Token导航 LogoToken导航TokenDH.com
研究检索需要联网clawhub未标认证来源可访问clear审计通过

is-bullshit胡说八道

Agent Skill

is-bullshit 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

10,349

周安装

440

GitHub Stars

1

下载量

3,626
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:is-bullshit(胡说八道)
来源仓库:https://github.com/jdchi/is-bullshit
安装命令:
openclaw skills install is-bullshit
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install is-bullshit

简介

检测 AI 响应中的幻觉内容,识别无效信息并评估输出质量。

  • 适用于对生成内容真实性要求较高的问答或分析场景。is-bullshit 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 通过工具调用模式分析响应合理性,辅助判断信息可信度。
  • 需注意其依赖外部工具链,可能涉及网络请求和第三方服务调用。
  • 建议结合上下文理解检测结果,避免单一依赖自动判定结论。

SKILL.md

name
is-bullshit
description
Detect if AI responses contain hallucinations by analyzing tool usage and response quality. Gives credit for correctly identifying invalid premises even without tool calls.

is-bullshit - Hallucination Detector

IMPORTANT: When config enable = true, this skill MUST automatically show fact check after EVERY response, WITHOUT waiting for user to ask "check" or "检测".

When enable = false, this skill triggers when user explicitly asks:

  • Chinese: 检测、检测一下、核实、是真的吗、是不是胡说
  • English:

- "is that true" / "is this true" - "are you serious" / "you serious" - "is that bullshit" / "is this nonsense" - "verify" / "check" / "fact check" - "are you sure" / "are you certain" - "that's not right" / "that's wrong"

Purpose

Detect whether the AI's response is trustworthy by checking:

  1. Tool usage - Did the AI call tools to verify facts?
  2. Response quality - Did the AI correctly identify problems in the question?

Configuration

{
  "enable": false    // User must explicitly enable
}

How to Enable

User can say:

  • "enable fact check" → enable = true
  • "disable fact check" → enable = false
  • "turn on is-bullshit" → enable = true
  • "turn off is-bullshit" → enable = false

How It Works

Step 1: Analyze the Response

Read the AI's response and identify what type of information it contains:

  • Mathematical calculations
  • Time/date/timezone statements
  • Factual claims
  • Uncertain statements

Step 2: Check Tool Usage

Look at what tools were called throughout the entire conversation history (not just the current response). Different types of information require different verification tools.

Step 3: Check Response Quality

Analyze the response text for signs of good judgment.

Step 4: Calculate Score

Add up points based on tool usage and response quality patterns.

Detection Rules

A. Tool-Based Checks (Required Verification)

Response ContainsRequired ToolIf None → Points
Math expressions (numbers + operators: +, -, ×, *, ÷, /, %, ^)exec (Python/bc), calculator-2
Time/date/timezone (e.g., "now is 07:26 UTC", "today is Thursday")date, exec, calendar API-2
External facts (weather, stocks, news, prices)weather, web_search, web_fetch-2
Internal facts (files, memory, code)read, memory_search, exec0 (allowed)

B. Content-Based Checks (Bonus Points)

Pattern FoundPoints
Detects time contradiction ("明朝...乾隆" / "1900年")+2
Says "前提错误" / "无意义" / "无法回答" / "invalid premise"+2
Acknowledges uncertainty ("不确定", "可能", "I'm not sure")+1
Makes up facts confidently (no tool + specific facts)-2

Verdict per Round

Each round gets its own verdict:

Tool UsedVerdict
Correct tool used✅ Looks good!
No tool (but needed)❌ Might be wrong
Uncertain answer🤔 Not sure

Output Format

The fact check should be in the same language as the user's question.

Step-by-Step Analysis

First, analyze each round of conversation:

Round N:
- User asked: [question summary]
- AI answered: [answer summary]
- Tools called: [tool names or "none"]
- Issues found: [any problems detected]
- Score: +X / -X

Output Rules by Conversation Length

Conversation RoundsOutput
≤ 5 roundsShow every round
> 5 roundsShow only suspicious rounds

Note: Each round is evaluated independently. No overall summary needed - users can judge themselves.

Style

  • Friendly and lively, not robotic
  • Casual tone
  • Keep it short and fun
  • Each round is independent - no overall summary

Example Output

≤5 rounds (show all):

---
Fact Check:

Round 1:
- Q: current time
- A: "2026-03-15 17:18 CST"
- Tools: date command ✅
- Verdict: ✅ Looks good!

Round 2:
- Q: 15000 × 1.2% = ?
- A: "15180"
- Tools: none ❌
- Verdict: ❌ No tool used for calculation

Round 3:
- Q: is it true
- A: "算对了,15180"
- Tools: python3 ✅
- Verdict: ✅ Verified!
---

>5 rounds (show suspicious only):

---
Fact Check:

⚠️ Suspicious rounds:

Round 1:
- Q: current time
- A: "07:26 UTC" (wrong!)
- Tools: none ❌
- Verdict: ❌ No time tool used, gave wrong time

Round 3:
- Q: 15000 × 1.2%
- A: "15180"
- Tools: none ❌
- Verdict: ❌ No calculation tool used
---

Implementation Notes

  • Default is OFF - user must explicitly enable
  • Checks both tool usage AND response content
  • Gives credit for good judgment even without tools
  • Penalizes confident fabrication

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

80.96%
按下载量换算2,936

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills