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.
How do I install this agent skill?
npx skills add https://github.com/lingzhi227/agent-research-skills --skill survey-generationIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill facilitates academic survey generation through a multi-step workflow. It leverages local scripts and organizes output into structured directories. A low-risk surface for indirect prompt injection is present because the skill ingests metadata from external academic papers without explicit sanitization or the use of protective boundary markers.
- Socketpass
No alerts
- Snykwarn
Risk: MEDIUM · No issues
- Runlayerwarn
2/2 files flagged
- ZeroLeakspass
Score: 93/100 · 2 sections analyzed
What does this agent skill do?
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
- Search Semantic Scholar / arXiv for papers on the topic
- Collect 50-200 relevant papers with titles and abstracts
- Filter by relevance and citation count
Step 2: Generate Outline (Multi-LLM Parallel)
- Generate N rough outlines independently (parallel)
- Merge outlines into a single comprehensive outline
- Expand each section into subsections
- Edit final outline to remove redundancies
Step 3: Write Subsections (RAG-Based)
For each subsection:
- Retrieve relevant papers for the subsection topic
- Generate content with inline citations
[paper_title] - Enforce minimum word count per subsection
- Only cite papers from the provided list
Step 4: Validate Citations
For each subsection:
- Check that cited paper titles are correct
- Verify citations support the claims made
- Remove or correct unsupported citations
- Use NLI (Natural Language Inference) for claim-source faithfulness
Step 5: Enhance Local Coherence
For each subsection:
- Read previous and following subsections
- Refine transitions and flow
- Preserve core content and citations
- Ensure smooth reading experience
Step 6: Convert Citations to BibTeX
- Replace
[paper_title]with\cite{key} - Generate BibTeX entries for all cited papers
- 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, literature-search, literature-review
- See also: related-work-writing
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/lingzhi227/agent-research-skills/survey-generation">View survey-generation on skillZs</a>