hallucination-prevention
De la autor
Detects and mitigates LLM hallucinations in production pipelines. Validates AI-generated facts, code, and decisions before they reach end users or downstream systems.
Instalare
npx skills add DevelopersGlobal/ai-agent-skills --skill hallucination-prevention -a claude-code
Se instalează în .claude/skills/hallucination-prevention/ · 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.
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Verificări de siguranță pe SKILL.md
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De ce 84
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.
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- doublecheckgithub/awesome-copilotThree-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review.Inginerie★ 40.4K
- LLM Output TestingPramodDutta/qaskillsTesting LLM-powered features including output quality validation, hallucination detection, token usage monitoring, and prompt regression testing.Testare★ 240
- ai-productcoco-research/cocoUse when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model output.Design★ 784
- preprocessing-data-with-automated-pipelinesforyourhealth111-pixel/Vibe-SkillsDesign and implement repeatable preprocessing pipelines for cleaning, encoding, transforming, and validating ML input data.Design★ 3.8K
- llm-pipelineericrisco/rsc-harnessUse when wiring several LLM calls into a production flow: typed contracts between steps, a router/gateway so 429s, timeouts and outages fail over instead of taking you down, and cost control via caching, model tiers and abort caps. NOT single-prompt wording (that is `prompt-engineering`), NOT a model-driven tool loop (that is `building-agents`).Altele★ 255
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