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Skills/lingzhi227/agent-research-skills/survey-generation
survey-generation logo

survey-generation

lingzhi227/agent-research-skills
816 installs133 stars
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Installation

npx skills add https://github.com/lingzhi227/agent-research-skills --skill survey-generation

Summary

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

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, literature-search, literature-review
  • See also: related-work-writing

Score

0–100
63/ 100

Grade

C

Popularity15/30

816 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Survey Generation skill score badge previewScore badge

Markdown

[![Survey Generation skill](https://www.remoteopenclaw.com/skills/lingzhi227/agent-research-skills/survey-generation/badges/score.svg)](https://www.remoteopenclaw.com/skills/lingzhi227/agent-research-skills/survey-generation)

HTML

<a href="https://www.remoteopenclaw.com/skills/lingzhi227/agent-research-skills/survey-generation"><img src="https://www.remoteopenclaw.com/skills/lingzhi227/agent-research-skills/survey-generation/badges/score.svg" alt="Survey Generation skill"/></a>

Survey Generation FAQ

How do I install the Survey Generation skill?

Run “npx skills add https://github.com/lingzhi227/agent-research-skills --skill survey-generation” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Survey Generation skill do?

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. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Survey Generation skill free?

Yes. Survey Generation is a free, open-source skill published from lingzhi227/agent-research-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Survey Generation work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Survey Generation works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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