improvement-orchestrator当需要一键跑完「生成→评分→评估→执行→门禁」全流程、失败后自动重试、或批量改进多个 skill 时使用。不用于单独评估 skill 质量（用 improvement-learner）或手动打分（用 improvement-discriminator）。
Install via ClawdBot CLI:
clawdbot install lanyasheng/improvement-orchestratorGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Apr 30, 2026
An AI development team uses the orchestrator to automatically run the full improvement cycle on a new skill, including generation, scoring, evaluation, execution, and gate checks, with retry on failure. This ensures robust skill upgrades without manual intervention.
A company maintaining a library of AI skills needs to improve several skills simultaneously. The orchestrator coordinates the pipeline across multiple targets, handling retries and producing a consolidated report of outcomes.
An AI agent leverages the orchestrator to periodically run a self-improvement loop, analyzing its own performance traces and refining its skills to adapt to new tasks or fix regressions, enhancing autonomy.
A DevOps team integrates the orchestrator into their CI/CD pipeline to ensure that any proposed skill change passes a comprehensive 6-layer gate before deployment, reducing risk of faulty updates.
Offer a service that continuously improves client skills using the orchestrator pipeline, charging a subscription fee per skill per month. Automates quality assurance and performance tuning.
License the orchestrator as part of an enterprise AI platform, allowing internal teams to automate skill improvements. Generate revenue through upfront licensing and annual maintenance fees.
Provide consulting to integrate the orchestrator into existing AI workflows, tailoring retry logic and gates. Charge a one-time integration fee plus ongoing support retainer.
💬 Integration Tip
Start by running the pipeline on a single non-critical skill to validate the state-root and retry behavior before scaling to batch improvements.
Scored Apr 30, 2026
Meta-skill for AI agent self-improvement. Analyzes runtime logs to detect error patterns, regressions, and inefficiencies, then generates structured improvem...
Stop waiting for prompts. Keep working.
Turn OpenClaw into a learning-loop agent with seeded workspace rules, skill promotion, reflective memory, and proactive maintenance.
Local Python orchestration skill: multi-agent workflows via shared blackboard file, permission gating, token budget scripts, and persistent project context....
Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.