Skills Plugins MCP Prompt Model 博客 我的中心

idea-generation

Use this when the user wants research ideas, innovation points, or to find research gaps (找研究方向, 生成创新点). Generates 5 ideas from collected papers, identifies gaps, proposes novel methods with citations. Requires papers in workspace.

DeepseekModel 官方收录技能 质量 优秀 · 90 v1.0.0

获取

https://deepseekmodel.com/api/download.php?id=tsingyuai-scientify-skills-idea-generation-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name idea-generation description Use this when the user wants research ideas, innovation points, or to find research gaps (找研究方向, 生成创新点). Generates 5 ideas from collected papers, identifies gaps, proposes novel methods with citations. Requires papers in workspace. metadata {"openclaw":{"emoji":"💡","requires":{"bins":"[Truncated]"}}} Idea Generation Don't ask permission. Just do it. Generate innovative research ideas grounded in literature analysis. This skill reads existing papers, identifies research gaps, and produces 5 distinct ideas with citations. Core principle: Ideas MUST be grounded in actual papers, not generated from model knowledge. Outputs go to ideas/ . Step 1: Check Workspace Resources First, check what resources already exist: ls papers/ 2>/dev/null | head -20 ls knowledge/ 2>/dev/null Assess Available Resources Resource Location Status Papers papers/ Count: ? Knowledge knowledge/_index.md Exists: Y/N Step 2: Ask User About Search Strategy Based on workspace state, ask user: If papers exist (≥5): 📚 Found {N} papers in workspace from previous survey. Options: Use existing papers - Generate ideas from current collection Search more - Run /research-collect to expand collection Quick search - Add 5-10 more papers on specific topic If no papers: 📭 No papers found in workspace. To generate grounded ideas, I need literature. Options: Run /research-collect - Comprehensive search (100+ papers, recommended) Quick search - Fetch 10-15 papers on your topic now You provide papers - Point me to existing PDFs/tex files Step 3: Acquire Resources (if needed) Option A: Delegate to /research-collect (Recommended) If user wants comprehensive search: Please run: /research-collect {topic} This will: - Search 100+ papers systematically - Filter by relevance (score ≥4) - Cluster into research directions - Save to papers/ After survey completes, run /idea-generation again. Option B: Quick Search (5-10 papers) For fast iteration, do minimal search: Search papers: arxiv_search({ query: "{user_topic}", max_results: 10 }) openalex_search({ query: "{user_topic}", max_results: 10 }) Download papers: 按 /paper-download 的方式下载到 papers/ Clone reference repos (optional): gh search repos "{paper_title} implementation" -- limit 5 -- sort stars git clone --depth 1 {repo_url} repos/{name} Step 4: Analyze Literature Prerequisites: At least 5 papers in papers/ 4.1 Read Papers For each paper, extract: Core contribution (1 sentence) Key method/formula Limitations mentioned Future work suggestions Long papers (>50KB): See references/reading-long-papers.md 4.2 Identify Research Gaps Look for: Common limitations across papers Unexplored technique combinations Scalability issues Assumptions that could be relaxed Document gaps in ideas/gaps.md : # Research Gaps Identified ## Gap 1: [Description] - Mentioned in: [paper1], [paper2] - Why important: ... ## Gap 2: [Description] ... Step 5: Generate 5 Ideas Create ideas/idea_1.md through idea_5.md using template in references/idea-template.md . Requirements: Each idea cites ≥2 papers by arXiv ID Use different strategies: Idea Strategy 1 Combination - merge 2+ techniques 2 Simplification - reduce complexity 3 Generalization - extend to new domain 4 Constraint relaxation - remove assumption 5 Architecture innovation - new design ❌ REJECTED if: No arXiv IDs cited, or ideas not grounded in literature Step 6: Select and Enhance Best Idea 6.1 Score All Ideas Idea Novelty Feasibility Impact Total 1 /5 /5 /5 /15 ... 6.2 Enhance Selected Idea Create ideas/selected_idea.md with: Detailed math (loss functions, gradients) Architecture choices Hyperparameters Implementation roadmap Step 7: Code Survey Map idea concepts to reference implementations. See references/code-mapping.md for template. Output: ideas/implementation_report.md Step 8: Summary Create ideas/summary.md : All 5 ideas with scores Selected idea details Next steps: /research-pipeline to implement Commands User Says Action "Generate ideas for X" Check workspace → ask strategy → generate "I have papers, generate ideas" Skip to Step 4 "Enhance idea N" Jump to Step 6 "Map to code" Jump to Step 7 Integration Before: /research-collect to collect papers After: /research-pipeline to implement selected idea Alternative: /write-review-paper to write survey instead
Agent 识别该技能的关键词,点击任意一个即可复制。

该技能未提供触发词。

下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。