Transform rough research questions into executable USACF research prompts. Use when user says "research", "research this", "investigate", "deep dive", "researcher", or pastes a research topic. Generates complete multi-agent swarm configuration with algorithm selection, claude-flow commands, and adversarial review.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。
SkillHub CLI
skillhub install dorukardahan/research-reprompter打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。
Voice-to-research engineering for Claude Code. Transform rough questions into executable USACF swarm configurations.
| Version | Changes |
|---|---|
| v2.0 | Full USACF integration: algorithm selection, claude-flow commands, adversarial review, fact-checking, memory namespaces |
| v1.0 | Initial version based on Reprompter v4.1 |
Turn your rough research questions into complete, executable multi-agent research prompts using the USACF framework.
The Problem:
The Solution: Smart interview → USACF super-prompt with all phases, agents, and commands.
Accept the user's rough research question (dictated, typed messily, or incomplete).
Trigger words: research, investigate, deep dive, analyze, research this
Auto-detect complexity to select algorithm:
Gather:
Generate complete executable configuration with:
这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。
# Researcher v2.0 (USACF Research Generator) > **Voice-to-research engineering for Claude Code. Transform rough questions into executable USACF swarm configurations.** ## Changelog | Version | Changes | |---------|---------| | **v2.0** | Full USACF integration: algorithm selection, claude-flow commands, adversarial review, fact-checking, memory namespaces | | v1.0 | Initial version based on Reprompter v4.1 | ## Purpose Turn your rough research questions into complete, executable multi-agent research prompts using the USACF framework. **The Problem:** - Research questions are often vague and unstructured - Manual setup of research swarms is tedious - Missing adversarial review leads to blind spots - No systematic algorithm selection **The Solution:** Smart interview → USACF super-prompt with all phases, agents, and commands. --- ## Process (4 steps) ### Step 1: Receive raw input Accept the user's rough research question (dictated, typed messily, or incomplete). **Trigger words:** `research`, `investigate`, `deep dive`, `analyze`, `research this` ### Step 2: Complexity detection **Auto-detect complexity to select algorithm:** - Simple (< 20 words, single topic) → CoT, 1-3 agents - Medium (branching, comparison) → ToT, 4-8 agents - Complex (comprehensive, multi-domain) → GoT, 9-15 agents ### Step 3: Smart interview (gather user input) Gather: 1. **Research Title** - Name for this research 2. **Subject** - What we're researching 3. **Subject Type** - Product / Software / Business / Process / Organization 4. **Research Type** - Competitive / Gap / Technical / Due Diligence / Market 5. **Objectives** - What to find out (1-20, one per line) 6. **Constraints** - Focus areas, limitations (optional) 7. **Depth** - CoT / ToT / GoT 8. **Output** - Brief / Full Report / Action Plan / Raw ### Step 4: Generate USACF super-prompt + score Generate complete executable configuration with: - Initialization commands - All phase agents (Discovery, Analysis, Adversarial, Syn...
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