Research
Plugin
agent-research-skills
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.
Plugin Signal60/100Solid
maintained30
capable73
documented100
adopted52
Install
$ npx -y skills add lingzhi227/agent-research-skills --agent claude-code
In this plugin
- skills
- algorithm-design
- atomic-decomposition
- backward-traceability
- citation-management
- code-debugging
- data-analysis
- deep-research
- excalidraw-skill
- experiment-code
- experiment-design
- figure-generation
- github-research
- idea-generation
- latex-formatting
- literature-review
- literature-search
- math-reasoning
- novelty-assessment
- paper-assembly
- paper-compilation
- paper-revision
- paper-to-code
- paper-writing-section
- rebuttal-writing
- related-work-writing
- research-planning
- self-review
- slide-generation
- survey-generation
- symbolic-equation
- table-generation
- commands
What's inside
Skill(31 skills)
/algorithm-designDesign algorithms with LaTeX pseudocode and UML diagrams. Generate algorithmic environments, Mermaid class/sequence diagrams, and ensure consistency between pseudocode and implementation. Use when formalizing methods for a paper./atomic-decompositionDecompose research ideas into atomic, self-contained concepts with bidirectional math-code mapping. For each concept, extract the math formula from papers and find code implementations. Use for complex system papers requiring formal grounding./backward-traceabilityMake every number in the final PDF traceable to the exact code line that produced it. Uses \hypertarget/\hyperlink LaTeX commands and \num{formula} evaluated at compile time. Use for reproducibility and data integrity verification./citation-managementManage BibTeX citations for LaTeX papers. Harvest missing citations from a draft using Semantic Scholar, validate cite keys against .bib files, deduplicate entries, and format bibliography. Use when working with references, BibTeX, or citations./code-debuggingDebug experiment code with structured error analysis. Categorize errors, apply targeted fixes with retry logic, and use reflection to prevent recurring issues. Use when experiment code fails or produces incorrect results./data-analysisGenerate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper.
- /deep-research
- /excalidraw-skill
- /experiment-code
- /experiment-design
- /figure-generation
- /github-research
- /idea-generation
- /latex-formatting
- /literature-review
- /literature-search
- /math-reasoning
- /novelty-assessment
- /paper-assembly
- /paper-compilation
- /paper-revision
- /paper-to-code
- /paper-writing-section
- /rebuttal-writing
- /related-work-writing
- /research-planning
- /self-review
- /slide-generation
- /survey-generation
- /symbolic-equation
- /table-generation
Command(1 command)
README
agent-research-skills
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. See SKILLS_DESIGN.md for the original design specifications.
Installation
One-line install
npx skills add lingzhi227/agent-research-skills -g -a claude-code
Use the
-g(global) flag. Scripts use~/.claude/skills/paths that require global installation.
Post-install setup
git clone https://github.com/lingzhi227/agent-research-skills.git /tmp/agent-research-skills
/tmp/agent-research-skills/install.sh
rm -rf /tmp/agent-research-skills
This installs slash commands, checks Python dependencies, and verifies script syntax.
Optional dependencies
| Package | Required by | Install |
|---|---|---|
| Python 3 | All scripts | brew install python3 |
| PyMuPDF | self-review, deep-research (PDF parsing) | pip install PyMuPDF |
| numpy + scipy | data-analysis (statistical tests) | pip install numpy scipy |
Optional configuration
-
Semantic Scholar API key (higher rate limits for literature search):
- Get one at https://www.semanticscholar.org/product/api#api-key
- Save in
~/keys.md:S2_API_Key: your-key-here
-
Output directory: Deep research outputs go to
~/deep-research-output/by default.
Available Skills (31)
Phase 0: Research Discovery & Planning
| Skill | Description | Scripts |
|---|---|---|
| github-research | 6-phase GitHub repo discovery, analysis, and integration planning for research topics | 13 scripts: search, clone, analyze structure/deps/impls, compare, compile report |
| deep-research | 6-phase systematic literature survey (frontier → survey → deep dive → code → synthesis → report) | 7 scripts: search APIs, PDF extraction, paper DB, BibTeX, report compilation |
| literature-search | Multi-source academic search (Semantic Scholar, arXiv, OpenAlex, CrossRef) with ranking | 4 scripts: search_crossref.py, download_arxiv_source.py, search_openalex.py + shared |
| literature-review | Multi-perspective dialogue simulation with expert personas for grounded literature review | Shares search scripts |
| idea-generation | Generate and score research ideas (Interestingness/Feasibility/Novelty) with iterative refinement | 1 script: novelty_check.py |
| novelty-assessment | Harsh-critic novelty evaluation with up to 10 rounds of literature search | Shares search scripts |
| research-planning | 4-stage research plan design with task dependency graphs | Prompt-only |
Phase 1: Method Design
| Skill | Description | Scripts |
|---|---|---|
| atomic-decomposition | Decompose ideas into atomic concepts with bidirectional math ↔ code mapping | Prompt-only |
| algorithm-design | Algorithm pseudocode (LaTeX) + UML diagrams (Mermaid) with consistency verification | Prompt-only |
| math-reasoning | Derivations, proofs, formalization, statistical test selection, notation tables | Prompt-only |
| symbolic-equation | LLM-guided evolutionary search for scientific equation discovery | Prompt-only |
Phase 2: Experiment Pipeline
| Skill | Description | Scripts |
|---|---|---|
| experiment-design | 4-stage progressive experiment planning (implement → tune → research → ablate) | 1 script: design_experiments.py |
| experiment-code | ML training/evaluation pipeline generation with iterative improvement | Prompt-only |
| code-debugging | Structured error analysis with categorization and 4-retry fix loop | Prompt-only |
| data-analysis | Statistical analysis with 4-round code review and appropriate test selection | 2 scripts: stat_summary.py, format_pvalue.py |
Phase 3: Paper Writing
| Skill | Description | Scripts |
|---|---|---|
| paper-writing-section | Section-by-section writing with section-specific guidance and two-pass refinement | Prompt-only |
| related-work-writing | Related Work section with thematic organization and compare-and-contrast style | Prompt-only |
| survey-generation | Complete survey paper via RAG-based subsection writing with citation validation | Shares search scripts |
| paper-to-code | Convert paper PDF to runnable code repo (Planning → Analysis → Coding pipeline) | Prompt-only |
Phase 4: Figures, Tables & Citations
| Skill | Description | Scripts |
|---|---|---|
| figure-generation | Publication-quality matplotlib figures with VLM feedback loop (10 figure types) | 1 script: figure_template.py |
| table-generation | JSON/CSV → LaTeX booktabs tables with bold-best, significance stars, multi-dataset | 1 script: results_to_table.py |
| citation-management | BibTeX harvesting, validation, deduplication, and auto-fix | 2 scripts: harvest_citations.py, validate_citations.py |
| backward-traceability | Every PDF number hyperlinks to the code line that produced it | 1 script: ref_numeric_values.py |
Phase 5: LaTeX & Compilation
| Skill | Description | Scripts |
|---|---|---|
| latex-formatting | Conference templates (ICML/ICLR/NeurIPS/AAAI/ACL), formatting fixes, pre-submission checks | 2 scripts: latex_checker.py, clean_latex.py |
| paper-compilation | Full pdflatex+bibtex pipeline with auto-fix error correction loop | 2 scripts: compile_paper.py, fix_latex_errors.py |
| excalidraw-skill | Programmatic Excalidraw diagramming via MCP tools with quality verification | MCP server (7 CJS files) |
Phase 6: Review & Polish
| Skill | Description | Scripts |
|---|---|---|
| self-review | 3-persona automated review (NeurIPS form) with reflection and meta-review | 2 scripts: extract_pdf_text.py, parse_pdf_sections.py |
| paper-revision | Map reviewer concerns to sections, apply targeted edits, verify improvements | Prompt-only |
| rebuttal-writing | Point-by-point rebuttal with evidence-based responses | Prompt-only |
| slide-generation | Paper → Beamer slides (extract elements, generate skeleton, simplify) | 1 script: extract_paper_elements.py |
| paper-assembly | End-to-end pipeline orchestrator with 9-phase checkpointing | 1 script: assembly_checker.py |
Usage
Slash commands
/research transformer architectures for long-context reasoning
Natural language (skills activate automatically)
"Analyze GitHub repos for multi-agent coordination research"
"Do a literature review on protein folding with LLMs"
"Write the Methods section of my paper"
"Generate a comparison table from results.json"
"Review my paper draft before submission"
"Make slides from my paper"
"Check if my idea is novel"
"Design experiments for my contrastive learning method"
Direct script usage
# Search GitHub repos for a research topic
python ~/.claude/skills/github-research/scripts/search_github.py --query "multi-agent LLM coordination" --max-results 50 --output repos.jsonl
# Analyze a cloned repo's structure
python ~/.claude/skills/github-research/scripts/analyze_repo_structure.py --repo-dir ./my-repo --output analysis.json
# Search literature
python ~/.claude/skills/literature-search/scripts/search_crossref.py --query "attention mechanism" --rows 10
# Validate citations
python ~/.claude/skills/citation-management/scripts/validate_citations.py --tex paper/main.tex --bib paper/references.bib
# Generate experiment design
python ~/.claude/skills/experiment-design/scripts/design_experiments.py --method "contrastive learning" --task classification --format markdown
# Format p-values
python ~/.claude/skills/data-analysis/scripts/format_pvalue.py --values "0.001 0.05 0.23" --format latex
# Extract paper elements for slides
python ~/.claude/skills/slide-generation/scripts/extract_paper_elements.py --tex main.tex --output slides.tex
# Check paper pipeline completeness
python ~/.claude/skills/paper-assembly/scripts/assembly_checker.py --dir paper/ --verbose
Architecture
All skills follow the same structure:
skills/<skill-name>/
├── SKILL.md # Skill definition (prompt, workflow, rules)
├── scripts/ # Executable tools (optional)
│ └── *.py # CLI scripts with argparse, docstring headers
└── references/ # Reference docs (optional)
└── *.md # Templates, API docs, patterns
Design principles:
- Scripts are stdlib-only where possible (no heavy dependencies)
- Every script has
--help, docstring header with usage examples, and argparse CLI - Skills link to each other via
## Related Skillssections (upstream/downstream/see-also) - Prompt-only skills are fully self-contained in SKILL.md
Requirements
- Claude Code
- Python 3
- Optional: PyMuPDF, numpy, scipy (see installation)
File tree
lingzhi227/agent-research-skillsView on GitHub
.gitignore
CHANGELOG.md
commands/
research.md
install.sh
README.md
skills/
SKILLS_DESIGN.md
SKILLS_IMPLEMENTED.md
algorithm-design/
references/
algorithm-templates.md
SKILL.md
atomic-decomposition/
references/
decomposition-prompts.md
SKILL.md
backward-traceability/
references/
traceability-patterns.md
scripts/
ref_numeric_values.py
SKILL.md
citation-management/
scripts/
harvest_citations.py
validate_citations.py
SKILL.md
code-debugging/
references/
debug-patterns.md
SKILL.md
data-analysis/
references/
review-prompts.md
scripts/
format_pvalue.py
stat_summary.py
SKILL.md
deep-research/
references/
api-reference.md
note-format.md
workflow-phases.md
scripts/
bibtex_manager.py
compile_report.py
download_papers.py
extract_pdf.py
paper_db.py
search_arxiv.py
search_semantic_scholar.py
SKILL.md
excalidraw-skill/
references/
cheatsheet.md
scripts/
clear-canvas.cjs
create-element.cjs
delete-element.cjs
export-elements.cjs
healthcheck.cjs
import-elements.cjs
update-element.cjs
SKILL.md
experiment-code/
references/
code-patterns.md
experiment-prompts.md
SKILL.md
experiment-design/
references/
stage-prompts.md
scripts/
design_experiments.py
SKILL.md
figure-generation/
references/
figure-prompts.md
scripts/
figure_template.py
SKILL.md
github-research/
references/
phase-guide.md
scripts/
analyze_repo_structure.py
clone_repo.py
compare_repos.py
compile_github_report.py
extract_dependencies.py
extract_research_refs.py
find_implementations.py
repo_db.py
repo_metadata.py
repo_readme_fetch.py
search_github_code.py
search_github.py
search_paperswithcode.py
SKILL.md
idea-generation/
references/
ideation-prompts.md
scripts/
novelty_check.py
SKILL.md
latex-formatting/
references/
venue-templates.md
scripts/
clean_latex.py
latex_checker.py
SKILL.md
literature-review/
references/
dialogue-prompts.md
review-workflow.md
SKILL.md
literature-search/
scripts/
download_arxiv_source.py
search_crossref.py
search_openalex.py
SKILL.md
math-reasoning/
references/
notation-guide.md
proof-templates.md
SKILL.md
novelty-assessment/
references/
assessment-prompts.md
SKILL.md
paper-assembly/
references/
orchestration-patterns.md
scripts/
assembly_checker.py
SKILL.md
paper-compilation/
scripts/
compile_paper.py
fix_latex_errors.py
SKILL.md
paper-revision/
references/
revision-prompts.md
SKILL.md
paper-to-code/
references/
paper-to-code-prompts.md
SKILL.md
paper-writing-section/
references/
refinement-prompts.md
section-tips.md
SKILL.md
rebuttal-writing/
references/
rebuttal-prompts.md
SKILL.md
related-work-writing/
references/
related-work-prompts.md
SKILL.md
research-planning/
references/
output-schemas.md
planning-prompts.md
SKILL.md
self-review/
references/
review-form.md
scripts/
extract_pdf_text.py
parse_pdf_sections.py
SKILL.md
slide-generation/
references/
slide-templates.md
scripts/
extract_paper_elements.py
SKILL.md
survey-generation/
references/
survey-prompts.md
SKILL.md
symbolic-equation/
references/
llmsr-patterns.md
SKILL.md
table-generation/
references/
table-templates.md
scripts/
results_to_table.py
SKILL.mdFAQ
agent-research-skills is a Claude Code plugin with 31 hand-picked skills for research work, indexed on Flowy. Install it with the command on its page. It includes algorithm-design, atomic-decomposition, backward-traceability. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
- What is agent-research-skills?
- 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.
- How do I install agent-research-skills?
- Run these in Claude Code: npx -y skills add lingzhi227/agent-research-skills --agent claude-code. Then prompt normally.
- Does agent-research-skills auto-invoke its skills?
- Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.
- Is agent-research-skills free?
- Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.