agent-eval
De la autor
カスタムタスクでコーディングエージェント(OpenAI Codex、Aider、Codex など)をヘッドツーヘッドで比較し、合格率、コスト、時間、一貫性のメトリクスを測定します
Instalare
npx skills add mturac/everything-openai-codex --skill agent-eval -a claude-code
Se instalează în .claude/skills/agent-eval/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
Vrei ca agentul să-ți propună skill-uri în timp ce scrii? Vezi cum folosești skill-urile din IDE.
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 80
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- agent-evaluationthiientv/godmodeDesigns and runs reproducible evaluations for AI agents, prompts, tools, skills, and model-backed workflows using realistic datasets, isolated baselines, objective assertions, rubric grading, trajectory analysis, cost/latency tracking, and regression comparison. Use when measuring agent quality, optimizing skill triggering, comparing prompts or models, or gating an AI feature release. Not for ordinary deterministic unit tests.Testare★ 99
- agentic-readinessCodeAlive-AI/ai-driven-developmentAudit and improve repositories for reliable agentic work across Codex and Codex App, Claude Code, and OpenCode. Use when reviewing AGENTS.md or CLAUDE.md quality and discovery, instruction routing in monorepos or meta-repos, agent settings, MCP configuration, skills, subagents, context budgets, or repository organization for coding agents.Inginerie★ 166
- agentic-evalgithub/awesome-copilotPatterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response qualityTestare★ 40.4K
- api-load-testerOneWave-AI/claude-skillsLoad tests API endpoints with progressive concurrency. Measures response times, error rates, throughput, and identifies breaking points. Generates a detailed report with latency percentiles, throughput curves, bottleneck analysis, and optimization recommendations.Inginerie★ 378
- xs-multi-agentkaraage0703/ai-assistant-workspace異なるproviderのAI(Codex/Claude/Grok/Cursor/Antigravity等)から独立意見を集め、共通論点で相互検討して統合する。最初に利用可能エージェントを検出する。「みんなで考えて」「マルチエージェントで分析して」「複数のAIでレビューして」と言われたら使う。Altele★ 137
- openai-docsaiskillstore/marketplaceUse for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex.Inginerie★ 444
Note și recenzii
—
nicio recenzie
Ai încercat acest skill? Notează-l ca să-i ajuți pe alții. Autentifică-te
Discuție
Intră în discuție. Autentifică-te