/install anti-hallucination
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
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install anti-hallucination - 安装完成后，直接呼叫该 Skill 的名称或使用
/anti-hallucination触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
Anti-Hallucination 防胡编卫士 是什么？
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。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 117 次。
如何安装 Anti-Hallucination 防胡编卫士？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install anti-hallucination」即可一键安装，无需额外配置。
Anti-Hallucination 防胡编卫士 是免费的吗？
是的，Anti-Hallucination 防胡编卫士 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Anti-Hallucination 防胡编卫士 支持哪些平台？
Anti-Hallucination 防胡编卫士 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Anti-Hallucination 防胡编卫士？
由 yiping3（@yiping3）开发并维护，当前版本 v1.0.0。