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lingzhi227/agent-research-skills1.2k installs

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-generation
view source ↗

Is 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

  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

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>