improvement Tianjin 是什么？
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 198 次。
如何安装 Self Improvement Tianjin？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install self-improvement-tianjin」即可一键安装，无需额外配置。
Self Improvement Tianjin 是免费的吗？
是的，Self Improvement Tianjin 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Self Improvement Tianjin 支持哪些平台？
Self Improvement Tianjin 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Self Improvement Tianjin？
由 tianjin-ren（@tianjin-ren）开发并维护，当前版本 v1.0.1。
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