データ分析
#research
market-research
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
DeepseekModel
キュレーション済みスキル
品質 優秀 · 90
v1.0.0
取得
https://deepseekmodel.com/api/download.php?id=affaan-m-ecc-cursor-skills-market-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 market-research description Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions. origin ECC Market Research Produce research that supports decisions, not research theater. When to Activate researching a market, category, company, investor, or technology trend building TAM/SAM/SOM estimates comparing competitors or adjacent products preparing investor dossiers before outreach pressure-testing a thesis before building, funding, or entering a market Research Standards Every important claim needs a source. Prefer recent data and call out stale data. Include contrarian evidence and downside cases. Translate findings into a decision, not just a summary. Separate fact, inference, and recommendation clearly. Common Research Modes Investor / Fund Diligence Collect: fund size, stage, and typical check size relevant portfolio companies public thesis and recent activity reasons the fund is or is not a fit any obvious red flags or mismatches Competitive Analysis Collect: product reality, not marketing copy funding and investor history if public traction metrics if public distribution and pricing clues strengths, weaknesses, and positioning gaps Market Sizing Use: top-down estimates from reports or public datasets bottom-up sanity checks from realistic customer acquisition assumptions explicit assumptions for every leap in logic Technology / Vendor Research Collect: how it works trade-offs and adoption signals integration complexity lock-in, security, compliance, and operational risk Output Format Default structure: executive summary key findings implications risks and caveats recommendation sources Quality Gate Before delivering: all numbers are sourced or labeled as estimates old data is flagged the recommendation follows from the evidence risks and counterarguments are included the output makes a decision easier
このスキルを起動するキーワード。クリックでコピーできます。
このスキルにはトリガーワードがありません。
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) |