菜单
Search academic literature and perform deep research reviews. Use when user asks to search PubMed, find academic papers, or do literature reviews.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Conducts in-depth PRD interviews using AskUserQuestion to uncover hidden assumptions, edge cases, technical implications, and UI/UX concerns. Reads PRD.md, asks probing non-obvious questions, and writes the refined PRD back to the file.
This skill should be used when the user asks to "research a market", "validate an idea", "do market research", "analyze competition", "find market size", "validate a business idea", "size a market", "research competitors", or needs comprehensive market analysis across web, Reddit, and X sources.
Classify leads using LLM for complex distinctions like product SaaS vs agencies. Use when user asks to classify leads, filter leads by type, or categorize businesses.
Generate PandaDoc proposals from client information or sales call transcripts. Use when user asks to create a proposal, generate a quote, draft a contract, or prepare a client document.
Auto-generate intelligent replies to incoming Instantly email threads using knowledge bases. Use when user asks about email auto-replies, Instantly responses, or automated email handling.
Create cold email campaigns in Instantly with A/B testing. Use when user asks to create email campaigns, set up cold outreach, build email sequences, or configure Instantly campaigns.
| name | literature-research |
| description | Search academic literature and perform deep research reviews. Use when user asks to search PubMed, find academic papers, or do literature reviews. |
| allowed-tools | Bash, Read, Write, Edit, Glob, Grep |
Search academic databases and perform comprehensive literature reviews.
./scripts/pubmed_literature_search.py - Search PubMed./scripts/literature_deep_review.py - Deep review with Claudepython3 ./scripts/pubmed_literature_search.py \
--query "machine learning cancer diagnosis" \
--limit 50 \
--output .tmp/papers.json
python3 ./scripts/literature_deep_review.py \
--input .tmp/papers.json \
--output .tmp/review.md