reddi-agent-evaluationreddi.tech fork of agent-evaluation. Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and produc...
Install via ClawdBot CLI:
clawdbot install nissan/reddi-agent-evaluationGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Mar 22, 2026
Evaluate an AI customer service agent for handling diverse customer inquiries, ensuring consistent response quality and adherence to company policies. Use behavioral contract testing to define expected interaction patterns and statistical evaluation to measure reliability across multiple test runs.
Assess an AI financial advisor agent's capability to provide accurate investment recommendations and regulatory compliance. Implement adversarial testing to simulate edge cases like market crashes and multi-dimensional evaluation to prevent gaming of performance metrics.
Test an AI diagnostic agent for reliability in interpreting medical data and suggesting treatments, focusing on flaky test handling due to variable inputs. Use capability assessment to ensure it meets clinical standards and regression testing to catch behavioral drifts after updates.
Benchmark an autonomous driving agent's decision-making in simulated traffic scenarios, emphasizing reliability metrics and behavioral invariants. Apply statistical test evaluation to analyze performance distributions and prevent data leakage from test environments into training.
Offer a cloud-based service where companies can upload their AI agents for automated evaluation, including behavioral regression tests and reliability scoring. Revenue is generated through subscription tiers based on test volume and advanced features like adversarial testing modules.
Provide expert consulting services to help organizations design and implement custom evaluation frameworks for their LLM agents, focusing on bridging benchmark and production gaps. Revenue comes from project-based fees and ongoing support contracts for monitoring and optimization.
Distribute the evaluation skill as open-source software to foster adoption, while offering paid enterprise support, customization, and integration services. Revenue is derived from support contracts, training workshops, and premium features for large-scale deployments.
💬 Integration Tip
Integrate this skill early in the agent development lifecycle to establish baseline metrics and use it with multi-agent orchestration skills for comprehensive testing in collaborative environments.
Scored Jun 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.