/survey-generation
Generate complete academic survey papers using multi-LLM parallel outline generation, RAG-based subsection writing, citation validation, and local coherence enhancement. Based on AutoSurvey pipeline. Use for writing comprehensive literature surveys.
$ npx -y skills add lingzhi227/agent-research-skills --skill survey-generation --agent claude-codeHow it fires
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- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
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/survey-generation
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Generate complete academic survey papers using multi-LLM parallel outline generation, RAG-based subsection writing, citation validation, and local coherence enhancement. Based on AutoSurvey pipeline. Use for writing comprehensive literature surveys.
SKILL.md
survey-generation.SKILL.mdname: survey-generation
description: Generate complete academic survey papers using multi-LLM parallel outline generation, RAG-based subsection writing, citation validation, and local coherence enhancement. Based on AutoSurvey pipeline. Use for writing comprehensive literature surveys.
argument-hint: [topic]
Survey Generation
Generate complete academic survey papers with structured outline, RAG-based writing, and citation validation.
Input
- `$0` — Survey topic or research area
Scripts
Literature search
python ~/.claude/skills/deep-research/scripts/search_semantic_scholar.py \
--query "relevant search query" --max-results 50
References
- Survey prompts (outline, writing, citation, coherence): `~/.claude/skills/survey-generation/references/survey-prompts.md`
Workflow (from AutoSurvey)
Step 1: Collect Papers
1. Search Semantic Scholar / arXiv for papers on the topic 2. Collect 50-200 relevant papers with titles and abstracts 3. Filter by relevance and citation count
Step 2: Generate Outline (Multi-LLM Parallel)
1. Generate N rough outlines independently (parallel) 2. Merge outlines into a single comprehensive outline 3. Expand each section into subsections 4. Edit final outline to remove redundancies
Step 3: Write Subsections (RAG-Based)
For each subsection: 1. Retrieve relevant papers for the subsection topic 2. Generate content with inline citations `[paper_title]` 3. Enforce minimum word count per subsection 4. Only cite papers from the provided list
Step 4: Validate Citations
For each subsection: 1. Check that cited paper titles are correct 2. Verify citations support the claims made 3. Remove or correct unsupported citations 4. Use NLI (Natural Language Inference) for claim-source faithfulness
Step 5: Enhance Local Coherence
For each subsection: 1. Read previous and following subsections 2. Refine transitions and flow 3. Preserve core content and citations 4. Ensure smooth reading experience
Step 6: Convert Citations to BibTeX
1. Replace `[paper_title]` with `\cite{key}` 2. Generate BibTeX entries for all cited papers 3. Validate all citation keys exist in .bib file
Output Structure
survey/
├── main.tex # Complete survey paper
├── references.bib # All citations
├── outline.json # Survey outline
└── sections/ # Individual section files
Rules
- Only cite papers from the collected paper list — never hallucinate citations
- Each subsection must meet minimum word count
- No duplicate subsections across sections
- Citation validation is mandatory before final output
- Local coherence enhancement must preserve all citations
- The survey should be comprehensive and logically organized
Related Skills
- Upstream: [deep-research](../deep-research/), [literature-search](../literature-search/), [literature-review](../literature-review/)
- See also: [related-work-writing](../related-work-writing/)
Read more
name: survey-generation description: Generate complete academic survey papers using multi-LLM parallel outline generation, RAG-based subsection writing, citation validation, and local coherence enhancement. Based on AutoSurvey pipeline. Use for writing comprehensive literature surveys. argument-hint: [topic]
Survey Generation
Generate complete academic survey papers with structured outline, RAG-based writing, and citation validation.
Input
- `$0` — Survey topic or research area
Scripts
Literature search
python ~/.claude/skills/deep-research/scripts/search_semantic_scholar.py \ --query "relevant search query" --max-results 50
References
- Survey prompts (outline, writing, citation, coherence): `~/.claude/skills/survey-generation/references/survey-prompts.md`
Workflow (from AutoSurvey)
Step 1: Collect Papers
1. Search Semantic Scholar / arXiv for papers on the topic 2. Collect 50-200 relevant papers with titles and abstracts 3. Filter by relevance and citation count
Step 2: Generate Outline (Multi-LLM Parallel)
1. Generate N rough outlines independently (parallel) 2. Merge outlines into a single comprehensive outline 3. Expand each section into subsections 4. Edit final outline to remove redundancies
Step 3: Write Subsections (RAG-Based)
For each subsection: 1. Retrieve relevant papers for the subsection topic 2. Generate content with inline citations `[paper_title]` 3. Enforce minimum word count per subsection 4. Only cite papers from the provided list
Step 4: Validate Citations
For each subsection: 1. Check that cited paper titles are correct 2. Verify citations support the claims made 3. Remove or correct unsupported citations 4. Use NLI (Natural Language Inference) for claim-source faithfulness
Step 5: Enhance Local Coherence
For each subsection: 1. Read previous and following subsections 2. Refine transitions and flow 3. Preserve core content and citations 4. Ensure smooth reading experience
Step 6: Convert Citations to BibTeX
1. Replace `[paper_title]` with `\cite{key}` 2. Generate BibTeX entries for all cited papers 3. Validate all citation keys exist in .bib file
Output Structure
survey/ ├── main.tex # Complete survey paper ├── references.bib # All citations ├── outline.json # Survey outline └── sections/ # Individual section files
Rules
- Only cite papers from the collected paper list — never hallucinate citations
- Each subsection must meet minimum word count
- No duplicate subsections across sections
- Citation validation is mandatory before final output
- Local coherence enhancement must preserve all citations
- The survey should be comprehensive and logically organized
Related Skills
- Upstream: [deep-research](../deep-research/), [literature-search](../literature-search/), [literature-review](../literature-review/)
- See also: [related-work-writing](../related-work-writing/)
31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.
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