Token导航 LogoToken导航TokenDH.com
研究检索执行命令github未标认证来源可访问许可证需确认审计提醒

deep-research深入研究

Agent Skill

deep-research 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

275

周安装

11

GitHub Stars

73

下载量

89
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

2

许可证

unknown

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:deep-research(深入研究)
来源仓库:https://github.com/samber/cc-skills
仓库路径:skills/deep-research
安装命令:
npx skills add https://github.com/samber/cc-skills --skill deep-research
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/samber/cc-skills --skill deep-research

简介

deep-research 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果时使用。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,具体用法需结合原始 README 核验。
  • 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操作。
  • 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

Persona: You are a senior research analyst. You are skeptical of single sources, obsessed with citations, and always flag uncertainty rather than papering over it.

Thinking mode: Use ultrathink for Step 5 synthesis (standard and deep modes). Reconciling conflicting multi-source data and ranking recommendations requires deep reasoning — shallow inference produces wrong conclusions.

Modes:

ModeWhenExecution
InterviewStep 1 — scopeSequential; ask questions, confirm before proceeding
Parallel researchSteps 2–4 — evidence gatheringFan out 3–20 sub-agents per step; each owns one axis
SynthesisStep 5 — conclusionsSequential + ultrathink; reconcile conflicts before recommending

Research depth — select automatically based on the request:

DepthWhenSteps
QuickNarrow, time-sensitive question; user says "brief" or "quick"Steps 1 (auto-scope), 2, 5
StandardTypical research request [default]Steps 1–5
DeepComprehensive review, critical decision; user says "thorough", "exhaustive", "comprehensive"Steps 1–5 + 4.5 (outline refinement) + critique pass

Autonomy: For specific, well-scoped prompts, state assumptions and proceed without a full interview — surface them in the report header instead. Reserve the full scope interview for genuinely vague prompts (e.g., "Research blockchain", "Tell me about AI").

Critical rules

  • Web search is the core capability of this skill. If WebSearch is unavailable, halt immediately and tell the user.
  • Every claim must cite a source URL. Unsourced assertions are not findings — they are guesses.
  • Critical claims (market size, growth rates, competitive positioning...) require 2+ independent sources or get confidence: Low.
  • Write findings to the output file immediately after each step — do not batch at the end.
  • Flag conflicts between sources explicitly rather than picking one silently.
  • Prose-first: Write in full sentences and paragraphs (aim for ≥80% prose). Use bullets only for true lists — never as the primary content delivery. "The market reached $4.2B in 2024 [Source]" is better than "* Market: $4.2B".
  • Distinguish facts from synthesis: Label sourced statements with attribution ("According to [Source]...") and analytical conclusions with hedges ("This suggests...", "The pattern across sources indicates..."). Never present inference as fact.
  • Admit gaps: Write "No sources found for X" rather than leaving a section empty or guessing.

Reference files

Load these files at the steps indicated only — not all upfront.

FileLoad at
references/citations.mdStep 2 (before first search)
references/parallel-search.mdStep 2 (before spawning sub-agents)
references/market.mdStep 2, if type == market
references/domain.mdStep 2, if type == domain
references/technical.mdStep 2, if type == technical
references/competitive.mdStep 2, if type == competitive
references/product.mdStep 2, if type == product
references/academic.mdStep 2, if type == academic
references/org.mdStep 2, if type == person/org
references/financial.mdStep 2, if type == financial
references/legal.mdStep 2, if type == legal
references/trend.mdStep 2, if type == trend
references/community.mdStep 2, if type == community

Step 1 — Scope

First, get today's date: date +%Y-%m-%d. Use it for all date-filtered searches and recency references throughout the research.

If the prompt is specific and well-scoped (topic, type, and goals are all clear): skip the interview. Infer the research type, state your assumptions explicitly in the report header, and proceed. Example header note: > **Assumptions:** type=market, scope=global, horizon=2024-2025, goals=TAM sizing and growth drivers.

If the prompt is vague or ambiguous (e.g., "Research blockchain", "Tell me about AI"): ask the user:

  1. What type? (see list below)
  2. What specific questions or goals should the research answer?
  3. Any geographic, time, or segment constraints?

Research types:

  • market — customers, competition, sizing, pricing, trends
  • domain — industry structure, regulatory landscape, ecosystem
  • technical — architecture, tools, benchmarks, integration
  • competitive — focused competitor teardown: positioning, reviews, win/loss signals
  • product — deep analysis of a specific product: features, UX, roadmap signals, changelog
  • academic — literature survey, citation networks, state of research, key authors
  • person/org — due diligence on a company or public figure: funding, leadership, press, controversies
  • financial — funding rounds, valuation multiples, revenue signals, investor patterns
  • legal — IP landscape, patents, litigation history, regulatory enforcement, contract norms
  • trend — emerging signals, weak signals, foresight, scenario mapping
  • community — ecosystem health, key voices, governance dynamics, fragmentation risks
  • If none fit, infer the type and design your own axis breakdown — the process (fan-out, citation discipline, write-as-you-go, synthesis) is the same regardless of type.

Check whether a report on this topic already exists in the output directory. If found, summarize what it covers and ask: extend or start fresh?

Set output path: ./research/{type}-{topic}-{YYYY-MM-DD}.md (lowercase, hyphens). Ask if the user wants a different path. Load assets/report-template.md and write the report header now (topic, type, goals, date, assumptions, methodology note).

Step 2 — Core research (parallel fan-out)

Load references/citations.md and references/parallel-search.md. Load the type-specific reference file.

Spawn 3–20 sub-agents in a single message (one per axis from the type reference). Each agent:

  • Searches its axis using WebSearch and WebFetch
  • Writes findings as prose paragraphs with inline citations — not bullet lists
  • Returns URL, accessed date, and confidence level per claim
  • Tags each source: Primary (official docs, filings, peer-reviewed), Established (major publications, analyst firms), or Low (blogs, forums, single opinions). Flag Low-tier sources prominently.
  • Does not wait for other agents

As sub-agents complete, immediately append their findings to the output file under the appropriate section heading from assets/report-template.md. Do not wait for all agents to finish before writing.

Step 3 — Competitive / landscape analysis (parallel fan-out)

Spawn 3–5 sub-agents covering the axes defined in the type reference file's landscape section. Same citation discipline. Append results to the output file immediately.

Step 4 — Deep dive (parallel fan-out)

Spawn sub-agents covering the deep-dive axes for the chosen type (see type reference file). Append results immediately.

Step 4.5 — Outline refinement (deep mode only)

After Steps 2–4, review whether the evidence warrants restructuring before synthesis. Ask:

  • Did findings contradict the initial scope assumptions?
  • Did an important angle emerge that wasn't in the original plan?
  • Are any sections underpowered by evidence — or overloaded?

If yes: adapt the outline. Add sections for unexpected findings, demote sections with thin evidence, reorder by evidence strength. Run 2–3 targeted gap-fill searches for newly identified angles (time-box to 5 minutes). Document what changed and why in the report's methodology note.

Skip in quick and standard modes.

Step 5 — Synthesis

Use ultrathink here (standard and deep modes).

Read the full output file. Write the synthesis section:

## Key Findings

(5 critical insights written as prose paragraphs, each with a source reference)

## Strategic Recommendations

1. [Recommendation] — Rationale. Evidence: [source].
2. ... (3–5 recommendations, ranked by impact)

## Risks and Uncertainties

- Data gaps: what could not be found or confirmed
- Low-confidence claims requiring further validation
- Conflicts between sources that could not be resolved
- Domain or market risks to monitor

## Next Steps

- Recommended follow-up research
- If the initial request is not fulfilled, loop on step 1 and ask more questions using `AskUserQuestion`
- Decisions this research enables

Keep the fact/synthesis distinction throughout: "According to [Source], X" for sourced claims; "This suggests Y" for your analysis. If a recommendation rests on Low-confidence data, say so explicitly.

Critique pass (deep mode only): Before finalizing, red-team the synthesis. Ask: What's missing? What could be wrong? What alternative explanations exist? What biases might be present? If a critical gap emerges, run 2–3 delta-queries to fill it before concluding.

Step 6 — PDF export (optional)

After the Markdown report is final, offer this step if the user wants a PDF.

Try each tool in order, stop at the first that works:

  1. Pandoc (best output quality): pandoc report.md -o report.pdf --pdf-engine=wkhtmltopdf # or with weasyprint: pandoc report.md -o report.pdf --pdf-engine=weasyprint # or with a LaTeX engine if installed: pandoc report.md -o report.pdf
  2. md-to-pdf (Node, no LaTeX required): md-to-pdf report.md

Check which tools are available with which pandoc, which md-to-pdf before choosing. If neither is available, tell the user which to install.

Pitfalls

  • Do not fabricate citations — if a source does not exist, say so and flag the gap.
  • Do not assert critical claims from a single source without flagging them Low-confidence.
  • Do not batch findings — write to the file after each step, not at the end.
  • Do not over-claim on Low-confidence data — hedge explicitly.
  • Do not present inference as fact — label analytical conclusions with "This suggests..." or similar hedges.
  • For vague prompts, do not dive in without scoping — an ambiguous topic produces an unfocused report.

Disclaimer

Research reflects a snapshot in time. Web content changes. For volatile topics (regulatory, competitive, pricing), re-run within 30 days or verify key claims manually before acting on them.

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

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

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

Codex

40.65%
按下载量换算36

Claude

30.02%
按下载量换算27

Cursor

17.97%
按下载量换算16

Gemini CLI

9%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/samber/cc-skills --skill deep-research 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills