跳到主要内容

deep-research 精选

Use this skill instead of WebSearch for ANY question requiring web research. Trigger on queries like "what is X", "explain X", "compare X and Y", "research X", or before content generation tasks. Provides systematic multi-angle research methodology instead of single superficial searches. Use this proactively when the user's question needs online information.

在 GitHub 打开

安装方式

cp -r skills/public/deep-research ~/.claude/skills/deep-research

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/

整仓一次性获取:git clone --depth 1 https://github.com/bytedance/deer-flow.git

依赖与权限

  • 无需 API Key
  • 无需联网
  • 无外部命令依赖
  • 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。

SKILL.md 正文

来源 bytedance/deer-flow@b346b17 · 许可 MIT · 内容未修改

Deep Research Skill

Overview

This skill provides a systematic methodology for conducting thorough web research. Load this skill BEFORE starting any content generation task to ensure you gather sufficient information from multiple angles, depths, and sources.

When to Use This Skill

Always load this skill when:

Research Questions

  • User asks "what is X", "explain X", "research X", "investigate X"
  • User wants to understand a concept, technology, or topic in depth
  • The question requires current, comprehensive information from multiple sources
  • A single web search would be insufficient to answer properly

Content Generation (Pre-research)

  • Creating presentations (PPT/slides)
  • Creating frontend designs or UI mockups
  • Writing articles, reports, or documentation
  • Producing videos or multimedia content
  • Any content that requires real-world information, examples, or current data

Core Principle

Never generate content based solely on general knowledge. The quality of your output directly depends on the quality and quantity of research conducted beforehand. A single search query is NEVER enough.

Research Methodology

Phase 1: Broad Exploration

Start with broad searches to understand the landscape:

  1. Initial Survey: Search for the main topic to understand the overall context
  2. Identify Dimensions: From initial results, identify key subtopics, themes, angles, or aspects that need deeper exploration
  3. Map the Territory: Note different perspectives, stakeholders, or viewpoints that exist

Example:

Topic: "AI in healthcare"
Initial searches:
- "AI healthcare applications 2024"
- "artificial intelligence medical diagnosis"
- "healthcare AI market trends"

Identified dimensions:
- Diagnostic AI (radiology, pathology)
- Treatment recommendation systems
- Administrative automation
- Patient monitoring
- Regulatory landscape
- Ethical considerations

Phase 2: Deep Dive

For each important dimension identified, conduct targeted research:

  1. Specific Queries: Search with precise keywords for each subtopic
  2. Multiple Phrasings: Try different keyword combinations and phrasings
  3. Fetch Full Content: Use web_fetch to read important sources in full, not just snippets
  4. Follow References: When sources mention other important resources, search for those too

Example:

Dimension: "Diagnostic AI in radiology"
Targeted searches:
- "AI radiology FDA approved systems"
- "chest X-ray AI detection accuracy"
- "radiology AI clinical trials results"

Then fetch and read:
- Key research papers or summaries
- Industry reports
- Real-world case studies

Phase 3: Diversity & Validation

Ensure comprehensive coverage by seeking diverse information types:

Information TypePurposeExample Searches
Facts & DataConcrete evidence"statistics", "data", "numbers", "market size"
Examples & CasesReal-world applications"case study", "example", "implementation"
Expert OpinionsAuthority perspectives"expert analysis", "interview", "commentary"
Trends & PredictionsFuture direction"trends 2024", "forecast", "future of"
ComparisonsContext and alternatives"vs", "comparison", "alternatives"
Challenges & CriticismsBalanced view"challenges", "limitations", "criticism"

Phase 4: Synthesis Check

Before proceeding to content generation, verify:

  • [ ] Have I searched from at least 3-5 different angles?
  • [ ] Have I fetched and read the most important sources in full?
  • [ ] Do I have concrete data, examples, and expert perspectives?
  • [ ] Have I explored both positive aspects and challenges/limitations?
  • [ ] Is my information current and from authoritative sources?

If any answer is NO, continue researching before generating content.

Search Strategy Tips

Effective Query Patterns

# Be specific with context
❌ "AI trends"
✅ "enterprise AI adoption trends 2024"

# Include authoritative source hints
"[topic] research paper"
"[topic] McKinsey report"
"[topic] industry analysis"

# Search for specific content types
"[topic] case study"
"[topic] statistics"
"[topic] expert interview"

# Use temporal qualifiers — always use the ACTUAL current year from <current_date>
"[topic] 2026"   # ← replace with real current year, never hardcode a past year
"[topic] latest"
"[topic] recent developments"

Temporal Awareness

Always check <current_date> in your context before forming ANY search query.

<current_date> gives you the full date: year, month, day, and weekday (e.g. 2026-02-28, Saturday). Use the right level of precision depending on what the user is asking:

User intentTemporal precision neededExample query
"today / this morning / just released"Month + Day"tech news February 28 2026"
"this week"Week range"technology releases week of Feb 24 2026"
"recently / latest / new"Month"AI breakthroughs February 2026"
"this year / trends"Year"software trends 2026"

Rules:

  • When the user asks about "today" or "just released", use month + day + year in your search queries to get same-day results
  • Never drop to year-only when day-level precision is needed — "tech news 2026" will NOT surface today's news
  • Try multiple phrasings: numeric form (2026-02-28), written form (February 28 2026), and relative terms (today, this week) across different queries

❌ User asks "what's new in tech today" → searching "new technology 2026" → misses today's news

✅ User asks "what's new in tech today" → searching "new technology February 28 2026" + "tech news today Feb 28" → gets today's results

When to Use web_fetch

Use web_fetch to read full content when:

  • A search result looks highly relevant and authoritative
  • You need detailed information beyond the snippet
  • The source contains data, case studies, or expert analysis
  • You want to understand the full context of a finding

Iterative Refinement

Research is iterative. After initial searches:

  1. Review what you've learned
  2. Identify gaps in your understanding
  3. Formulate new, more targeted queries
  4. Repeat until you have comprehensive coverage

Quality Bar

Your research is sufficient when you can confidently answer:

  • What are the key facts and data points?
  • What are 2-3 concrete real-world examples?
  • What do experts say about this topic?
  • What are the current trends and future directions?
  • What are the challenges or limitations?
  • What makes this topic relevant or important now?

Common Mistakes to Avoid

  • ❌ Stopping after 1-2 searches
  • ❌ Relying on search snippets without reading full sources
  • ❌ Searching only one aspect of a multi-faceted topic
  • ❌ Ignoring contradicting viewpoints or challenges
  • ❌ Using outdated information when current data exists
  • ❌ Starting content generation before research is complete

Output

After completing research, you should have:

  1. A comprehensive understanding of the topic from multiple angles
  2. Specific facts, data points, and statistics
  3. Real-world examples and case studies
  4. Expert perspectives and authoritative sources
  5. Current trends and relevant context

Only then proceed to content generation, using the gathered information to create high-quality, well-informed content.

质量与来源

所属仓库
bytedance/deer-flow
仓库星标
8.4 万
最近更新
今天
采集时间
今天
commit
b346b17fce89
内容指纹
sha256:04712f4daa7937c
文件路径
skills/public/deep-research/SKILL.md

同仓库其它 Skill

查看全部 32 个
blocking-io-guard
Ensure async-path backend code that could block the asyncio event loop is protected by a teeth-verified runtime anchor in tests/blocking_io/. Use when changing backend Python under app/, packages/harness/deerflow/, or scripts/, when running a blocking-IO triage round over the whole repo, or when a reviewer/CI asks for blocking-IO coverage. Runs a deterministic scan (changed-lines or full-repo), routes each candidate, drafts/extends an anchor, and proves it fails when the blocking IO regresses.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
deerflow-maintainer-orchestrator
Use when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review comments, review PR or issue batches, compare competing PRs that target the same issue, give fix strategy, risk classification, and validation guidance. Intended for maintainers and trusted local agents, not general contributors.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
engineer-system-change
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
smoke-test
End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke test deployment", "verify installation", "test service availability", "end-to-end test", or similar.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
academic-paper-review
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
bootstrap
Generate a personalized SOUL.md through a warm, adaptive onboarding conversation. Trigger when the user wants to create, set up, or initialize their AI partner's identity — e.g., "create my SOUL.md", "bootstrap my agent", "set up my AI partner", "define who you are", "let's do onboarding", "personalize this AI", "make you mine", or when a SOUL.md is missing. Also trigger for updates: "update my SOUL.md", "change my AI's personality", "tweak the soul".
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端

相似 Skill

更多「研究」
last30days
Research what people actually say about any topic in the last 30 days. Pulls posts and engagement from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the web. Includes a doctor health check to diagnose broken or missing sources.
精选 mvanhorn/last30days-skill 6.4 万 原文
Claude CodeCodex CLIMCP 客户端
agent-reach
MUST USE when user wants to 调研/research/搜索/search/查/找/look up anything on the internet — e.g. 全网调研 X / 帮我调研一下 X / 查一下 X / 搜搜 X / 看看大家怎么评价 X / X 上有什么讨论 / research this topic。 Also MUST USE when user mentions any platform or shares any URL/链接: 小红书/xiaohongshu/xhs, Twitter/推特/X, B站/bilibili, Reddit, Facebook, Instagram, V2EX, LinkedIn/领英/Boss直聘/招聘/求职/jobs, YouTube, GitHub code search, 小宇宙播客, 雪球/股票行情, RSS feeds, or any web URL. 16 platforms, multi-backend routing (OpenCLI / per-platform CLIs / APIs). Zero config for 6 channels. Run `agent-reach doctor --json` to see which backend serves each platform right now. NOT for: 写报告/数据分析/翻译等内容加工(本 skill 只负责从互联网获取内容); 发帖/评论/点赞等写操作;已有专门 skill 的平台(先用专门 skill)。 【路由方式】SKILL.md 包含路由表和常用命令,复杂场景需按需阅读对应分类的 references/*.md。 分类:search / social (小红书/推特/B站/V2EX/Reddit/Facebook/Instagram) / career(LinkedIn/Boss直聘) / dev(github) / web(网页/文章/RSS) / video(YouTube/B站/播客) / finance(雪球/股票)。
精选 Panniantong/Agent-Reach 9.6 万 原文
Claude CodeCursorMCP 客户端
academic-paper-reviewer
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정, revisar artículo, revisión entre pares, revisión de manuscrito, informe de árbitro, revisa mi artículo, criticar artículo, simular revisión, revisión editorial, calibrar revisor.
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code
academic-paper
12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, I got reviewer comments, revision roadmap, should we push back, conference rebuttal, grant panel response, audit my rebuttal, check my response draft, AI disclosure, check citations, citation check, check my references, verify references, look over the refs, 寫論文, 學術論文, 引導我寫論文, 審查意見, 我收到審查意見, 修訂路線圖, 評估回覆, 檢查引用, 引用檢查, 檢查參考文獻, 核對文獻, 논문 작성, 초록 작성, 논문 수정, 논문 계획을 도와줘, 심사 의견을 받았어, 심사 의견 반영, 답변서 점검, AI 사용 고지, 인용 확인, 인용 형식 검사, enmendar mi artículo, redactar artículo, guía mi artículo, analizar reseñas, auditar mi respuesta, verificar borrador de respuesta, verificar citas, divulgación de IA.
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code
academic-pipeline
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로, flujo de trabajo académico, investigación a artículo, flujo completo de artículo, pipeline de investigación completa, publicación de investigación, flujo de trabajo completo del artículo.
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code
sr-screener
Protocol-driven study screening for systematic, scoping and rapid reviews. Turns a proposal or PROSPERO protocol into confirmed eligibility rules, then screens titles/abstracts and full texts with two blinded AI reviewers and a third-reviewer adjudicator: ordered exclusion codes, no silent defaults, resumable batch runs, QC (seed studies, near-miss rechecks, kappa and PABAK), PRISMA 2020 counts, EndNote/Zotero RIS groups, an Excel log, a methods draft and a literature_corpus handoff to academic-paper. Reads RIS, PubMed .nbib, Web of Science and CSV exports; removes duplicates. 8 modes: protocol, quick, pilot, ta-screen, ft-screen, adjudicate, audit, report. Use it to screen records against eligibility criteria, pilot screening, resolve screening conflicts, audit exclusions or report the selection process. Triggers on: screen these papers, title/abstract screening, full-text screening, screening conflicts, inclusion criteria, PRISMA flow, غربالگری مقالات, اسکرینینگ عنوان و چکیده, معیارهای ورود و خروج.
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code