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Agent Skill · 研究检索

deep-research-article(深度研究文章)

deep-research-article 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。

deep-research-article 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 52,496。

总安装 558周安装 23GitHub Stars 34下载 182核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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-article(深度研究文章)
来源仓库:https://github.com/autobyteus/autobyteus-skills
仓库路径:skills/deep-research-article
安装命令:
npx skills add https://github.com/autobyteus/autobyteus-skills --skill deep-research-article
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/autobyteus/autobyteus-skills --skill deep-research-article

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于生成带强推理与过渡的文章,支持互联网增强与离线模式。输出 article.md 为主 artifact,附带证据提取与 claim ledger。可对接 infographic 工具生成幻灯片,实现内容多格式复用。需明确受众与使用场景以调整语言风格与深度。

deep-research-article 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/deep-research-article

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/autobyteus/autobyteus-skills --skill deep-rese…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

deep-research-article 怎么安装?

在终端执行 npx skills add https://github.com/autobyteus/autobyteus-skills --skill deep-research-artic…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

deep-research-article 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

deep-research-article 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

deep-research-article 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

deep-research-article 用的人多吗?

公开数据是累计安装 558 次,近一周安装 23 次,下载 182 次,GitHub 34 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

deep-research-article 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
deep-research-article

深度研究文章 · 本页

55834只读未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Deep Research Article

Overview (primary artifact)

Produce:

  1. article.md: one coherent article with strong reasoning and transitions

This skill is intentionally topic-agnostic. If the user later wants an image-only deck, pass the approved article directly to infographic-powerpoint-deck, which can ingest raw articles or structured slide tables.

In internet-backed mode, also produce a research package:

  • source_dossier.md
  • evidence_extract.md
  • research_notes.md
  • claim_evidence_ledger.md

Workflow

Step 0 — Confirm constraints and research mode

Ask only what’s necessary:

  • Audience + use case (sermon, lesson, blog, internal memo)
  • Desired length (minutes or word count)
  • Language (CN/EN/bilingual) and tone (academic / pastoral / simple)
  • Success criteria (what a “good final article” must achieve for this user)
  • Explicit non-goals/out-of-scope topics to prevent drift
  • For Bible: translation/version and whether to include cross-references
  • Must-use sources or explicit constraints (paywalled-only, region scope, date range)
  • Whether web research is prohibited by user/policy

Default mode is internet-backed deep research. Only skip internet if user explicitly asks for no-web research. If the user does not specify a length, do not default to a short article. Read references/longform_depth_standard.md and use the long-form depth defaults there.

Step 1 — Internet source sweep (required by default)

Follow references/web_research_protocol.md and create source_dossier.md using references/source_dossier_template.md.

Minimum source counts:

  • Normal: at least 8 sources
  • Deep: at least 12 sources

Coverage requirements:

  • At least 2 source types (e.g., primary + secondary)
  • At least 2 sources that present meaningful tension/alternative interpretation
  • For time-sensitive topics: include recent sources and clearly note dates

Drafting is blocked until this step is complete.

Step 1a — No-web fallback (only when explicitly requested)

If the user explicitly forbids web research:

  • Use only provided/local materials.
  • Build source_dossier.md from local sources.
  • Mark mode as no-web constrained in the dossier.
  • Keep the same extraction/ledger/QA flow, but clearly flag evidence limits in the article.

Step 1b — Evidence extraction (deep reading)

Create evidence_extract.md from the dossier using references/evidence_extraction_template.md.

For each major source, record:

  • exact claim/data point extracted
  • what it supports or challenges
  • uncertainty/caveat

For Bible passages:

  • Note structure (pericope boundaries), repeated words, contrasts, commands, warnings, comfort.
  • Identify “center of gravity” (main burden) and what the text is not saying.

Step 1c — Research notes (synthesis scratchpad)

Create research_notes.md using references/research_notes_template.md:

  • key definitions
  • observations from sources/text
  • competing interpretations
  • load-bearing facts with source IDs
  • open questions

Step 1d — Claim→evidence ledger (required)

Before drafting, build claim_evidence_ledger.md:

  • Use references/claim_evidence_ledger_template.md.
  • Every major claim must have at least one evidence anchor and source ID.
  • Mark confidence and disconfirmation condition.

Step 2 — Argument outline (the real engine)

Write an outline that is easy to defend:

  • Thesis (one sentence)
  • Mainline statement (one sentence): what the article must prove for this user, and what is explicitly out of scope
  • 3–6 supporting moves (each is a claim → evidence → implication)
  • Guardrails: what to omit, what not to overclaim
  • Transition logic: why move A leads to move B

Before drafting, run a quick outline challenge:

  • For each move, state “if removed, what breaks?”
  • Remove or merge moves that don’t break anything important.

Step 3 — Draft article.md

Use the skeleton in references/article_skeleton.md. Also read references/longform_depth_standard.md.

Rules:

  • Prefer short paragraphs with explicit signposting (“因此/所以/因为/然而”).
  • Separate observation vs application.
  • Include explicit citations (source IDs and links) for load-bearing claims.
  • Default to a substantial long-form article unless the user explicitly asked for a brief.
  • Integrate evidence into the body itself. Do not outsource the reasoning to a references section or tell the reader to “see the sources” instead of explaining the point.
  • A 3–6 move outline does not mean a short article. Each move may need multiple subsections or several paragraphs of evidence synthesis, tension, and implications.
  • If evidence is mixed, present both sides and state your judgment criteria.

Step 4 — QA gates (logic + evidence)

Run both:

  • references/logic_qa_checklist.md
  • references/evidence_gates.md
  • references/objectivity_checks.md
  • references/mainline_coherence_gate.md
  • references/final_article_quality_gate.md

If any hard gate fails, return to Step 1 (source sweep) or Step 1b (evidence extraction). In no-web constrained mode, return to Step 1a and narrow claims as needed.

Step 4b — Iterate until it “locks” (human-like drafting)

Deep research writing is normally iterative. Use references/iteration_protocol.md:

  • revise thesis/outline if QA reveals gaps
  • rewrite sections for clarity and scope
  • add/remove evidence so every claim is supported
  • trim or rewrite off-mainline sections (anything that does not advance the thesis)
  • repeat QA + quality scoring until stop criteria are met

Step 4c — Revision log (recommended for real iteration)

Humans keep track of what changed; do the same to avoid thrash:

  • Add a short “Revision notes” section to article.md, or keep a separate revision_log.md.
  • Use references/revision_log_template.md.

Step 5 — Stop at the approved article

The normal end state of this skill is an approved article.md plus the supporting research package. Do not create a separate slide-extraction handoff artifact as part of the default deep-research workflow. If the user wants slides after the article is approved, hand the article directly to infographic-powerpoint-deck.

Output files (recommended)

  • article.md
  • source_dossier.md (required in internet-backed mode)
  • evidence_extract.md (required in internet-backed mode)
  • research_notes.md (required)
  • claim_evidence_ledger.md (required)
  • revision_log.md (optional, but helpful)

References

  • Read references/article_skeleton.md when drafting article.md.
  • Read references/web_research_protocol.md for the required search/deep-reading workflow.
  • Read references/source_dossier_template.md to structure source collection.
  • Read references/evidence_extraction_template.md for claim-level extraction.
  • Read references/source_strategy.md to pick sources and record uncertainty.
  • Read references/research_notes_template.md to structure research_notes.md.
  • Read references/claim_evidence_ledger_template.md to prevent unsupported claims.
  • Read references/logic_qa_checklist.md for the reasoning QA pass.
  • Read references/evidence_gates.md for objective evidence sufficiency gates.
  • Read references/objectivity_checks.md for neutrality and confidence calibration checks.
  • Read references/mainline_coherence_gate.md to catch and remove sections that drift away from the core thesis/user intent.
  • Read references/final_article_quality_gate.md for final draft quality scoring before handoff.
  • Read references/longform_depth_standard.md so the final article defaults to paper-grade depth rather than a short summary.
  • Read references/iteration_protocol.md for iterative improvement and stop criteria.
  • Read references/revision_log_template.md to track iterations cleanly.

平台分布

Codex

38.39%
按下载量换算70

Claude

29.54%
按下载量换算54

Cursor

19.18%
按下载量换算35

Gemini CLI

9.94%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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