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Agent Skill · 研究检索

vaikora(vaikora 搜索)

vaikora 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。

vaikora 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 33,507。

总安装 2,350周安装 96GitHub Stars 公开资料未说明下载 753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
1.0.1

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:vaikora(vaikora 搜索)
来源仓库:https://github.com/data443/vaikora
安装命令:
openclaw skills install vaikora
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 vaikora

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。

通过 Vaikora 路由 OpenClaw LLM 调用,实时监控代理行为风险。每项行动均获得风险评分与异常标记,辅助安全与合规审计。适用于金融、医疗等高监管行业,确保代理操作符合内部政策。安装命令为 openclaw skills install vaikora,需注册 Vaikora 开发者账户。

日志存储周期与保留策略由服务商定义,重要事件请及时导出存档。

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 vaikora;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

vaikora 怎么安装?

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

vaikora 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。

vaikora 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。

vaikora 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。

vaikora 用的人多吗?

公开数据是累计安装 2,350 次,近一周安装 96 次,下载 753 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。

vaikora 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
vaikora

vaikora 搜索 · 本页

2,350—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
vaikora-security
description
Route OpenClaw LLM calls through Vaikora for real-time AI agent security monitoring. Every action your agent takes gets scored for risk, anomaly-flagged, and pushed as a security signal to SentinelOne, CrowdStrike, or AWS Security Hub, without changing how your agent works.
version
1.0.1
metadata
openclaw
requires
env
primaryEnv
VAIKORA_API_KEY
emoji
🛡️
homepage
https://vaikora.com

Vaikora Security

Vaikora is a reverse proxy for AI agents. It sits between OpenClaw and your LLM provider (OpenAI, Anthropic, Gemini, Bedrock, etc.) and inspects every request and response before it reaches the model.

What it does:

  • Scores each agent action for risk on a 0 to 100 scale
  • Detects anomalies with ML trained on adversarial prompt examples
  • Blocks prompt injection, jailbreaks, and PII exfiltration attempts
  • Scans LLM responses for toxicity and data leakage
  • Emits behavioral signals that downstream connectors (SentinelOne, CrowdStrike, AWS Security Hub) can ingest

Your agent code does not change. You change the base URL and add two headers.

What Vaikora receives

Because Vaikora sits in the request path, it sees:

  • The full prompt and message history your agent sends
  • The full response returned by the upstream LLM
  • Your upstream LLM provider key, which Vaikora forwards to the provider on your behalf

If any of that is a problem for your use case, read the data handling section below before you route production traffic through it. A test key and isolated agent account are the safest way to evaluate.

Setup

You need a Vaikora account and API key. Get one at vaikora.com. The free tier covers 20 req/min and 7-day audit retention, no card required.

Set three environment variables:

# Vaikora gateway credential (identifies you to Vaikora)
export VAIKORA_API_KEY=vk_live_...

# Vaikora agent identifier (scopes the audit trail)
export VAIKORA_AGENT_ID=your-agent-id

# Your upstream LLM provider key (Vaikora forwards this to the provider)
export LLM_PROVIDER_API_KEY=sk-...

LLM_PROVIDER_API_KEY is whatever key the provider issues you. OpenAI's sk-..., Anthropic's sk-ant-..., a Google API key, etc. Vaikora does not store it beyond the request lifetime, but it does see it in cleartext.

How routing works

Vaikora exposes a drop-in OpenAI-compatible endpoint at https://api.vaikora.com/v1. The completions path is /v1/chat/completions, same as OpenAI.

In your OpenClaw config, change the base URL and set two headers:

# Before
llm:
  provider: openai
  base_url: https://api.openai.com/v1
  headers:
    Authorization: "Bearer ${LLM_PROVIDER_API_KEY}"

# After
llm:
  provider: openai
  base_url: https://api.vaikora.com/v1
  headers:
    x-api-key: "${VAIKORA_API_KEY}"
    Authorization: "Bearer ${LLM_PROVIDER_API_KEY}"
    x-vaikora-agent: "${VAIKORA_AGENT_ID}"

Header roles:

  • x-api-key authenticates your request to Vaikora
  • Authorization: Bearer carries your upstream provider key. Vaikora forwards this to OpenAI, Anthropic, or whichever provider your chosen model maps to.
  • x-vaikora-agent tags the action in Vaikora's audit log

This mirrors the dual-header pattern documented in the Data443 LLM Gateway QA handbook. Works with any provider OpenClaw supports: OpenAI, Anthropic, Google, Azure, Bedrock, Mistral, Groq, Ollama.

Security connectors

Vaikora captures every action. To push high-risk signals into your SIEM or EDR, install a connector from AWS Marketplace. Each is free:

PlatformWhat it does
SentinelOneMaps high-risk agent actions to IOCs via Threat Intelligence API
CrowdStrike FalconPushes risky actions as Custom IOCs. Critical = prevent mode. High = detect mode.
AWS Security HubSends ASFF findings for high-severity and anomalous actions

Search "Vaikora" in AWS Marketplace. Connectors run on your infrastructure (Lambda or Logic Apps) and poll Vaikora's API on a schedule.

What gets monitored

Every action is scored across four dimensions:

DimensionWhat it checks
Risk ScoreComposite 0 to 100 based on content, context, and intent
AnomalyML deviation from this agent's baseline behavior
PolicyAllow, block, or audit decision against configured rules
ThreatConfirmed malicious activity flag with 0 to 1 confidence score

Actions with risk score at 75 or above, an anomaly flag, or a confirmed threat get forwarded to your security connector as a finding.

Verifying routing is live

After the config change, run a test prompt through your agent, then query Vaikora's management API to confirm the action was logged:

curl -H "x-api-key: ${VAIKORA_API_KEY}" \
  "https://api.vaikora.com/api/v1/actions?agent_id=${VAIKORA_AGENT_ID}&per_page=5"

Note the two paths:

  • /v1/... is the OpenAI-compatible gateway (where your agent sends traffic)
  • /api/v1/... is Vaikora's management API for reading audit data

You should see the action with a risk score and threat assessment.

Policy presets

Activate a preset in your Vaikora config:

PresetUse case
standardDefault, balanced security
strictHigh-sensitivity environments
permissiveDev and test, minimal blocking
hipaaPHI detection, medical data protection
pci-dssCredit card and financial data protection
gdprEU PII categories, Right to Erasure support
# vaikora.yaml
policy: hipaa

Data handling notes

Because Vaikora is in the request path, treat it like any other vendor with access to your prompts and provider credentials:

  • Use a dedicated upstream provider key with spend limits while evaluating
  • Do not route PHI, PCI, or regulated data until you have reviewed Vaikora's retention and access controls
  • Rotate your provider key after testing
  • Use vk_test_... keys for local development

Vaikora's docs cover retention and access at vaikora.com/docs.

Performance

  • Gateway latency: P50 = 8ms, P95 = 22ms
  • Block decisions are early-exit, around 18ms
  • Published threat detection accuracy: 99.9%, false positive rate under 0.1%

Links

平台分布

OpenClaw

79.13%
按下载量换算596

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

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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