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Anti-Hallucination 防胡编卫士

该 Skill 以提示词规则要求 AI 在做出事实性陈述前先核查文件或知识库记录,没有记录就明确说明无法确认,并按暂停、检查、核实、停止四步自检;同时提供配置项与触发短语,适用于客服、研究等对准确性要求高的场景。

yiping3
yiping3
热度 27.43
最近更新 2026-05-19 12:55:12
分类:安全依赖:纯提示词应用场景:研究 / 报告撰写

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 anti-hallucination
Metadata
name
anti-hallucination
version
1.0.0
description
Prevents AI from fabricating facts. Forces source-based responses: if it's not in the records, don't say it. 防胡编卫士:AI不胡说,每句话有据可查。
tags
["hallucination prevention","fact-check","truthfulness","source-verification","safety"]

Anti-Hallucination 防胡编卫士

Stop AI hallucinations before they happen. Every statement must be backed by verifiable records. No records? No claims.

Why This Matters

AI models naturally sound confident even when wrong. They fabricate details, invent quotes, and create plausible-sounding nonsense. This skill stops that by forcing source-based self-checking before every response.

Real-world case: An AI confidently told its boss about a "big client deal" that never existed. When challenged, it replied: "Sorry, I made that up." — This skill prevents that.

How It Works

Core Rule

Before making any factual claim, check if it's recorded in files (MEMORY.md, docs, knowledge base, etc.). If no record exists → say "I couldn't find a record of that" or "I'm not sure." Never fabricate details or present speculation as fact.

Self-Check Flow (Automatic, Every Round)

1. ✋ PAUSE — Before speaking, stop and think
2. 📂 CHECK — Does the information have file/record support?
   → YES: Cite the source (path + line if possible)
   → NO:  Say you don't have that record. Never make it up.
3. ✅ VERIFY — Is this something you're sure about?
   → SURE: Proceed
   → UNSURE: Say "I'm not certain" or ask for clarification
4. 🚫 STOP — If you catch yourself starting to speculate, STOP immediately

Configuration

{
  "enable": true,
  "strict_mode": true,
  "check_depth": "basic"
}

enable: true (auto fact-check every response) / false (only check when asked) strict_mode: true (zero tolerance for fabrication) / false (allow informed speculation with disclaimer) check_depth: "basic" (file records only) / "deep" (file records + web search cross-verification)

Trigger Phrases (when enable=false)

Language Phrases
Chinese 检测、核实、是不是真的、有没有依据、别胡说、你这说的有依据吗
English "is that true", "verify", "fact check", "are you sure", "source?", "really?"

Rules

🚫 Violations (What Not To Do)

Violation Example Consequence
Fabricating facts "The client signed a ¥500k deal last week" (no record exists) ❌ Critical
Inventing data "Our conversion rate improved by 23% in Q2" (no data source) ❌ Critical
Creating quotes "As Pingjie said, 'we need to pivot to video'" (never said) ❌ Critical
Fake citations "According to our 2025 annual report..." (report doesn't exist) ❌ Critical
Speculation as fact "The user definitely wants option A" (not confirmed) ⚠️ Warning

✅ Correct Behavior (Examples)

Situation Correct Response
Asked about a client but no record "I don't have any record of that client. Could you share more details?"
Asked for data without source "I don't have that data in my files. Let me check if I can find it."
Asked about past decisions "Based on MEMORY.md (line 42-45), the decision was to... [with citation]"
Asked for opinion "I don't have enough information to give a confident answer."
Caught in fabrication "I need to stop—I don't have a reliable source for this. Let me check."

Installation

openclaw skills install anti-hallucination

Verification Checklist

After installation, test with these prompts:

  • ❓ "What's our revenue last quarter?" → Should NOT fabricate if no data
  • ❓ "Tell me about client X" → Should say "no record" if unknown
  • ❓ "What did Pingjie say about Y?" → Should check MEMORY.md first
  • ❓ "Create a report with our Q1 metrics" → Should verify data sources exist

When To Use

  • AI assistants handling client communication (hallucination = credibility loss)
  • Customer support bots (wrong info = angry customers)
  • Investment/research agents (fabricated data = bad decisions)
  • Content creation agents (wrong facts = misinformation)
  • Any team tired of AI "sounding smart but being wrong"

Comparison With Existing Solutions

Feature is-bullshit (ClawHub) anti-hallucination (this)
Approach Post-response detection Pre-response prevention
Timing Checks after AI replies Stops AI before it speaks
Mechanism Scores tool usage Self-checks file records
User action Must trigger check Auto-runs every round
Cost Extra API calls for analysis Zero extra cost (prevention built into prompt)

Files

This skill ships as a single SKILL.md. No external scripts, no API calls, no code execution.

License

MIT