Token导航 LogoToken导航

Agent Skill · 研究检索

cross-check(交叉检查)

cross-check 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。

cross-check 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 21,311。

总安装 4,896周安装 204GitHub Stars 公开资料未说明下载 1,632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-0
版本
2.1.0

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:cross-check(交叉检查)
来源仓库:https://github.com/tommot2/cross-check
安装命令:
openclaw skills install cross-check
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 cross-check

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

在内联阶段挑战代理假设,通过独立验证轮次提升回答准确性。适合复杂查询或多源信息冲突的场景,减少错误结论。检测潜在偏见和事实矛盾,强制二次核查关键数据。cross-check 属于研究检索类 Skill,可作为该场景下的辅助能力补充。安装前无需特殊权限,但需用户提供完整上下文和问题描述。

适用于科研、投资或法律等专业领域的高精度信息需求。

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 OpenClaw;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 openclaw skills install cross-check;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

    它需要需要联网,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

cross-check 怎么安装?

在终端执行 openclaw skills install cross-check。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

cross-check 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

cross-check 需要什么权限?

权限级别是需要联网。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。

cross-check 是免费的吗?

来源标注的许可证是 MIT-0。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。

cross-check 用的人多吗?

公开数据是累计安装 4,896 次,近一周安装 204 次,下载 1,632 次。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。

cross-check 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,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 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
cross-check

交叉检查 · 本页

4,896—需要联网MIT-0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

name
cross-check
description
Inline assumption checker that challenges your agent's thinking before responding. Detects complex queries and runs independent verification rounds, identifies blind spots and logical flaws. Two modes: Reinforced (same model, 2 rounds default) and Cross-Check (second model as verifier via sessions_spawn). Compact output by default, detailed on request. Use when: (1) 'cross-check this', (2) 'challenge your assumptions', (3) 'am I missing something?', (4) complex decisions, (5) long prompts where accuracy matters, (6) 'get a second opinion', (7) 'stress-test this idea'. Homepage: https://clawhub.ai/skills/cross-check
metadata
openclaw
configPaths
capabilities

Cross-Check v2.1

Install: clawhub install cross-check

Verify assumptions in your responses. Opt-in — the agent suggests verification, you decide.

Capabilities Used

  • sessions_spawn — For 2-model verification mode (optional). Requires a second configured model. Only used when user explicitly requests "cross-check 2-model".
  • HEARTBEAT.md — Reads (never writes) to check if user has enabled auto-suggestions.

Language

Detect from the user's message language. Default: English.

How It Works

Default: Suggest, Don't Auto-Run

When the agent detects a complex response (3+ assumptions), it appends a one-line suggestion:

💡 Cross-Check available — reply "cross-check" to verify these assumptions.

The user chooses whether to activate. No silent auto-invocation.

User Activates

CommandAction
"cross-check" / "sjekk dette"Lite mode (2 rounds)
"cross-check deep"Deep mode (3 rounds or 2-model)
"cross-check 2-model"2-model mode (requires sessions_spawn + second model)
"cross-check off"Disable suggestions for this session

Opt-In Auto-Suggestions via HEARTBEAT

If the user adds the following to their HEARTBEAT.md:

## Cross-Check
- auto-suggest: true

...then the agent will suggest Cross-Check when it detects 3+ assumptions, without the user needing to trigger it first. This is still a suggestion — the user must reply "cross-check" to actually run it.

Three Output Levels

Default — Confidence Note

For responses with 1-2 assumptions, append:

Confidence: [High / Medium / Low]
Key assumption: [the main assumption]

Lite — 2 Rounds (same model)

Round 1 "The Analyst": Solve fully, extract assumptions. Round 2 "The Challenger": Solve from scratch, different angles.

Output (max 8 lines):

Cross-Check (Lite):
  Agreement: [what both agreed on]
  Difference: [where they disagreed]
  Blind spot: [thing neither considered]
  Confidence: [High / Medium / Low]

Deep — 3 Rounds or 2-Model

Option A: Reinforced (same model, 3 rounds) Round 3 "The Synthesizer": Both answers visible, finds consensus/divergence/blind spots. Includes pre-mortem.

Option B: Cross-Check (second model) Uses sessions_spawn to run a verifier sub-agent. Requires a second configured model.

  • Step 1: Primary solves, extracts assumptions
  • Step 2: Verifier challenges each assumption from 4 perspectives (Skeptic, Expert, Beneficiary, Contrarian)
  • Step 3: Primary integrates challenges

Output (max 15 lines):

Cross-Check (Deep):
  Mode: [Reinforced / Cross-Check]
  Consensus: [findings all rounds agree on]
  Divergence: [where rounds disagreed + resolution]
  Blind spots: [things none considered]
  Assumptions:
    - [assumption]: [confidence] — [confirmed/challenged/revised]
  Confidence: [High / Medium / Low]

Assumption Tracking

Every round tracks: core assumptions, confidence (High/Medium/Low), unknowns, biases.

Guidelines for Agent

  1. Suggest, don't auto-run — show "Cross-Check available" line, let user decide
  2. Respect "cross-check off" — disable suggestions for the session
  3. Check HEARTBEAT.md — if auto-suggest is enabled, suggest proactively
  4. Compact output — max 8 lines lite, 15 deep
  5. Never modify files — reads HEARTBEAT.md only
  6. 2-model is optional — only mention if user asks or has multiple models
  7. Cost awareness — lite = ~2x tokens, deep = ~3x tokens

Privacy and Safety

  • Session-only — nothing persisted
  • No personal data written anywhere
  • Verifier receives only problem context + assumptions
  • No file writes, no web searches unless user requests
  • Uses only OpenClaw's configured providers via sessions_spawn

What This Skill Does NOT Do

  • Does NOT auto-run verification without user opt-in
  • Does NOT modify any files
  • Does NOT replace the primary model
  • Does NOT persist anything
  • Does NOT send raw user data externally

More by TommoT2

  • setup-doctor — Diagnose and fix OpenClaw setup issues
  • context-brief — Persistent context survival across sessions
  • tommo-skill-guard — Security scanner for installed skills
  • locale-dates — Format dates/times for any locale

Install the full suite:

clawhub install setup-doctor context-brief tommo-skill-guard locale-dates

平台分布

OpenClaw

78.94%
按下载量换算1,288

安全审计

VirusTotal

未展示

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills