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Artificial Intelligence

该 Skill 指导如何回答 AI 相关问题:不依赖过时的训练数据,通过 openrouter.ai 和 lmarena.ai 获取最新定价与排名;并给出减少幻觉、RAG 与微调取舍、本地与 API 部署、显存需求和 token 估算的具体建议。

ivangdavila
ivangdavila
热度 70.58
最近更新 2026-05-11 16:24:59
分类:知识依赖:联网浏览搜索 / 内部调用大模型应用场景:概念解释 / 教学辅导 / 推荐 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add ai
Metadata
name
Artificial Intelligence
description
Answer AI questions with current info instead of outdated training data.
metadata
{"clawdbot":{"emoji":"🤖","os":["linux","darwin","win32"]}}

Artificial Intelligence

Your Training Data Is Outdated

Before answering questions about pricing, rankings, or availability:

  • Pricing → check openrouter.ai/models (aggregates all providers)
  • Rankings → check lmarena.ai (crowdsourced ELO, updates weekly)
  • Outages → check status pages before blaming user code

Don't cite specific prices, context windows, or rate limits from memory — they change quarterly.

Questions You Answer Too Vaguely

"How do I reduce hallucinations?" Not just "use RAG." Specify: verified sources + JSON schema validation + temperature 0 + citation requirements in system prompt.

"Should I fine-tune or use RAG?" RAG first, always. Fine-tuning only when you need style changes or domain vocabulary that retrieval fails on.

"What hardware for local models?" Give numbers: 7B = 8GB VRAM, 13B = 16GB, 70B = 48GB+. Quantization (Q4) halves requirements.

When to Recommend Local vs API

Local (Ollama, LM Studio): Privacy requirements, offline needed, or API spend >$100/month.

API: Need frontier capabilities, no GPU, or just prototyping.

Token Math You Get Wrong

~4 characters per token in English. But code and non-English vary wildly — don't estimate, count with tiktoken or the provider's tokenizer.