self-improving-agent-python
v1.0.1Implement a 3-layer self-improvement process for agents to evaluate tasks, learn from outcomes, optimize performance, and share knowledge across agents.
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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OpenClaw
Benign
high confidencePurpose & Capability
Name/description describe a local self-improvement system; the provided Python scripts implement evaluation, lesson recording, optimization, and cross-agent sync via local files under the workspace directory—this matches the stated purpose.
Instruction Scope
SKILL.md instructs running the included scripts and documents the filesystem layout. The runtime instructions and scripts only read/write local JSON files and do not attempt to access network endpoints, credentials, or unrelated system files.
Install Mechanism
There is no install spec and no external downloads. The skill is distributed as plain Python scripts (no package installation or remote fetch), which is low-risk from an install perspective.
Credentials
The skill requests no environment variables or credentials. It does assume a WorkBuddy-style workspace directory (DEFAULT_OPENCLAW_DIR = ~/.workbuddy) and will operate on files under that hierarchy; no secrets are required or requested.
Persistence & Privilege
always:false and no autonomous-model restrictions. However, sync_learning.py enumerates all workspaces under ~/.workbuddy and copies collective-wisdom.json into each workspace's shared-context/self-improvement directory — this intentionally modifies other workspace directories on the same host. This behavior matches the 'cross-agent sharing' purpose but is a persistent file-write capability that you should consider before using on multi-user or shared machines.
Assessment
This skill appears to do what it says: it stores evaluations, lessons, and optimization plans as JSON files in your WorkBuddy workspace and can copy a shared 'collective-wisdom.json' into every workspace under ~/.workbuddy. Before installing or running it: (1) confirm you are okay with the skill creating and writing files under ~/.workbuddy and across any workspace-* directories on the machine, (2) inspect the included scripts (they are all present and readable) and backup any existing shared-context/ self-improvement files you care about, (3) if you run sync_learning.py on a multi-user or shared machine, be aware it will write into other workspaces under ~/.workbuddy, and (4) run the scripts as a non-privileged user and in an isolated workspace if you want to limit impact. No network endpoints or credentials are used by the skill.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.