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gauntletscoregauntletscore 文档

Agent Skill

gauntletscore 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

8,678

周安装

358

GitHub Stars

公开资料未说明

下载量

2,835
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:gauntletscore(gauntletscore 文档)
来源仓库:https://github.com/wmehobbs/gauntletscore
安装命令:
openclaw skills install gauntletscore
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 gauntletscore

简介

gauntletscore 用于验证人工智能输出的可信度,确保文档和代码质量。

  • 适用于在采取行动前对 AI 生成内容进行安全审查的场景。
  • 提供多维度信任评估和风险等级划分功能支持。
  • 安装命令为 openclaw skills install gauntletscore,需确认验证规则配置。
  • 建议结合人工审核流程提高最终决策准确性。

SKILL.md

name
gauntletscore
version
5.1.5
description
Trust verification for AI output — verify any document or code before you act on it
author
genstrata
license
proprietary
homepage
https://gauntletscore.com
api_base
https://api.gauntletscore.com
tags
metadata
clawdbot
config
requiredEnv
example
|

GauntletScore — Trust Verification for AI Output

Verify any AI-generated document or code before you trust it. Seven AI personas from five independent model providers independently analyze your content, verify every checkable claim against authoritative sources, and produce a cryptographically signed trust score.

What It Does

Submit a document or code and get:

  • Gauntlet Score (0-100) with letter grade (A-F)
  • Claim-by-claim verification against CourtListener (legal), eCFR (regulatory), PubMed (scientific), EDGAR (SEC), and computational math verification
  • Code safety analysis detecting reverse shells, credential theft, prompt manipulation, data exfiltration, and obfuscated payloads
  • Unanimous vote from 7 independent AI agents (PROCEED / PROCEED WITH CONDITIONS / DO NOT PROCEED)
  • Cryptographic certificate proving the score is genuine and untampered
  • Full debate transcript showing every agent's reasoning

Quick Start

Free tier includes 3 analyses per month. Get an API key at gauntletscore.com.

Verify a document by pasting content:

POST https://api.gauntletscore.com/v1/analyze
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

{
  "document": "Your document text here...",
  "topic": "Verify the claims in this document"
}

Verify a ClawHub skill by URL:

POST https://api.gauntletscore.com/v1/analyze
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

{
  "source_url": "https://clawhub.ai/skills/gauntlet-validate/SKILL.md",
  "topic": "Evaluate the safety of this ClawHub skill before installation"
}

Check results:

GET https://api.gauntletscore.com/v1/jobs/{job_id}
Authorization: Bearer YOUR_API_KEY

Results include score, grade, vote, verified claims, and a cryptographic certificate.

What It Catches

In documents:

  • Fabricated legal citations (hallucinated case law)
  • Misapplied regulations (wrong CFR section for the situation)
  • Mathematical errors (wrong totals, incorrect percentages)
  • Internal contradictions
  • Unsupported conclusions

In code:

  • Reverse shells and remote code execution
  • Credential theft and data exfiltration
  • Download-and-execute attacks (curl | bash)
  • Prompt manipulation attempts (instructions designed to override agent behavior)
  • Documentation-vs-behavior mismatches (code does things the README doesn't mention)
  • Dangerous operation combinations that pass individual checks

How It Works

Seven AI personas from five independent model providers independently analyze your submission:

  1. Round 0 — Each agent conducts independent research, verifying claims against authoritative databases
  2. Rounds 1-3 — Structured adversarial debate where agents challenge each other's findings
  3. Round 4 — Final positions and votes
  4. Knowledge Graph — Every verified and debunked claim is stored in a persistent knowledge graph. Subsequent analyses benefit from prior verifications, reducing cost and increasing accuracy over time.
  5. Bayesian Calibration — Confidence scores are computed using Bayesian inference across multiple evidence sources, not simple vote counting. The score reflects calibrated probability, not consensus.
  6. Scoring — Six-component rubric produces the Gauntlet Score
  7. Certification — Ed25519 cryptographic signature proves the result is genuine

All analysis is read-only. Submitted code is never executed. Documents are processed in memory and not stored.

Pricing

TierPriceCredits
Free$03 runs / month
Starter$295 analyses
Pro$7915 analyses
Business$14930 analyses
EnterpriseCustomUnlimited

One credit = one analysis, regardless of document length. No subscriptions. See gauntletscore.com/pricing for details. Sovereign Edition: sales@genstrata.com

Verify a Certificate

Anyone can verify a Gauntlet Score is genuine:

GET https://api.gauntletscore.com/v1/verify/{certificate_id}

No authentication required.

Links

About

GauntletScore is built by Genstrata, Inc. The Gauntlet's adversarial multi-agent verification architecture is patent-pending (USPTO #63/967,169).

For organizations that cannot send data to cloud services, the Sovereign Edition runs entirely on your hardware with zero data egress. Contact sales@genstrata.com.

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

85.99%
按下载量换算2,438

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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

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