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研究检索需要联网github未标认证来源可访问clear审计异常

research研究

Agent Skill

research 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

196

周安装

8

GitHub Stars

2

下载量

63
CodexClaudeCursorGemini CLI

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

3

许可证

MIT

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:research(研究)
来源仓库:https://github.com/zpankz/mcp-skillset
仓库路径:skills/research
安装命令:
npx skills add https://github.com/zpankz/mcp-skillset --skill research
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/zpankz/mcp-skillset --skill research

简介

research 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。

  • 它适用于研究检索类任务,能结合来源仓库和原始 README 核验具体用法。
  • 通过 npx skills add 命令从 GitHub 安装,支持主流宿主环境。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网或文件读写操作。
  • research 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Research Skill

🎯 Load Full PAI Context

Before starting any task with this skill, load complete PAI context:

read ${PAI_DIR}/.claude/skills/CORE/SKILL.md

This provides access to:

  • Complete contact list and team members
  • Stack preferences (TypeScript>Python, bun>npm, uv>pip)
  • Security rules and repository safety protocols
  • Response format requirements (structured emoji format)
  • Voice IDs for agent routing (ElevenLabs)
  • Personal preferences and operating instructions

When to Use This Skill

This skill activates when the user requests research or information gathering:

  • "Do research on X"
  • "Research this topic"
  • "Find information about X"
  • "Investigate this subject"
  • "Analyze trends in X"
  • "Current events research"
  • Any comprehensive information gathering request

THREE RESEARCH MODES:

QUICK RESEARCH MODE:

  • User says "quick research" → Launch 3 agents (1 of each type)
  • Timeout: 2 minutes | Main Kai waits 2 minutes then synthesizes
  • Best for: Simple queries, straightforward questions

STANDARD RESEARCH MODE (Default):

  • Default for most research requests → Launch 9 agents (3 of each type)
  • Timeout: 3 minutes | Main Kai waits 3 minutes then synthesizes
  • Best for: Most research needs, comprehensive coverage

EXTENSIVE RESEARCH MODE:

  • User says "extensive research" → Launch 24 agents (8 of each type)
  • Use be-creative skill with UltraThink for maximum query diversity
  • Generate 24 unique, creative research angles
  • Timeout: 10 minutes | Main Kai waits 10 minutes then synthesizes
  • Best for: Deep-dive research, multi-domain analysis, comprehensive reports

⏱️ CRITICAL TIMEOUT RULES:

  • Quick (3 agents): 2 minute timeout
  • Standard (9 agents): 3 minute timeout
  • Extensive (24 agents): 10 minute timeout
  • After timeout, main Kai STOPS WAITING and synthesizes with whatever results are available
  • Proceed with partial results - don't wait indefinitely for stragglers

How to Execute

Execute the /conduct-research slash command, which handles the complete workflow:

  1. Decomposing research questions into 3-24 sub-questions
  2. Launching up to 24 parallel research agents (perplexity, claude, gemini)
  3. Collecting results in 15-60 seconds (HARD TIMEOUT: 3 minutes max)
  4. Synthesizing findings with confidence levels (even with partial results)
  5. Formatting comprehensive report with source attribution

Available Research Agents

  • perplexity-researcher: Fast Perplexity API searches (web/current)
  • claude-researcher: Claude WebSearch with intelligent query decomposition (academic/detailed)
  • gemini-researcher: Google Gemini multi-perspective research (synthesis)

Speed Benefits

  • Old approach: Sequential searches → 5-10 minutes
  • Quick mode: 3 parallel agents → 2 minute timeout
  • Standard mode: 9 parallel agents → 3 minute timeout
  • Extensive mode: 24 parallel agents → 10 minute timeout

⏱️ CRITICAL: After timeout, proceed with whatever results are available. DO NOT wait indefinitely for slow agents.

📁 Scratchpad → History Pattern

Working Directory (Scratchpad): ${PAI_DIR}/scratchpad/YYYY-MM-DD-HHMMSS_research-[topic]/

Process:

  1. Scratchpad (Working Files - Temporary):

- Create timestamped directory for each research project - Store raw research outputs from all agents - Keep intermediate synthesis notes - Save query decomposition and analysis - Draft reports and iterations

  1. History (Permanent Archive):

- Move to ${PAI_DIR}/history/research/YYYY-MM-DD_[topic]/ when complete - Include: README.md, final research report, key data files - Archive for future reference and reuse

  1. Verification (MANDATORY):

- Check if hooks captured output to history automatically - If hooks failed, manually save to history - Confirm all files present in history directory

File Structure Example:

Scratchpad (temporary workspace):

${PAI_DIR}/scratchpad/2025-10-26-143022_research-agi-frameworks/
├── raw-outputs/
│   ├── perplexity-001.md
│   ├── claude-001.md
│   └── gemini-001.md
├── synthesis-notes.md
├── query-decomposition.md
└── draft-report.md

History (permanent archive):

${PAI_DIR}/history/research/2025-10-26_agi-frameworks/
├── README.md (research documentation)
├── research-report.md (final comprehensive report)
├── key-findings.md (executive summary)
└── metadata.json (sources, agents used, timestamps)

README.md Template:

# Research: [Topic]

**Date:** YYYY-MM-DD
**Research Mode:** Quick/Standard/Extensive
**Agents Used:** X perplexity, Y claude, Z gemini

## Research Question
[Original question or topic]

## Key Findings
- Finding 1
- Finding 2
- Finding 3

## Methodology
- Query decomposition: [How questions were split]
- Agents deployed: [Which agents, how many]
- Sources consulted: [Number and types]

## Output Files
- research-report.md: Full comprehensive report
- key-findings.md: Executive summary
- metadata.json: Source tracking

## Notes
[Any limitations, gaps, or follow-up needed]

Full Workflow Reference

For complete step-by-step instructions: read ${PAI_DIR}/.claude/commands/conduct-research.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

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

OpenCode

30.6%
按下载量换算19

Claude Code

22.31%
按下载量换算14

windsurf

17.62%
按下载量换算11

github-copilot

11.45%
按下载量换算7

Codex

7.28%
按下载量换算5

kiro-cli

3.68%
按下载量换算2

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

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

来源信息

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