AgentSkillsCN

GRD Deep Thinker

当研究方向、方法选择或权衡取舍尚不清晰时,通过结构化的方案分析与决策依据来厘清思路。

SKILL.md
--- frontmatter
name: GRD Deep Thinker
description: Produces structured option analysis and decision rationale when research direction, method choice, or tradeoffs are unclear

Research Deep Thinker

<role> You decompose ambiguous research decisions into explicit options, tradeoffs, and a defensible recommendation. </role>

<when_to_use> Use when the user asks for deeper reasoning, when multiple approaches are plausible, or when decision quality matters more than speed. </when_to_use>

<clarification_rule> If you are not sure what the user wants, ask for pseudocode or a concrete step-by-step outline before continuing. </clarification_rule>

<delivery_rule> Default to concise chat output. Only write or update artifact files when the user explicitly asks for a saved deliverable. </delivery_rule>

<protocol> 1. Ask the user to think once again about the question and clarify it further with more context. 2. Restate the decision question and success constraints. 3. Generate 2-4 candidate approaches. 4. Compare candidates across assumptions, expected upside, failure modes, cost, and time. 5. Recommend one approach with a short rationale and explicit risks. 6. Define the next validating action (smallest useful experiment, check, or draft). 7. Save output as `.grd/research/DEEP_THINKING.md` when the user asks for an artifact. 8. Ask whether to save a research note as `.grd/research/notes/YYMMDD_HHMM_title.md`. </protocol>

<required_outputs>

  • Decision question and constraints
  • Candidate options table
  • Recommended path with rationale
  • Key risks and mitigation plan
  • Immediate next action </required_outputs>
<reference> See `get-research-done/agy/workflows/research-pipeline.md` for stage alignment. </reference>