agent-optimizerV6.1 Agent 性能优化器 - 基于轨迹分析和奖励反馈的轻量级优化框架
Install via ClawdBot CLI:
clawdbot install sandmark78/agent-optimizerGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://github.com/openclaw/openclawAudited Apr 17, 2026 · audit v1.0
Generated Mar 22, 2026
Optimizes tutorial generation by recording trajectories and user ratings, then analyzing patterns to improve content quality and user satisfaction. Ideal for content creation platforms or educational tools.
Enhances financial prediction accuracy by tracking ROI forecasts and rewarding based on error reduction, leading to better investment decisions. Suitable for fintech or investment advisory services.
Improves web scraping reliability by monitoring success rates and retry counts, optimizing performance for data collection tasks. Useful for data analytics or automation companies.
Records support interactions and user feedback to refine response strategies, increasing resolution rates and customer satisfaction. Applicable to customer service platforms.
Tracks campaign outputs and ROI metrics to adjust strategies, boosting engagement and conversion rates. Beneficial for digital marketing agencies.
Offers the optimizer as a cloud-based service with tiered pricing based on usage and features, targeting businesses seeking scalable AI performance improvements. Generates recurring revenue through monthly or annual subscriptions.
Provides tailored optimization services, including setup, analysis, and integration for specific client needs, ideal for enterprises with complex AI workflows. Revenue comes from project-based fees and ongoing support contracts.
Offers a free basic version for small-scale use, with advanced features like detailed trend analysis and A/B testing available in paid tiers. Attracts a broad user base and converts high-value customers.
💬 Integration Tip
Start by setting up the optimizer in a test environment to record initial trajectories before deploying in production, ensuring minimal disruption.
Scored Apr 19, 2026
Meta-skill for AI agent self-improvement. Analyzes runtime logs to detect error patterns, regressions, and inefficiencies, then generates structured improvem...
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Turn OpenClaw into a learning-loop agent with seeded workspace rules, skill promotion, reflective memory, and proactive maintenance.
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.
Complete toolkit for creating autonomous AI agents and managing Discord channels for OpenClaw. Use when setting up multi-agent systems, creating new agents, or managing Discord channel organization.