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Max-Self-Improvement
by
ruiyongwang
· GitHub ↗
· v1.0.1
· MIT-0
63
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0
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0
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1
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Install in OpenClaw
/install max-self-improvement
Description
MiniMax Agent self-evolution system with 5-layer memory for continuous learning, error analysis, and persistent personalized context management.
Usage Guidance
This skill appears to implement the described learning/memory features, but there are ambiguities and privacy concerns you should resolve before installing:
1) Ask the author where memory files will be stored exactly. If they are written to /memories or any absolute system path, insist they write only inside a sandboxed skill-specific directory (e.g., under the skill bundle or a configured data directory).
2) Confirm retention and deletion policies. "Never auto-delete" preferences can accumulate sensitive data — require an explicit delete/expire mechanism and ability for the user to purge stored memories.
3) Audit what the skill logs. The ERRORS.md templates invite logging "Environment details"; verify that environment variables, secrets, tokens, or file contents will not be captured or that logs are sanitized/encrypted.
4) Run the skill in an isolated environment first (non-production account or container) and monitor where files are created when activating error-detector/activator.
5) If you need stronger assurance, request a signed source/homepage or a maintainer contact and require the code to be adjusted so all writes are confined to a clearly documented skill-local path and retention controls are exposed to the user.
Given the inconsistencies (absolute vs skill-local paths) and the potential for persistent capture of environment/context, treat this skill as potentially privacy-sensitive until the above are clarified.
Capability Analysis
Type: OpenClaw Skill
Name: max-self-improvement
Version: 1.0.1
The 'max-self-improvement' skill bundle is a framework designed to provide an AI agent with a persistent memory and self-optimization system. It uses a structured directory of Markdown files (e.g., /memories/, .learnings/) to track user preferences, task states, and error logs. The included shell scripts (activator.sh, error-detector.sh) and Python utilities (package_skill.py, validate_skill.py) are standard administrative tools for logging and maintenance, showing no signs of data exfiltration, malicious execution, or unauthorized persistence.
Capability Assessment
Purpose & Capability
The declared purpose (self-improvement, multi-layer memory, cross-session context) aligns with the provided templates and helper scripts which create and append to learning/error logs and provide memory file templates. However there is an inconsistency: the SKILL.md repeatedly references persistent paths under /memories/ (absolute-root style), while the executable scripts (activator.sh, error-detector.sh) create and write to a skill-local .learnings directory ($SKILL_DIR/.learnings). It's unclear whether memory files are intended to live inside the skill bundle, under a shared /memories directory, or elsewhere — that ambiguity matters for scope and data access.
Instruction Scope
SKILL.md instructs the agent to read/write persistent memory files (session_notes.md, user_preferences.md, patterns.md, metrics.md) and to log 'Environment details' for error entries. Those instructions give the agent explicit license to collect and persist contextual/environment details and never-auto-delete user preferences. The instructions also use absolute paths (/memories/...), which could cause writes outside the skill sandbox if followed literally. While shipped scripts are limited to the skill directory, the prose grants broader discretion to the agent to access and persist data beyond the skill's own files.
Install Mechanism
There is no install spec (instruction-only skill). The included helper scripts are simple shell/Python utilities for packaging and validation and do not download remote code. No networked install or archive extraction from arbitrary URLs is present in the package.
Credentials
The skill declares no required environment variables or external credentials. However the error logging templates and SKILL.md suggest capturing 'Environment details' and 'Environment details if relevant' in ERRORS.md entries, which could lead to accidental inclusion of environment variables or other sensitive runtime context in persistent logs. No justification is provided for retention duration (user_preferences marked '永不自动删除'), increasing privacy risk.
Persistence & Privilege
The skill is designed for persistent, cross-session memory and explicitly marks some user preferences as 'never automatically deleted.' While the skill is not forced-always and has no declared elevated privileges, persistent storage combined with the agent's normal autonomous invocation could produce long-lived data. The key risk is ambiguous storage location (skill-local vs system-wide /memories) and lack of retention/deletion controls; this increases the blast radius for accidental data exposure or accumulation of sensitive context.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install max-self-improvement - After installation, invoke the skill by name or use
/max-self-improvement - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Reference ClawHub self-improving-agent: Added .learnings system, Shell scripts, assets templates
Metadata
Frequently Asked Questions
What is Max-Self-Improvement?
MiniMax Agent self-evolution system with 5-layer memory for continuous learning, error analysis, and persistent personalized context management. It is an AI Agent Skill for Claude Code / OpenClaw, with 63 downloads so far.
How do I install Max-Self-Improvement?
Run "/install max-self-improvement" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Max-Self-Improvement free?
Yes, Max-Self-Improvement is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Max-Self-Improvement support?
Max-Self-Improvement is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Max-Self-Improvement?
It is built and maintained by ruiyongwang (@ruiyongwang); the current version is v1.0.1.
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