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bmad-advanced-elicitationbmad 高级诱导

Agent Skill

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。

总安装

3,182

周安装

130

GitHub Stars

45,884

下载量

1,030
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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-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

简介

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。

SKILL.md

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

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

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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

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

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权限和风险

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安装前确认

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