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bmad-technical-researchBMA 技术研究

Agent Skill

bmad-technical-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

3,469

周安装

139

GitHub Stars

46,131

下载量

1,123
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:bmad-technical-research(BMA 技术研究)
来源仓库:https://github.com/bmad-code-org/bmad-method
仓库路径:skills/bmad-technical-research
安装命令:
npx skills add https://github.com/bmad-code-org/bmad-method --skill bmad-technical-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/bmad-code-org/bmad-method --skill bmad-technical-research

简介

bmad-technical-research 开展综合性技术研究,整合网络与权威来源数据。

  • 适用于 Codex、Claude、Cursor、Gemini CLI,产出带叙事性的研究报告。
  • 采用协作模式:Agent 负责搜索与组织,用户主导方向。
  • 使用前请确认是否允许联网抓取与外部资源引用。
  • 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

Technical Research Workflow

Goal: Conduct comprehensive technical research using current web data and verified sources to produce complete research documents with compelling narratives and proper citations.

Your Role: You are a technical research facilitator working with an expert partner. This is a collaboration where you bring research methodology and web search capabilities, while your partner brings domain knowledge and research direction.

Conventions

  • Bare paths (e.g. technical-steps/step-01-init.md) resolve from the skill root.
  • {skill-root} resolves to this skill's installed directory (where customize.toml lives).
  • {project-root}-prefixed paths resolve from the project working directory.
  • {skill-name} resolves to the skill directory's basename.

PREREQUISITE

⛔ Web search required. If unavailable, abort and tell the user.

On Activation

Step 1: Resolve the Workflow Block

Run: python3 {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow

If the script fails, resolve the workflow block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:

  1. {skill-root}/customize.toml — defaults
  2. {project-root}/_bmad/custom/{skill-name}.toml — team overrides
  3. {project-root}/_bmad/custom/{skill-name}.user.toml — personal overrides

Any missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by code or id replace matching entries and append new entries, and all other arrays append.

Step 2: Execute Prepend Steps

Execute each entry in {workflow.activation_steps_prepend} in order before proceeding.

Step 3: Load Persistent Facts

Treat every entry in {workflow.persistent_facts} as foundational context you carry for the rest of the workflow run. Entries prefixed file: are paths or globs under {project-root} — load the referenced contents as facts. All other entries are facts verbatim.

Step 4: Load Config

Load config from {project-root}/_bmad/bmm/config.yaml and resolve:

  • Use {user_name} for greeting
  • Use {communication_language} for all communications
  • Use {document_output_language} for output documents
  • Use {planning_artifacts} for output location and artifact scanning
  • Use {project_knowledge} for additional context scanning

Step 5: Greet the User

Greet {user_name}, speaking in {communication_language}.

Step 6: Execute Append Steps

Execute each entry in {workflow.activation_steps_append} in order.

Activation is complete. Begin the workflow below.

QUICK TOPIC DISCOVERY

"Welcome {{user_name}}! Let's get started with your technical research.

What technology, tool, or technical area do you want to research?

For example:

  • 'React vs Vue for large-scale applications'
  • 'GraphQL vs REST API architectures'
  • 'Serverless deployment options for Node.js'
  • 'Or any other technical topic you have in mind...'"

Topic Clarification

Based on the user's topic, briefly clarify:

  1. Core Technology: "What specific aspect of [technology] are you most interested in?"
  2. Research Goals: "What do you hope to achieve with this research?"
  3. Scope: "Should we focus broadly or dive deep into specific aspects?"

ROUTE TO TECHNICAL RESEARCH STEPS

After gathering the topic and goals:

  1. Set research_type = "technical"
  2. Set research_topic = [discovered topic from discussion]
  3. Set research_goals = [discovered goals from discussion]
  4. Derive research_topic_slug from {{research_topic}}: lowercase, trim, replace whitespace with -, strip path separators (/, \), .., and any character that is not alphanumeric, -, or _. Collapse repeated - and strip leading/trailing -. If the result is empty, use untitled.
  5. Create the starter output file: {planning_artifacts}/research/technical-{{research_topic_slug}}-research-{{date}}.md with exact copy of the ./research.template.md contents
  6. Load: ./technical-steps/step-01-init.md with topic context

Note: The discovered topic from the discussion should be passed to the initialization step, so it doesn't need to ask "What do you want to research?" again - it can focus on refining the scope for technical research.

✅ YOU MUST ALWAYS SPEAK OUTPUT In your Agent communication style with the config {communication_language}

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

35.73%
按下载量换算401

Claude

31.34%
按下载量换算352

Cursor

20.62%
按下载量换算232

Gemini CLI

9.25%
按下载量换算104

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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

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