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self evolving agent
by
Range King
· GitHub ↗
· v1.1.0
· MIT-0
260
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2
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Install in OpenClaw
/install self-evo-agent
Description
Build a goal-driven self-learning loop for OpenClaw and coding agents. Use when the agent should not only log mistakes, but diagnose capability gaps, maintai...
Usage Guidance
This skill appears to be what it says: a workspace-based capability-evolution system. The main risk is that it includes shell/Python scripts and a hook handler that can run on your machine and may call models or networked APIs. Before installing or enabling hooks: 1) open and review scripts/* (bootstrap-workspace.sh, run-evals.py, run-benchmark.py, error-detector.sh, activator.sh, migrate-self-improving.py) and hooks/openclaw/handler.ts for network calls, subprocess execs, or credential reads; 2) check for expected env vars (OPENAI_API_KEY or similar) or hardcoded endpoints; 3) back up your existing ~/.openclaw/workspace/.learnings and other workspace files; 4) prefer manual cloning and local inspection rather than asking the agent to fetch/enable the skill automatically; 5) run scripts in a sandboxed/dev workspace first (not on production data); and 6) only enable the hook after you are satisfied no unexpected network exfiltration or privilege changes occur. If you want, provide the contents of the scripts and handler.ts and I can flag any suspicious code patterns specifically.
Capability Analysis
Type: OpenClaw Skill
Name: self-evo-agent
Version: 1.1.0
This skill bundle implements a highly autonomous 'self-evolving' loop that instructs the agent to diagnose its own capability gaps and 'promote' new behavioral rules into persistent policy files such as SOUL.md and AGENTS.md. While the stated intent is self-improvement, the mechanism essentially allows the agent to rewrite its own governing instructions over time. The bundle includes several scripts (run-benchmark.py, run-evals.py, bootstrap-workspace.sh) that perform file system operations, manage symlinks in ~/.codex/skills, and execute local commands like 'codex exec'. The combination of autonomous self-modification of core instructions and script-based environment manipulation represents a significant attack surface for unintended behavior or self-exploitation.
Capability Assessment
Purpose & Capability
The name, README, SKILL.md and file layout align: the skill expects to read/write an OpenClaw workspace, maintain ledgers, generate training units, and optionally provide hooks. Those capabilities reasonably require the files and ledgers the repo contains.
Instruction Scope
SKILL.md explicitly instructs the agent to read and update workspace files (assets/, modules/, system/), run light or full loops, and optionally enable hooks. That behavior is in‑scope for a capability‑evolution skill, but it also instructs running supplied scripts and copying hook files into ~/.openclaw which grants the skill the ability to persist and act across sessions — you should review the scripts and hook handler for unexpected actions before enabling.
Install Mechanism
There is no formal install spec (instruction-only), but the repo includes executable scripts and an OpenClaw hook. Installation options point to GitHub or a local copy (both reasonable). The GitHub source is an expected host; no arbitrary shorteners or third‑party binary downloads are referenced. Still, because the package contains scripts that may be executed locally, inspect them prior to running.
Credentials
Registry metadata declares no required env vars, but repository artifacts (agents/openai.yaml, benchmark scripts, run-benchmark.py, run-evals.py, and handler.ts) suggest model-in-the-loop or external API use that typically requires credentials (e.g., OPENAI_API_KEY) or network access. The skill does not document required credentials or network endpoints — this mismatch is a risk and should be validated by reading the scripts and hook code.
Persistence & Privilege
always is false and hooks are optional. The skill asks to bootstrap a persistent workspace (~/.openclaw/workspace/.evolution) and optionally enable a hook, which is appropriate for a memory/evolution skill. There is no claim it will force-enable itself or modify other skills' configs.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install self-evo-agent - After installation, invoke the skill by name or use
/self-evo-agent - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
Add migration support and light/full-loop guidance
v1.0.0
Initial release of self-evolving-agent 1.0.0:
- Refactored from passive self-improvement into an explicit capability evolution system.
- Introduced capability mapping, proactive learning agenda, and structured training units.
- Added explicit evaluation ladder (recorded → understood → practiced → passed → generalized → promoted).
- Established clear file map for orchestration, modules, and learning assets.
- Provided step-by-step closed-loop workflow for classification, execution, reflection, and promotion.
- Replaced previous implementation with a lightweight, modular structure focused on diagnosis and validated learning.
Metadata
Frequently Asked Questions
What is self evolving agent?
Build a goal-driven self-learning loop for OpenClaw and coding agents. Use when the agent should not only log mistakes, but diagnose capability gaps, maintai... It is an AI Agent Skill for Claude Code / OpenClaw, with 260 downloads so far.
How do I install self evolving agent?
Run "/install self-evo-agent" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is self evolving agent free?
Yes, self evolving agent is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does self evolving agent support?
self evolving agent is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created self evolving agent?
It is built and maintained by Range King (@rangeking); the current version is v1.1.0.
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