automation-skill advanced active

Self Improving Agent

One-pass answers miss nuance and contain errors you won't catch until too late. Iteration takes manual effort you don't have. The openclaw self improving agent critiques and rewrites until quality passes.

openclaw self-improving meta-learning feedback optimization autonomous

What breaks without openclaw self improving agent

Single-pass errors shipped as final answers. No quality gate before delivery. High-stakes tasks flying blind.

→
Iteratively refined output × 285-star self-critique loop ÷ 15–25 minutes ÷ capped iteration cost = analysis you can trust without manual review.

openclaw self improving agent — what it actually does

01
Enables multi-pass answer refinement with self-critique loops inside OpenClaw.
02
Prefixes any task with /improve to activate automatic improvement cycles.
03
Caps iterations with SELF_IMPROVE_MAX_ITERATIONS to control token spend.
04
Shows iteration diffs in the log to make improvement steps transparent.

Security check — openclaw self improving agent

Privacy score: 7/10 — accesses connected platform APIs only. Lock it: review OAuth scopes before install, confirm macOS, Linux; OpenClaw ≥1.0 compatibility.

Quick start — openclaw self improving agent in 15–25 minutes

Setup time: 15–25 minutes

!
You need:
  • OpenClaw core
  • sufficient API quota for multi-pass calls

Install the package:

# Install via ClawhHub
clawhub install pskoett/self-improving-agent
1
Install the skill
2
Set SELF_IMPROVE_MAX_ITERATIONS=3 in .env
3
Prefix any task with /improve to enable self-critique
4
Review the iteration log to see improvement steps

Troubleshooting openclaw self improving agent

1
1. Each iteration doubles API token consumption — set a hard iteration cap
2
2. Diminishing returns beyond 3 iterations for most tasks

Compatibility & status

Works with: macOS, Linux; OpenClaw ≥1.0 advanced Last updated: Nov 2025 ★ 285 on GitHub MIT

Official docs →

View on GitHub →

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Self Improving Agent 1 0 11
An OpenClaw agent that improves its own SKILL.md based on usage feedback — the self-upgrading agent pattern.
Capability Evolver
An agent that evolves its own capabilities by analysing task patterns and rewriting its skill config.

Ship the first-pass answer and discover the error after the deadline. Add self-improvement now and catch mistakes before they leave the session.

Get it on GitHub →