データ分析
#research
deep-research
Produce an in-depth, source-grounded research report. Use for broad questions requiring multiple research threads, reconciliation, and a cited report rather than a quick factual lookup.
DeepseekModel
キュレーション済みスキル
品質 優秀 · 78
v1.0.0
取得
https://deepseekmodel.com/api/download.php?id=nateberkopec-dotfiles-files-home-claude-skills-deep-research-skill-md&format=skill
ダウンロード .skill
標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name deep-research description Produce an in-depth, source-grounded research report. Use for broad questions requiring multiple research threads, reconciliation, and a cited report rather than a quick factual lookup. Deep research Use separate agents for source gathering and final synthesis so each role keeps a clean context. The lead coordinates, interviews, delegates reconnaissance, checks coverage, and validates the final report; it does not perform independent web research. For a narrow fact or small documentation lookup, answer directly instead of using this workflow. 1. Define the question Ask one focused round at a time until the audience, decision, boundaries, desired depth, source constraints, date range, output location, and success criteria are clear. Propose a research question and outline for approval. Do not begin full research before approval. When the topic needs a methodological lens, read references/research-frameworks.md only for the applicable framework. 2. Delegate reconnaissance Launch a small reconnaissance assignment to identify terminology, source types, obvious subquestions, and likely blind spots. Use its findings to divide the outline into non-overlapping research threads. Keep a coverage map connecting every approved section to at least one assignment. Before launching researchers or a report writer, read references/agent-briefs.md and apply the relevant contract. Give each researcher one thread and one output file under research_notes/ . Parallelize independent threads; keep dependent work sequential. Completion criterion: every outline section has an owner, boundaries, evidence standard, and note path. 3. Research and close gaps Wait for all assignments, then inspect every note for source quality, missing citations, contradictions, and unfilled sections. Delegate targeted follow-ups rather than silently filling gaps. Preserve conflicting credible evidence for synthesis. Completion criterion: every approved section has adequate primary or authoritative support, or an explicit documented limitation. 4. Synthesize Delegate the report to a fresh writer with the approved question, outline, all note paths, and final path. Require citations near claims, explicit conflict handling, limitations, and a source list. The report must be synthesis, not pasted notes. Review the output against the coverage map. Send specific defects back to the writer or a researcher and repeat until every section is supported and the report satisfies the agreed success criteria. 5. Deliver Return the report path, a concise summary of conclusions, important uncertainties, and the source count. Keep research_notes/ unless the user asks to remove it. Do not present the report as complete while a cited claim is unsupported, a credible conflict is hidden, or an approved section is missing.
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ダウンロードした .skill に含まれるフィールド。
| フィールド | 説明 |
|---|---|
| format | フォーマット識別子(skill/v1) |
| skill_id | スキル固有 ID |
| name | スキル名 |
| version | バージョン |
| description | 説明 |
| category | カテゴリ(配列) |
| trigger_words | トリガーワード |
| tags | タグ |
| source | ソース |
| source_url | ソース URL(本ページ) |
| exported_at | エクスポート日時(ダウンロード毎) |
| system_prompt | システムプロンプト本文 |
| model_config | モデル設定:provider / model / temperature / max_tokens / top_p |
| examples | サンプル |
| install_guide | 各プラットフォームの導入説明(Coze / Dify / Claude / カスタム) |