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/install my-first-test-01
Description
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
Usage Guidance
This package implements a reasonable 'self‑improvement' logging workflow (creates .learnings, optional hooks to remind the agent, and helpers to extract skills). Before installing: (1) Verify the source — the registry metadata name/slug differs from the files' internal metadata (the package appears to contain 'self-improving-agent' content but is registered as 'my-first-test-01'); confirm you trust the repository and author. (2) Review the hook scripts (activator.sh, error-detector.sh, handler.js/ts, extract-skill.sh) yourself — they run locally and will be executed with the agent's permissions if you enable hooks. (3) Be cautious about enabling PostToolUse / cross-session features: the skill suggests reading/sending other sessions' transcripts and logging tool output; do not enable those unless you trust the environment and understand the privacy implications. (4) If you install, prefer project-level, minimal setup (only UserPromptSubmit) and do not enable any global user-level hooks until tested in a safe environment; ensure hooks/scripts have appropriate filesystem permissions. (5) If you need higher assurance, ask the publisher to fix the metadata mismatch and provide a signed or canonical source URL before use.
Capability Analysis
Type: OpenClaw Skill
Name: my-first-test-01
Version: 1.0.2
The skill bundle implements a 'self-improvement' framework that allows an AI agent to log errors, user corrections, and feature requests into a local `.learnings/` directory. It includes shell scripts (`activator.sh`, `error-detector.sh`, `extract-skill.sh`) and OpenClaw hooks (`handler.js`) designed to remind the agent to capture insights or detect command failures. The code logic is transparent and aligned with its stated purpose, featuring basic path sanitization in the skill extraction script to prevent directory traversal and focusing entirely on local workspace management without any signs of data exfiltration or unauthorized remote execution.
Capability Tags
Capability Assessment
Purpose & Capability
The included files implement a 'self-improvement' / 'self-improving-agent' skill (hooks, activator, error detector, extract-skill helper) and the SKILL.md describes that purpose. However the registry metadata (skill name/slug/owner) does not match the internal SKILL.md/_meta.json references (e.g., registry lists 'my-first-test-01' but files identify 'self-improving-agent' / 'self-improvement'). This packaging/metadata mismatch is unexpected and should be verified (could be benign repackaging, but it could also be a mistaken or malicious replacement). Otherwise, the code and instructions align with the stated purpose (creating .learnings logs, injecting reminders, optional hooks).
Instruction Scope
The runtime instructions and scripts create/require writing files under workspace or user home (~/.openclaw/workspace and ~/.openclaw/hooks) and recommend enabling hooks that will run on agent lifecycle events. The references also show using cross-session APIs (sessions_history, sessions_send, sessions_spawn) which can read or send session transcripts; the SKILL.md warns to use these only in trusted environments, but the presence of those instructions increases the risk of inadvertent exposure of transcripts or command output. The error-detector script reads CLAUDE_TOOL_OUTPUT (tool output) and may cause automated reminders to be issued when errors are detected — useful but potentially sensitive if error output contains secrets. Overall the instructions grant the agent discretion to read and promote learnings across sessions; that is within the skill's purpose but requires user caution.
Install Mechanism
There is no formal install spec in the registry (instruction-only), which is lower risk. The SKILL.md suggests installing via git clone from GitHub (https://github.com/peterskoett/self-improving-agent.git) or via a 'clawdhub' command — both are normal for an open-source skill. The included scripts operate locally and the extract-skill helper defends against path traversal/absolute paths. No external downloads from untrusted hosts or archive extraction were found.
Credentials
The registry lists no required environment variables or credentials, which matches the benign-sounding purpose. However the error-detector.sh reads CLAUDE_TOOL_OUTPUT (an agent-provided env var) even though it's not declared in metadata — this is expected for hooks but should be noted. More importantly, the skill's workflow encourages logging command outputs and session transcripts into .learnings and (optionally) promoting them to shared workspace files; while the SKILL.md explicitly warns not to log secrets, the mechanism relies on the agent and user following that guidance, so there's a practical risk of sensitive data being recorded if the user or agent is not careful.
Persistence & Privilege
The skill does not request always:true and is user-invocable; hooks and scripts are opt-in and only run if the user copies/enables them in their OpenClaw/agent config. The hook handlers inject a virtual bootstrap file (reminder) but do not modify other skills or system-wide settings. Enabling user-level hooks will give the skill global effect for that user, so enabling them is a conscious, persistent choice.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install my-first-test-01 - After installation, invoke the skill by name or use
/my-first-test-01 - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
No file changes were detected in this release.
There are no updates for users in version 1.0.2.
v1.0.0
Initial release of the self-improvement skill.
- Logs learnings, errors, and feature requests to structured markdown files for continuous improvement.
- Provides initialization workflow to ensure `.learnings/` directory and required files exist without overwriting.
- Defines clear guidelines and formats for logging corrections, insights, errors, and best practices.
- Supports both OpenClaw and generic agent/project setups.
- Offers mechanisms for promoting key learnings to broader workspace memory (e.g., AGENTS.md, SOUL.md, TOOLS.md).
- Includes safety guidelines to avoid logging sensitive information by default.
Metadata
Frequently Asked Questions
What is my-first-test-01?
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau... It is an AI Agent Skill for Claude Code / OpenClaw, with 80 downloads so far.
How do I install my-first-test-01?
Run "/install my-first-test-01" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is my-first-test-01 free?
Yes, my-first-test-01 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does my-first-test-01 support?
my-first-test-01 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created my-first-test-01?
It is built and maintained by muyangsx (@muyangsx); the current version is v1.0.2.
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