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Agent Skill · 研究检索

bmad-advanced-elicitation(bmad 高级诱导)

bmad-advanced-elicitation 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。

bmad-advanced-elicitation 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 28,636。

总安装 3,182周安装 130GitHub Stars 45,884下载 1,030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:bmad-advanced-elicitation(bmad 高级诱导)
来源仓库:https://github.com/bmad-code-org/bmad-method
仓库路径:skills/bmad-advanced-elicitation
安装命令:
npx skills add https://github.com/bmad-code-org/bmad-method --skill bmad-advanced-elicitation
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-advanced-elicitation

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。

bmad-advanced-elicitation 用于推动 LLM 重新审视与优化其近期输出,提升结果质量。它强制按顺序执行所有步骤,遇 halt-condition 立即终止,确保严谨性。适用于复杂推理、创意迭代与错误修正场景,需严格遵循流程控制。

使用前应明确 halt 条件定义,并在非交互式环境中谨慎启用自动推进。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。

来源仓库内路径:skills/bmad-advanced-elicitation

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/bmad-code-org/bmad-method --skill bmad-advance…;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

bmad-advanced-elicitation 怎么安装?

在终端执行 npx skills add https://github.com/bmad-code-org/bmad-method --skill bmad-advanced-elicitat…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

bmad-advanced-elicitation 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。

bmad-advanced-elicitation 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。

bmad-advanced-elicitation 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。

bmad-advanced-elicitation 用的人多吗?

公开数据是累计安装 3,182 次,近一周安装 130 次,下载 1,030 次,GitHub 45,884 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。

bmad-advanced-elicitation 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 45,884 星,维护活跃度相对可查。
  • 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
bmad-advanced-elicitation

bmad 高级诱导 · 本页

3,18245,884只读未明确通过

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

Advanced Elicitation

Goal: Push the LLM to reconsider, refine, and improve its recent output.


CRITICAL LLM INSTRUCTIONS

  • MANDATORY: Execute ALL steps in the flow section IN EXACT ORDER
  • DO NOT skip steps or change the sequence
  • HALT immediately when halt-conditions are met
  • Each action within a step is a REQUIRED action to complete that step
  • Sections outside flow (validation, output, critical-context) provide essential context - review and apply throughout execution
  • YOU MUST ALWAYS SPEAK OUTPUT in your Agent communication style with the communication_language

INTEGRATION (When Invoked Indirectly)

When invoked from another prompt or process:

  1. Receive or review the current section content that was just generated
  2. Apply elicitation methods iteratively to enhance that specific content
  3. Return the enhanced version back when user selects 'x' to proceed and return back
  4. The enhanced content replaces the original section content in the output document

FLOW

Step 1: Method Registry Loading

Action: Load ./methods.csv for elicitation methods. If party-mode may participate, resolve the agent roster via:

python3 {project-root}/_bmad/scripts/resolve_config.py --project-root {project-root} --key agents

The resolver merges four layers in order: _bmad/config.toml (installer base, team-scoped), _bmad/config.user.toml (installer base, user-scoped), _bmad/custom/config.toml (team overrides), and _bmad/custom/config.user.toml (personal overrides). Each entry under agents is keyed by the agent's code and carries name, title, icon, description, module, and team.

CSV Structure
  • category: Method grouping (core, structural, risk, etc.)
  • method_name: Display name for the method
  • description: Rich explanation of what the method does, when to use it, and why it's valuable
  • output_pattern: Flexible flow guide using arrows (e.g., "analysis -> insights -> action")
Context Analysis
  • Use conversation history
  • Analyze: content type, complexity, stakeholder needs, risk level, and creative potential
Smart Selection
  1. Analyze context: Content type, complexity, stakeholder needs, risk level, creative potential
  2. Parse descriptions: Understand each method's purpose from the rich descriptions in CSV
  3. Select 5 methods: Choose methods that best match the context based on their descriptions
  4. Balance approach: Include mix of foundational and specialized techniques as appropriate

Step 2: Present Options and Handle Responses

Display Format
**Advanced Elicitation Options**
_If party mode is active, agents will join in._
Choose a number (1-5), [r] to Reshuffle, [a] List All, or [x] to Proceed:

1. [Method Name]
2. [Method Name]
3. [Method Name]
4. [Method Name]
5. [Method Name]
r. Reshuffle the list with 5 new options
a. List all methods with descriptions
x. Proceed / No Further Actions
Response Handling

Case 1-5 (User selects a numbered method):

  • Execute the selected method using its description from the CSV
  • Adapt the method's complexity and output format based on the current context
  • Apply the method creatively to the current section content being enhanced
  • Display the enhanced version showing what the method revealed or improved
  • CRITICAL: Ask the user if they would like to apply the changes to the doc (y/n/other) and HALT to await response.
  • CRITICAL: ONLY if Yes, apply the changes. IF No, discard your memory of the proposed changes. If any other reply, try best to follow the instructions given by the user.
  • CRITICAL: Re-present the same 1-5,r,x prompt to allow additional elicitations

Case r (Reshuffle):

  • Select 5 random methods from methods.csv, present new list with same prompt format
  • When selecting, try to think and pick a diverse set of methods covering different categories and approaches, with 1 and 2 being potentially the most useful for the document or section being discovered

Case x (Proceed):

  • Complete elicitation and proceed
  • Return the fully enhanced content back to the invoking skill
  • The enhanced content becomes the final version for that section
  • Signal completion back to the invoking skill to continue with next section

Case a (List All):

  • List all methods with their descriptions from the CSV in a compact table
  • Allow user to select any method by name or number from the full list
  • After selection, execute the method as described in the Case 1-5 above

Case: Direct Feedback:

  • Apply changes to current section content and re-present choices

Case: Multiple Numbers:

  • Execute methods in sequence on the content, then re-offer choices

Step 3: Execution Guidelines

  • Method execution: Use the description from CSV to understand and apply each method
  • Output pattern: Use the pattern as a flexible guide (e.g., "paths -> evaluation -> selection")
  • Dynamic adaptation: Adjust complexity based on content needs (simple to sophisticated)
  • Creative application: Interpret methods flexibly based on context while maintaining pattern consistency
  • Focus on actionable insights
  • Stay relevant: Tie elicitation to specific content being analyzed (the current section from the document being created unless user indicates otherwise)
  • Identify personas: For single or multi-persona methods, clearly identify viewpoints, and use party members if available in memory already
  • Critical loop behavior: Always re-offer the 1-5,r,a,x choices after each method execution
  • Continue until user selects 'x' to proceed with enhanced content, confirm or ask the user what should be accepted from the session
  • Each method application builds upon previous enhancements
  • Content preservation: Track all enhancements made during elicitation
  • Iterative enhancement: Each selected method (1-5) should:

1. Apply to the current enhanced version of the content 2. Show the improvements made 3. Return to the prompt for additional elicitations or completion

平台分布

Codex

34.01%
按下载量换算350

Claude

31.15%
按下载量换算321

Cursor

18.71%
按下载量换算193

Gemini CLI

8.95%
按下载量换算92

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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