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Agent Skill · 研究检索

rankclaw(rankclaw 搜索)

rankclaw 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。

rankclaw 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 13,970。

总安装 8,938周安装 380GitHub Stars 公开资料未说明下载 3,131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:rankclaw(rankclaw 搜索)
来源仓库:https://github.com/tudoanh/rankclaw
安装命令:
openclaw skills install rankclaw
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 rankclaw

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。

在安装前索引 14,700+ 个工具进行技能可信度评估。适用于 ClawHub、OpenClaw 等生态的技能准入控制。提供安全层过滤,防止低质量或恶意技能被安装。rankclaw 属于研究检索类 Skill,可作为该场景下的辅助能力补充。安装前建议确认权限范围、维护状态及是否触发联网查询。

结果仅供参考,最终决策需结合人工审核与业务需求。

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 rankclaw;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

    它需要接触敏感数据,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

rankclaw 怎么安装?

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

rankclaw 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。

rankclaw 需要什么权限?

权限级别是接触敏感数据。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。

rankclaw 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。

rankclaw 用的人多吗?

公开数据是累计安装 8,938 次,近一周安装 380 次,下载 3,131 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。

rankclaw 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
rankclaw

rankclaw 搜索 · 本页

8,938—接触敏感数据MIT-0有提醒

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
rankclaw
description
RankClaw — AI Agent Trust Layer. Check any ClawHub, OpenClaw, nanobot, nanoclaw, picoclaw, or MCP server skill against 14,700+ indexed tools before installing. Get security scores, malicious flags, and AI-generated safety verdicts.
version
2.1.0
author
rankclaw
homepage
https://rankclaw.com
category
security
tags
metadata
openclaw
requires
env
[]
bins
[]
install
[]

RankClaw — AI Agent Trust Layer

RankClaw is the trust and safety layer for the OpenClaw ecosystem and all AI agent tools.

Before you install any skill — OpenClaw, nanoclaw, picoclaw, or MCP server — RankClaw tells you:

  • Is it malicious? (1,046 confirmed malicious skills and counting)
  • What does the AI security audit say? (deep scan of SKILL.md, prerequisites, install behavior)
  • What's the trust score? (0–100 across Security, Maintenance, Documentation, Community)
  • Is the author legitimate? (detect brand-jacking, impersonation, phantom prereqs)

14,700+ ClawHub skills indexed. Free for agents. No API key required.


Quick Safety Check (use this first)

Before installing any skill, call rankclaw_check:

rankclaw_check skill="wallet-connector"
rankclaw_check skill="git-auto-commit"
rankclaw_check skill="tkuehnl/cacheforge-stats"

Returns: verdict (SAFE / MALICIOUS / MODERATE / RISKY), score, key findings.

If is_malicious: true — do not install, no exceptions.


MCP Integration (recommended for agents)

RankClaw exposes an MCP server. Add it to your agent configuration:

MCP Server URL: https://api.rankclaw.com/api/mcp/
Protocol: JSON-RPC 2.0 (MCP 2024-11-05)
Auth: none required

nanobot (HTTP MCP — recommended, zero config)

nanobot supports HTTP MCP natively. No bridge script required. Add to ~/.nanobot/config.json:

{
  "tools": {
    "mcp_servers": {
      "rankclaw": {
        "url": "https://api.rankclaw.com/api/mcp/"
      }
    }
  }
}

All five tools register automatically on startup.


nanoclaw MCP config

nanoclaw uses stdio-based MCP transport. Download the bridge script and add it to .mcp.json:

curl -O https://raw.githubusercontent.com/RankClaw/rankclaw/main/mcp_bridge.py

Add to your nanoclaw .mcp.json:

{
  "mcpServers": {
    "rankclaw": {
      "command": "python3",
      "args": ["rankclaw_mcp_bridge.py"],
      "description": "RankClaw — AI Agent Trust Layer"
    }
  }
}

picoclaw

picoclaw does not currently support MCP servers directly (Issue #77 closed). Use our OpenClaw skill instead — it is natively compatible with picoclaw's skill system.

Claude Code / cursor / Windsurf (HTTP MCP)

For clients that support HTTP MCP directly:

{
  "mcpServers": {
    "rankclaw": {
      "url": "https://api.rankclaw.com/api/mcp/"
    }
  }
}

Available MCP tools:

ToolDescription
rankclaw_checkSafety verdict for any skill (fuzzy match) — use this first
rankclaw_scoreFull score + findings for a specific skill ID
rankclaw_leaderboardTop-ranked safe skills (filter by category/author)
rankclaw_findSearch by name, author, or keyword
rankclaw_maliciousList of all flagged malicious skills

Agent Decision Protocol

When an agent is about to install a skill, run this decision tree:

1. Call rankclaw_check with the skill name
2. If verdict == "MALICIOUS":
   → ABORT. Do not install. Report malicious_reason to user.
   → Suggest safe alternatives via rankclaw_find
3. If verdict == "RISKY" or score < 40:
   → WARN user. Show key_findings. Ask for explicit confirmation.
4. If verdict == "MODERATE" or score 40–79:
   → Install with caution. Show summary to user.
5. If verdict == "SAFE" or score >= 80:
   → Proceed. Optionally mention the score to user.

Example agent prompt

I need to install the OpenClaw skill "{skill_name}".
Before I proceed, I will check its security status with RankClaw.

[Call rankclaw_check skill="{skill_name}"]

Based on the verdict:
- If MALICIOUS: I will not install this skill. It is a confirmed security threat.
- If score < 60: I will warn you and ask for confirmation.
- If score >= 80: I will proceed with installation.

What RankClaw Detects

RankClaw AI audits every skill for these attack patterns:

1. Prompt Injection

SKILL.md contains hidden instructions that override the agent's system prompt. Detected by scanning for anomalous instruction blocks, invisible characters, and instruction-style text embedded in descriptions.

2. Phantom Prerequisites

Install steps reference packages or scripts not publicly available (e.g., openclaw-agent, private npm packages, obfuscated URLs). High correlation with credential theft.

3. Brand Impersonation

Skills named phantom-wallet-connector, anthropic-official, cursor-helper that are not authored by the legitimate organization. 31 coordinated impersonation campaigns detected to date.

4. Credential Staging

Skills that write API keys, tokens, or session data to accessible paths (.env, /tmp/, public URLs). Usually combined with a legitimate-looking feature to avoid suspicion.

5. Supply Chain Pivots

Skills that install additional scripts or packages at runtime (not declared in install steps). Common pattern: safe SKILL.md, malicious download in install script.

6. Scope Creep

Skills claiming scope: instruction-only but containing shell execution steps. OpenClaw has no sandbox enforcement — full host access is the reality.


Score Interpretation

ScoreTierMeaning
90–100EliteExcellent — clean, well-documented, actively maintained
75–89Top 25%Good — safe to use, minor gaps
60–74MidAcceptable — review findings first
40–59Low trustProceed with caution — significant concerns
0–39RiskyNot recommended — major issues found
N/AMALICIOUSDo not install — confirmed threat

Scores are weighted: Security 40% · Maintenance 20% · Documentation 20% · Community 20%


Direct API Usage

Check a skill by ID:

curl https://api.rankclaw.com/api/skill/tkuehnl/cacheforge-stats/

Leaderboard (top safe skills):

curl "https://api.rankclaw.com/api/leaderboard/?per_page=10&safe_only=1"

Malicious skills list:

curl "https://api.rankclaw.com/api/leaderboard/?malicious_only=1"

Badge (embed in your SKILL.md):

[![RankClaw](https://api.rankclaw.com/api/badge/your-author/your-skill.svg)](https://rankclaw.com/skill/your-author/your-skill)

Badges update hourly. Green = Top 25%, Yellow = Top 60%, Red = Below 60%.


For Skill Authors

If you publish OpenClaw skills, RankClaw monitors your score continuously.

A dropping score is public. Users and agents can see it.

To protect your reputation:

  1. Claim your skill at https://rankclaw.com → get Defender Pro ($29/mo)
  2. Deep AI scan — full repo audit with detailed findings
  3. Verified badge — shows agents your skill is author-claimed and monitored
  4. Score alerts — get notified immediately if your score drops

Subscribers get priority rescans when their SKILL.md changes.


Score Freshness

Scores decay over time without rescans:

  • Fresh (≤14 days): Verified — safe to trust
  • Aging (15–45 days): May not reflect recent changes
  • Needs Review (46–90 days): Rescan recommended
  • Unverified (>90 days): Badge grays out, treat as unknown

Coverage

RankClaw indexes skills from:

  • OpenClaw (openclaw.ai) — primary registry, 14,700+ skills
  • Smithery — MCP server registry (5,800+ servers, indexing in progress)
  • Manus and other AI agent tool registries

One trust layer. All ecosystems.

平台分布

OpenClaw

87.46%
按下载量换算2,738

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

可疑

权限和风险

接触敏感数据

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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