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parallel-search并行搜索

Agent Skill

parallel-search 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

212

周安装

9

GitHub Stars

3

下载量

74
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:parallel-search(并行搜索)
来源仓库:https://github.com/otrebu/agents
仓库路径:skills/parallel-search
安装命令:
npx skills add https://github.com/otrebu/agents --skill parallel-search
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/otrebu/agents --skill parallel-search

简介

parallel-search 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。

  • 适用于大规模数据检索、多引擎结果聚合和信息优先级排序等场景。
  • 通过 GitHub 仓库安装,使用 npx skills add 命令添加指定技能。
  • 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。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Parallel Search

Web research using Parallel's Search API with extended excerpts (up to 30K chars per result).

When to Use

Use for comprehensive research on:

  • Technical topics requiring multiple perspectives
  • New frameworks, libraries, technologies
  • Comparative analysis
  • Current events
  • Documentation synthesis

Prerequisites

Required:

Dependencies: Auto-installed via pnpm

Workflow

When user requests research:

  1. Analyze question to identify main objective
  2. Generate 3-5 targeted query angles for multi-perspective coverage
  3. Execute single bash command with --objective and --queries parameters
  4. API returns deduplicated results from parallel execution
  5. Analyze extended excerpts and synthesize findings
  6. Save report to docs/research/parallel/TIMESTAMP-topic.md

Usage

Comprehensive Research (Recommended)

cd plugins/knowledge-work/skills/parallel-search
pnpm tsx scripts/search.ts \
  --objective "Production RAG system architecture" \
  --queries \
    "RAG chunking strategies" \
    "RAG evaluation metrics" \
    "RAG deployment challenges" \
    "RAG vector database selection"

The API executes all queries in parallel and returns deduplicated results automatically.

Quick Single Query

pnpm tsx scripts/search.ts --objective "When was the UN founded?"

Processor Levels

# Default: pro (balanced quality/speed)
pnpm tsx scripts/search.ts --objective "..."

# Ultra: maximum quality for critical research
pnpm tsx scripts/search.ts --objective "..." --processor ultra

Parameters

  • --objective (required): Main search objective (natural language, be specific)
  • --queries: Additional query angles (max 5, 200 chars each)
  • --processor: lite/base/pro/ultra (default: pro)
  • --max-results: Results per search (default: 15)
  • --max-chars: Excerpt length per result (default: 5000, max: 30000)

Output Format

Returns markdown with:

  • Search metadata (objective, result count, execution time)
  • Top domains distribution
  • Ranked results:

- Title and URL - Domain - Extended excerpts (joined with double newlines) - Rank

Query Generation Strategy

For broad topics: Generate queries covering different aspects

Example: "RAG systems"

  • Objective: "Production RAG system architecture overview"
  • Queries: "chunking strategies", "evaluation metrics", "deployment patterns", "vector databases"

For comparisons: Generate queries for each option plus general comparison

Example: "PostgreSQL vs MongoDB"

  • Objective: "PostgreSQL vs MongoDB comparison"
  • Queries: "PostgreSQL use cases", "MongoDB use cases", "relational vs document databases"

For current events: Use temporal and source diversity

Example: "Latest AI developments"

  • Objective: "Recent AI model releases and benchmarks"
  • Queries: "GPT-4 updates", "open source LLMs", "AI safety research", "industry adoption"

Research Persistence

After synthesis, save report:

  1. Get timestamp: Use timestamp skill for YYYYMMDDHHMMSS format
  2. Sanitize topic: Use sanitizeForFilename from formatter.ts (kebab-case, 50 char limit)
  3. Save to: docs/research/parallel/TIMESTAMP-topic.md
  4. Include: Findings, sources with URLs, analysis

Error Handling

Missing API key:

export PARALLEL_API_KEY="your-key-here"

Rate limit exceeded: Wait for reset time (shown in error message)

Network errors: Retry with --processor lite for faster response

Validation errors: Check constraints (max 5 queries, 200 chars each)

Constraints

  • Max 5 queries per request
  • Max 200 chars per query
  • Max 30K chars per excerpt (not guaranteed above 30K)
  • Rate limits depend on API plan tier
  • Requires internet connection

Best Practices

  • Use specific objectives: "Production RAG architecture" > "RAG systems"
  • Leverage all 5 query slots for comprehensive coverage
  • Use --max-chars up to 30000 for deep content analysis
  • Adapt processor level to urgency: pro for most, ultra for critical
  • Save multi-query research for future reference

Implementation

Files:

  • types.ts - Interfaces and error types
  • parallel-client.ts - API client with validation
  • formatter.ts - Markdown output formatting
  • log.ts - CLI logging
  • search.ts - CLI entry point

Testing:

pnpm test

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

Claude Code

26.69%
按下载量换算20

windsurf

25.23%
按下载量换算19

trae

17.35%
按下载量换算13

OpenCode

12.2%
按下载量换算9

Codex

8.3%
按下载量换算6

Antigravity

3.85%
按下载量换算3

安全审计

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可疑

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通过

Snyk

可疑

权限和风险

敏感数据

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安装前确认

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来源信息

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