Agent skill

Research Survey

by EvoScientist in EvoScientist/EvoSkills

Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary…

Apache-2.0Auto-check passedResearch & Science

Install Research Survey

skills CLI
$ npx skills add EvoScientist/EvoSkills --skill research-survey -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install EvoScientist/EvoSkills research-survey --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/EvoScientist/EvoSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research-survey .claude/skills/research-survey && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
research-survey
GitHub stars
478
Used in
3 other repos
Token cost
~2.5k tokens
SKILL.md length
1,048 words
Files
4 (incl. references, assets)
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary…

  • Works in 6 steps: Generate Outline → Draft Survey → Expand Sections → …
  • : user wants a literature review
  • SKILL.md covers When to Use, When NOT to Use, Dependency: paper-navigator and Stage 1: Generate Outline, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Research Survey is an agent skill from EvoScientist/EvoSkills. Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly. Produces survey-grade output with taxonomy-based method analysis, LaTeX formalizations, comparative tables, and dense citations. Use when: user wants a literature review, research survey, field overview, or systematic synthesis of multiple papers. Do NOT use for finding/searching…

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files and assets (for example `assets/survey-template.md`, `references/section-quality-checklist.md` and `references/survey-methodology.md`).

It sits in Research & Science, covering Literature review, Brainstorming and Scientific writing. It works with LaTeX. The repository describes itself as: 🧬 Extend EvoScientist with Installable Skill & Knowledge Packs. The licence is Apache-2.0.

When your agent uses it

  • : user wants a literature review
  • Research survey
  • Systematic synthesis of multiple papers
  • Finding/searching papers (use paper-navigator)

Example prompts

  • “Use the research-survey skill to generate structured literature survey reports from collected papers using a multi-stage pipeline: outline…”
  • “/research-survey”

Requirements

  • Pre-approved tools (allowed-tools): write_file, edit_file, read_file, think_tool

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Generate Outline
  2. Draft Survey
  3. Expand Sections
  4. Generate Section Summaries
  5. Refine Summary Sections
  6. Assemble Final Survey

What it can do on your machine

Read from SKILL.md and the folder at commit 9a9f8cf. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • write_file
    • edit_file
    • read_file
    • think_tool

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Research Survey loads about 2.5k tokens when it runs, and up to ~4.6k if it reads all its reference files. Until then it costs about 168 tokens; SKILL.md has 1,048 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~168
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from EvoScientist/EvoSkills at commit 9a9f8cf, republished under its Apache-2.0 licence (© EvoScientist). 1,048 words, ~2,543 tokens.

Download SKILL.mdSave it as .claude/skills/research-survey/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
research-survey
description
Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly. Produces survey-grade output with taxonomy-based method analysis, LaTeX formalizations, comparative tables, and dense citations. Use when: user wants a literature review, research survey, field overview, or systematic synthesis of multiple papers. Do NOT use for finding/searching papers (use paper-navigator), generating research ideas (use research-ideation), or writing a paper's Related Work section (use paper-writing).
allowed-tools
write_file, edit_file, read_file, think_tool
metadata.author
EvoScientist
metadata.version
1.0.0
metadata.tags
core, research, literature, survey, synthesis

Research Survey

Generates high-quality, survey-grade literature reviews from papers collected by paper-navigator.

paper-navigator (collect 30-120 papers)
    ↓
Stage 1: Generate Outline (query-type adaptive structure)
    ↓
Stage 2: Draft Survey (outline + top-30 papers)
    ↓
Stage 3: Expand Sections (draft + all papers, section-by-section)
    ↓
Stage 4: Generate Section Summaries
    ↓
Stage 5: Refine Summary Sections (Abstract/Intro/Conclusion)
    ↓
Stage 6: Assemble + References

When to Use

  • User asks for a "literature review", "survey", "field overview", or "systematic review"
  • User has collected papers and wants them synthesized into a structured report
  • User wants to understand the full landscape of a research field

When NOT to Use

  • Finding papers → use paper-navigator first, then come here
  • Generating research ideas → use research-ideation
  • Writing a Related Work section for a paper → use paper-writing

Dependency: paper-navigator

This skill requires papers as input. If the user hasn't provided papers, first invoke paper-navigator (Workflow 1, target 30-120 papers) to collect them.

CRITICAL: All paper discovery MUST use the paper-navigator skill and its scripts (scholar_search, citation_traverse, arxiv_monitor, recommend, etc.). Using WebSearch, WebFetch, or any generic web search tool for finding papers is PROHIBITED. Generic web search cannot access Semantic Scholar, citation graphs, or academic recommendation systems. Only paper-navigator provides the academic search infrastructure needed for survey-quality literature collection.


Stage 1: Generate Outline

This is a two-phase process. Different fields have different survey conventions — a clinical systematic review looks nothing like a CS methods survey. First generate a domain-appropriate template, then create the detailed outline.

Phase 1A: Generate Domain-Specific Survey Template

Before outlining, identify the field and adapt the structure:

  1. Identify the field from the user's goal and collected papers
  2. Select section names and organization logic using the field-specific conventions in assets/survey-template.md (e.g., medicine organizes by intervention type and follows PRISMA; chemistry organizes by reaction class; social sciences organize by theoretical perspective)
  3. Add field-specific sections (e.g., Risk of Bias Assessment for medicine, Structure-Property Relationships for materials, Ethical Considerations for human-subjects research)
  4. Determine comparison table dimensions appropriate to the field
Phase 1B: Create Detailed Outline

With the domain-specific template as the framework, generate the outline:

Query Type Classification
TypeExampleStructure
A: Single-topic deep dive"Catalyst design for electrochemical CO2 reduction"Intro → Problem Definition → Methods (by mechanism/approach) → Evaluation → Challenges → Conclusion
B: Multi-topic parallel"Drug resistance mechanisms and therapeutic strategies in cancer immunotherapy"Intro → Topic 1 (definition + methods) → Topic 2 (definition + methods) → Evaluation → Challenges → Conclusion
C: Pipeline/stage-based"From sample preparation to data analysis in single-cell RNA sequencing"Chapters organized by workflow stages
Outline Requirements

The outline is NOT a simple heading list — it's a blueprint with meta-instructions for each section. For each ## Section:

  • Include [Instruction: ...] specifying what the section must contain
  • Specify required tables with field-appropriate columns
  • For main body sections: mandate taxonomy by underlying principle/mechanism, NOT chronology
  • Include any field-required elements (e.g., PRISMA flowchart for medical systematic reviews, mathematical formalism for physics)

See references/survey-methodology.md for full outline generation rules and assets/survey-template.md for field-specific conventions.


Stage 2: Draft Survey

Generate a complete draft from the outline using the top-30 most relevant papers.

  • Use numbered citations [1], [2, 3] throughout
  • Follow the outline's meta-instructions strictly
  • Each methods section must build a taxonomy and include comparison tables
  • Problem definition must include LaTeX formalization ($$...$$)

Stage 3: Expand Sections

Expand each non-summary section using all collected papers (30-120). This is where survey-grade depth is achieved.

Section Expansion Targets
Section TypeTarget LengthFocus
Methods6000+ words per paradigm chapterTechnical narratives, mechanism analysis, comparison tables
Evaluation3500+ wordsBenchmark taxonomy, metric analysis, SOTA summary
Challenges3000+ wordsProblem definition + evidence + opportunity per challenge
Applications3000+ wordsReal-world use cases with specific achievements
Problem Definition2000+ wordsLaTeX formalization, constraints, assumptions
Other2500+ wordsDefault
Expansion Rules
  1. Thematic coherence: Keep same themes and narrative flow as draft — don't introduce unrelated topics
  2. Cite comprehensively: Use as many relevant papers from the full collection as possible
  3. Survey-grade depth: Multi-paragraph technical narratives per method family, not shallow bullet points
  4. For each paradigm/method family, include:
    • Technical narrative: How it works, theoretical assumptions, nuances between papers
    • Critical analysis: Why effective, trade-offs, failure modes
    • Comparative analysis table: Method | Core Mechanism | Key Advantage | Limitation | Performance

Show full SKILL.md (410 more words)Show less

Stage 4: Generate Section Summaries

After all content sections are expanded, generate a condensed summary for each major section:

  1. Summarize each expanded section in 150-300 words
  2. Preserve the key taxonomy, representative methods, and main trade-offs
  3. Keep citation anchors so later summary sections remain grounded

These section summaries become the shared context for the final abstract, introduction, and conclusion.


Stage 5: Refine Summary Sections

After all content sections are expanded, refine the summary sections (Abstract, Introduction, Conclusion):

  1. Use all section summaries as context to rewrite Abstract, Introduction, Conclusion
  2. This ensures summary sections accurately reflect the full survey content
Summary Section Standards

Abstract (300-500 words):

  • Continuous narrative, NO bullet points or bold labels
  • Must cover: background → gap → scope → key findings → outlook

Introduction:

  • Continuous narrative, NO subsections or bullet points
  • Must cover: research background → why traditional methods fail → method summary → scope & organization

Conclusion:

  • Summarize findings, state which paradigm is most promising
  • Respond to user's original research goal
  • Provide clear "next step" recommendation

Stage 6: Assemble Final Survey

Assemble sections in outline order, then append formatted references:

**1. Title** (Year). _Authors_. *Venue*. Citations: N. [[Link]](url)

Save to /artifacts/survey-{topic}-{date}.md.


Core Quality Principles

  1. Build taxonomy, don't enumerate: Cluster papers by technical mechanism, not chronology. This is the defining characteristic of a survey vs. a summary.

  2. Critical insight over description: For EVERY method, analyze WHY it works, WHAT trade-off it makes, WHERE it fails. This separates survey-grade writing from shallow summaries.

  3. Goal-centric filtering: Every piece of information must answer "How does this help achieve the research goal?" Discard information that doesn't serve the goal, even if it's interesting.

  4. Strict terminology fidelity: Use the user's exact technical terms. Do NOT drift to related but different concepts.

  5. Dense citations: Ground ALL claims with numbered citations [X]. Nearly every sentence should reference at least one paper.

  6. Zero vagueness: Replace generic statements with specific method names, dataset names, metric values, and problem descriptions.

  7. Visual structure: Use Markdown tables extensively — paradigm comparison, intra-paradigm method comparison, benchmark tables, metric tables.


Reference Materials

ResourceLocationPurpose
Multi-stage pipeline detailsreferences/survey-methodology.mdFull methodology: outline rules, section standards, expansion targets
Section quality checklistreferences/section-quality-checklist.mdPer-section verification checklist before finalizing
Survey output templateassets/survey-template.mdEnglish Markdown template with section structure, table formats, and placeholder guidance

Handoff

From → ToWhen
paper-navigator → herePapers collected, user wants synthesis
Here → research-ideationSurvey reveals research gaps worth pursuing
Here → paper-writingSurvey informs Related Work section of a paper
Here → paper-planningSurvey provides literature context for story design

© EvoScientist, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references, assets) in skills/research-survey of EvoScientist/EvoSkills.

  • SKILL.md
  • assets/survey-template.md
  • references/section-quality-checklist.md
  • references/survey-methodology.md

Open the folder on GitHubat commit 9a9f8cf

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in EvoScientist/EvoSkills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Research Survey next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Research Survey compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Survey this skillEvoScientist/EvoSkills4783 repos~2.5kAutomated safety check: PassApache-2.0
Research Depth ControlBingHanOfUESTC/open_agent_team106—~989Automated safety check: PassMIT
Academic Paper Writing PipelineImbad0202/academic-research-skills51k—~16kAutomated safety check: PassCustom licence
Paper SkillcLin-c/paper-skill119—~2.6kAutomated safety check: PassMIT
Paper NavigatorAI4Scientist/nano-scientist128—~7.7kAutomated safety check: NotesNone
Research Paper WritingAlexAI-MCP/hermes-CCC135—~1.2kAutomated safety check: NotesMIT

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Works with

Questions about Research Survey

What does Research Survey do?

Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary…. Research Survey is an agent skill from EvoScientist/EvoSkills. Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly.

When should I use Research Survey?

Research Survey fits situations like: : user wants a literature review; research survey; systematic synthesis of multiple papers; finding/searching papers (use paper-navigator).

How do I install Research Survey in Claude Code?

Run `npx skills add EvoScientist/EvoSkills --skill research-survey -a claude-code`. Or copy the skill folder (skills/research-survey in EvoScientist/EvoSkills) into .claude/skills/research-survey in your project. Claude Code loads it when a task matches its description.

How do I install Research Survey in Codex?

Run `npx skills add EvoScientist/EvoSkills --skill research-survey -a codex`. Or copy the skill folder (skills/research-survey in EvoScientist/EvoSkills) into .agents/skills/research-survey in your project. Codex loads it when a task matches its description.

Can I use Research Survey in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add EvoScientist/EvoSkills --skill research-survey -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-survey, .gemini/skills/research-survey, .github/skills/research-survey and .opencode/skills/research-survey in your project.

What does Research Survey need to run?

SKILL.md names no scripts, command-line tools or credentials: Research Survey is instructions for the agent only. Its frontmatter pre-approves these tools: write_file, edit_file, read_file, think_tool.

Does Research Survey access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Research Survey safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Research Survey use?

Research Survey is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research Survey use?

About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Research Survey?

Skills that share tags, products or a category with Research Survey: Research Depth Control (BingHanOfUESTC/open_agent_team, 106 stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars), Paper Skill (cLin-c/paper-skill, 119 stars) and Paper Navigator (AI4Scientist/nano-scientist, 128 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Survey?

EvoScientist (a GitHub organization) maintains it in EvoScientist/EvoSkills, which has 478 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on September 30, 2026.

Source: EvoScientist/EvoSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.