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parallel-deep-research

by @parallel-webv
4.5(20)

ユーザーが「深度研究」または「詳尽」を明示的に要求した場合にのみ有効化され、包括的で詳細な情報収集と分析を行い、詳細な研究レポートを提供します。

deep-researchparallel-processinginformation-retrievaldata-synthesisai-agentsGitHub
インストール方法
npx skills add parallel-web/parallel-agent-skills --skill parallel-deep-research
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Before / After 効果比較

1
使用前

従来の調査方法は時間がかかりがちで、短時間で包括的かつ深い情報を得ることは困難です。複雑なテーマに直面すると、情報が断片化し、全体像を把握することが難しくなり、意思決定の質に影響を与えます。

使用後

このスキルを活用することで、深層並行研究を行い、多岐にわたる情報源から情報を包括的に収集・統合できます。詳細かつ包括的な調査レポートを提供し、ユーザーが複雑なテーマを迅速に理解し、賢明な意思決定を行うのを支援します。

SKILL.md

Deep Research

Research topic: $ARGUMENTS

When to use (vs parallel-web-search)

ONLY use this skill when the user explicitly requests deep/exhaustive research. Deep research is 10-100x slower and more expensive than parallel-web-search. For normal "research X" requests, quick lookups, or fact-checking, use parallel-web-search instead.

Step 1: Start the research

parallel-cli research run "$ARGUMENTS" --processor pro-fast --no-wait --json

This returns instantly. Do NOT omit --no-wait — without it the command blocks for minutes and will time out.

Processor options (choose based on user request):

ProcessorExpected latencyUse when
pro-fast30s – 5 minDefault — good balance of depth and speed
ultra-fast1 – 10 minDeeper analysis, more sources (~2x cost)
ultra5 – 25 minMaximum depth, only when explicitly requested (~3x cost)

Parse the JSON output to extract the run_id and monitoring URL. Immediately tell the user:

  • Deep research has been kicked off
  • The expected latency for the processor tier chosen (from the table above)
  • The monitoring URL where they can track progress

Tell them they can background the polling step to continue working while it runs.

Step 2: Poll for results

Choose a descriptive filename based on the topic (e.g., ai-chip-market-2026, react-vs-vue-comparison). Use lowercase with hyphens, no spaces.

parallel-cli research poll "$RUN_ID" -o "$FILENAME" --timeout 540

Important:

  • Use --timeout 540 (9 minutes) to stay within tool execution limits
  • Do NOT pass --json — the full output is large and will flood context. The -o flag writes results to files instead.
  • The -o flag generates two output files:
    • $FILENAME.json — metadata and basis
    • $FILENAME.md — formatted markdown report
  • The poll command prints an executive summary to stdout when the research completes. Share this executive summary with the user — it gives them a quick overview without having to open the files.

If the poll times out

Higher processor tiers can take longer than 9 minutes. If the poll exits without completing:

  1. Tell the user the research is still running server-side
  2. Re-run the same parallel-cli research poll command to continue waiting

Response format

After step 1: Share the monitoring URL (for tracking progress only — it is not the final report).

After step 2:

  1. Share the executive summary that the poll command printed to stdout
  2. Tell the user the two generated file paths:
    • $FILENAME.md — formatted markdown report
    • $FILENAME.json — metadata and basis

Do NOT re-share the monitoring URL after completion — the results are in the files, not at that link.

Ask the user if they would like to read through the files for more detail. Do NOT read the file contents into context unless the user asks.

Setup

If parallel-cli is not found, install and authenticate:

curl -fsSL https://parallel.ai/install.sh | bash

If unable to install that way, install via pipx instead:

pipx install "parallel-web-tools[cli]"
pipx ensurepath

Then authenticate:

parallel-cli login

Or set an API key: export PARALLEL_API_KEY="your-key"

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統計データ

インストール数8.5K
評価4.5 / 5.0
バージョン
更新日2026年5月23日
比較事例1 件

ユーザー評価

4.5(20)
5
30%
4
55%
3
15%
2
0%
1
0%

この Skill を評価

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対応プラットフォーム

🔧Claude Code
🔧OpenClaw
🔧OpenCode
🔧Codex
🔧Gemini CLI
🔧GitHub Copilot
🔧Amp
🔧Kimi CLI

タイムライン

作成2026年3月16日
最終更新2026年5月23日