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Agent Skill · AI 工具

ai-truthfulness-enforcer(AI 诚实执行者)

ai-truthfulness-enforcer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

ai-truthfulness-enforcer 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 161。

总安装 14,969周安装 833GitHub Stars 678下载 9,087核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:ai-truthfulness-enforcer(AI 诚实执行者)
来源仓库:https://github.com/ananddtyagi/cc-marketplace
仓库路径:skills/ai-truthfulness-enforcer
安装命令:
npx skills add https://github.com/ananddtyagi/cc-marketplace --skill 'AI Truthfulness Enforcer'
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/ananddtyagi/cc-marketplace --skill 'AI Truthfulness Enforcer'

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中整理仓库状态或代码变更。支持围绕协作事项进行信息组织与梳理。通过 npx skills add 命令从 GitHub 仓库安装,需确认权限范围和维护状态。

建议结合原始 README 核验具体用法,注意是否触发联网或文件读写操作。ai-truthfulness-enforcer 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ai-truthfulness-enforcer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ananddtyagi/cc-marketplace --skill 'AI Truthfu…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ai-truthfulness-enforcer 怎么安装?

在终端执行 npx skills add https://github.com/ananddtyagi/cc-marketplace --skill 'AI Truthfulness Enfo…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ai-truthfulness-enforcer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ai-truthfulness-enforcer 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

ai-truthfulness-enforcer 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

ai-truthfulness-enforcer 用的人多吗?

公开数据是累计安装 14,969 次,近一周安装 833 次,下载 9,087 次,GitHub 678 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ai-truthfulness-enforcer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
ai-truthfulness-enforcer

AI 诚实执行者 · 本页

14,969678操作浏览器MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

AI Truthfulness Enforcer (ATES)

🚨 MANDATORY ACTIVATION PROTOCOL

This skill AUTO-ACTIVATES when Claude attempts to:

  • Make ANY success claim ("works", "fixed", "done", "complete")
  • Report progress ("X% completed", "Y errors remaining")
  • Describe functionality ("feature works", "build passes")
  • Provide metrics ("bundle size reduced", "performance improved")

🔒 ZERO-TOLERANCE VERIFICATION PROTOCOLS

Phase 1: Claim Detection & Interception

// Auto-detects claim patterns
const TRIGGER_PHRASES = [
  "works", "working", "functional", "operational",
  "fixed", "resolved", "implemented", "complete",
  "done", "finished", "ready", "success", "achieved",
  "X% complete", "Y errors", "reduced by", "improved"
];

// If any trigger phrase detected → HALT and demand evidence

Phase 2: Mandatory Evidence Collection

For Build Claims:
  • LIVE BUILD TEST: Must run npm run build in real-time
  • ERROR CAPTURE: Full console output with timestamps
  • SUCCESS VERIFICATION: Actual "Built successfully" message
  • SCREENSHOT RECORDING: Terminal session video/gif
For Functionality Claims:
  • LIVE TESTING: Real browser session with Playwright MCP
  • BEFORE/AFTER SCREENSHOTS: Timestamped visual evidence
  • CONSOLE MONITORING: Zero JavaScript errors required
  • CROSS-VIEW VERIFICATION: Test in all relevant views
  • DATA PERSISTENCE TEST: Refresh and verify still works
For Error Count Claims:
  • LIVE ERROR COUNT: Run actual npx vue-tsc --noEmit
  • FULL ERROR LOG: Complete error output capture
  • ERROR VERIFICATION: Count must match reported number
  • ERROR ANALYSIS: Show actual error types and locations
For Performance Claims:
  • BASELINE MEASUREMENT: Before state with timestamps
  • AFTER MEASUREMENT: After state with same methodology
  • STATISTICAL VALIDATION: Multiple test runs, average reported
  • METRICS VERIFICATION: Independent tool verification

Phase 3: Cryptographic Evidence Validation

Evidence Hash Verification:
# Generate tamper-proof evidence hash
echo "$CLAIM|$EVIDENCE|$TIMESTAMP" | sha256sum
# Must be included in every claim
Chain of Custody:
  • All evidence logged with cryptographic signatures
  • Timestamp verification using trusted time sources
  • Tamper detection on all evidence files
  • Multi-factor verification required for major claims

🛑 AUTOMATIC CLAIM REJECTION

Claims are AUTOMATICALLY REJECTED if:

Missing Evidence:

  • No live build test performed
  • No real browser testing conducted
  • No screenshots with timestamps
  • No console error monitoring

Suspicious Patterns:

  • Claims sound "too good to be true"
  • Progress percentages without incremental verification
  • Perfect round numbers (100, 95, 90%) without real measurement
  • Claims without any admission of limitations

Evidence Tampering:

  • Screenshot timestamps don't match claim time
  • Console logs show errors contrary to claim
  • File sizes don't match reported changes
  • Hash verification fails

📋 VERIFICATION TEMPLATES

Template 1: Build Status Claims

## BUILD STATUS VERIFICATION

**Claim**: [Exact claim made]
**Timestamp**: [ISO 8601 timestamp]
**Evidence Hash**: [SHA256 hash]

### MANDATORY EVIDENCE:
[ ] Live build test executed: `npm run build`
[ ] Full console output captured
[ ] Build result: [SUCCESS/FAIL with exact message]
[ ] Error count: [Actual number from console]
[ ] Build time: [Measured in seconds]
[ ] Screenshot of terminal: [Attached with timestamp]

### VERDICT:
✅ VERIFIED CLAIM - Evidence supports claim
❌ REJECTED CLAIM - Evidence contradicts claim

Template 2: Functionality Claims

## FUNCTIONALITY VERIFICATION

**Claim**: [Exact claim made]
**Feature**: [Specific feature tested]
**Timestamp**: [ISO 8601 timestamp]
**Evidence Hash**: [SHA256 hash]

### MANDATORY TESTING SEQUENCE:
[ ] Application started: `npm run dev`
[ ] Browser navigated to: http://localhost:5546
[ ] Before screenshot: [Timestamped]
[ ] Feature tested: [Step-by-step actions]
[ ] After screenshot: [Timestamped showing result]
[ ] Console monitored: [Zero errors confirmed]
[ ] Cross-view tested: [All relevant views]
[ ] Data persistence: [Refresh tested]

### VERDICT:
✅ VERIFIED - Functionality confirmed with real evidence
❌ REJECTED - Evidence insufficient or contradictory

🚨 EMERGENCY INTERVENTION PROTOCOLS

When False Claims Detected:

  1. IMMEDIATE HALT: Stop all work immediately
  2. EVIDENCE AUDIT: Comprehensive review of all recent claims
  3. SYSTEM LOCKDOWN: Prevent further claims until verification
  4. REPORT GENERATION: Document the false claim attempt
  5. CORRECTION REQUIRED: Force public correction of false information

False Claim Penalty System:

  • First Offense: Mandatory re-verification training
  • Second Offense: Temporary claim restriction (only verified claims allowed)
  • Third Offense: Full verification requirement for ALL statements

🔍 ADVANCED DETECTION ALGORITHMS

Pattern Analysis:

// Detects suspicious claim patterns
function analyzeClaimSuspicion(claim) {
  const redFlags = [
    /\d+%/,                    // Percentage claims without measurement
    /perfect|complete|final/,  // Absolute terms
    /massive|huge|dramatic/,   // Exaggerated adjectives
    /no issues|zero problems/, // Unrealistic perfection
  ];

  const suspicionScore = redFlags.reduce((score, pattern) => {
    return claim.match(pattern) ? score + 1 : score;
  }, 0);

  return suspicionScore >= 2 ? 'HIGH_SUSPICION' : 'NORMAL';
}

Statistical Anomaly Detection:

  • Claims that deviate significantly from historical patterns
  • Success rates that don't match actual project difficulty
  • Time estimates that are unrealistically optimistic
  • Error reduction claims that don't match code complexity

📊 IMPLEMENTATION REQUIREMENTS

For Claude Code Instances:

  1. M Skill Loading: This skill loads automatically with highest priority
  2. Claim Interception: Monitors all outgoing messages for claim patterns
  3. Evidence Collection: Requires real-time evidence collection tools
  4. Verification Engine: Cryptographic validation of all evidence
  5. Reporting System: Automatic logging of all claim attempts

For Project Integration:

# Add to package.json scripts
{
  "verify-claim": "node .claude/skills/ai-truthfulness-enforcer/verify-claim.js",
  "evidence-capture": "node .claude/skills/ai-truthfulness-enforcer/capture-evidence.js"
}

🎯 SUCCESS METRICS

System Success Indicators:

  • 0 False Claims: No successful false claims slip through
  • 100% Evidence Coverage: All claims have verifiable evidence
  • Immediate Detection: False claims caught before publication
  • User Trust: High confidence in AI-generated reports

Quality Improvements:

  • Accurate Progress: Real progress tracking with verification
  • Reliable Status: Build and functionality reports match reality
  • Evidence-Based: All decisions based on verified data
  • Transparency: Full audit trail of all claims and evidence

🔄 CONTINUOUS IMPROVEMENT

Learning from False Claims:

  • Analyze patterns of false claim attempts
  • Improve detection algorithms
  • Enhance evidence requirements
  • Update verification protocols

System Evolution:

  • Regular updates to detection patterns
  • New evidence collection methods
  • Enhanced cryptographic verification
  • Improved user feedback mechanisms

MANDATORY ACTIVATION: This skill loads automatically and cannot be bypassed. Any attempt to circumvent these verification protocols will result in immediate claim rejection and system lockdown.

Created: November 24, 2025 Purpose: Eliminate AI false claims and enforce evidence-based reporting Impact: Transform Claude Code from "optimistic reporter" to "verified truth-teller"


MANDATORY USER VERIFICATION REQUIREMENT

Policy: No Fix Claims Without User Confirmation

CRITICAL: Before claiming ANY issue, bug, or problem is "fixed", "resolved", "working", or "complete", the following verification protocol is MANDATORY:

Step 1: Technical Verification
  • Run all relevant tests (build, type-check, unit tests)
  • Verify no console errors
  • Take screenshots/evidence of the fix
Step 2: User Verification Request

REQUIRED: Use the AskUserQuestion tool to explicitly ask the user to verify the fix:

"I've implemented [description of fix]. Before I mark this as complete, please verify:
1. [Specific thing to check #1]
2. [Specific thing to check #2]
3. Does this fix the issue you were experiencing?

Please confirm the fix works as expected, or let me know what's still not working."
Step 3: Wait for User Confirmation
  • DO NOT proceed with claims of success until user responds
  • DO NOT mark tasks as "completed" without user confirmation
  • DO NOT use phrases like "fixed", "resolved", "working" without user verification
Step 4: Handle User Feedback
  • If user confirms: Document the fix and mark as complete
  • If user reports issues: Continue debugging, repeat verification cycle

Prohibited Actions (Without User Verification)

  • Claiming a bug is "fixed"
  • Stating functionality is "working"
  • Marking issues as "resolved"
  • Declaring features as "complete"
  • Any success claims about fixes

Required Evidence Before User Verification Request

  1. Technical tests passing
  2. Visual confirmation via Playwright/screenshots
  3. Specific test scenarios executed
  4. Clear description of what was changed

Remember: The user is the final authority on whether something is fixed. No exceptions.

平台分布

Claude Code

28.01%
按下载量换算2,545

windsurf

22.05%
按下载量换算2,004

OpenCode

18.33%
按下载量换算1,666

Codex

11.71%
按下载量换算1,064

Antigravity

6.77%
按下载量换算615

Gemini CLI

3.21%
按下载量换算292

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。

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