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Skill1.5k estrellas del repoactualizado 18d ago

nanoresearch-writing

The nanoresearch-writing skill transforms research planning and experimental results into a complete LaTeX paper draft. It parses ideation outputs, experimental blueprints, and results data to automatically generate structured sections including abstract, introduction, related work, methods, experiments, and conclusion. The skill produces publication-ready figures, tables, and a compiled PDF document. Use this when you have completed research ideation, experimental planning, and data collection and need to synthesize all outputs into a formatted academic paper.

Instalar en Claude Code
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git clone --depth 1 https://github.com/OpenRaiser/NanoResearch /tmp/nanoresearch-writing && cp -r /tmp/nanoresearch-writing/skills/nanoresearch-writing ~/.claude/skills/nanoresearch-writing
Después abre una sesión nueva de Claude Code; el skill carga automáticamente.

SKILL.md

# Writing Skill

## Purpose
Take all previous outputs (ideation, planning, experiment results) and produce a complete LaTeX paper draft with figures, tables, and bibliography.

## Tools Required
- `generate_latex`: Generate and assemble LaTeX source files for each paper section
- `compile_pdf`: Compile the LaTeX source into a PDF document
- `generate_figure`: Produce publication-quality figures from experiment results

## Input
- `ideation_output`: Path to `papers/ideation_output.json` from the ideation skill
- `experiment_blueprint`: Path to `papers/experiment_blueprint.json` from the planning skill
- `experiment_results`: Path to `experiments/` directory containing code and results from the experiment skill

## Process
1. Parse all upstream outputs to gather hypotheses, literature, experiment design, and results
2. Generate the paper outline following a standard structure (Abstract, Introduction, Related Work, Method, Experiments, Conclusion)
3. Draft the Abstract summarizing the problem, approach, and key findings
4. Draft the Introduction motivating the research question and stating contributions
5. Draft Related Work synthesizing the surveyed literature from the ideation stage
6. Draft the Method section describing the proposed approach in detail
7. Draft the Experiments section with dataset descriptions, baseline comparisons, and ablation results
8. Generate figures (performance plots, ablation charts, architecture diagrams) using `generate_figure`
9. Generate tables summarizing quantitative results
10. Draft the Conclusion with a summary of findings and future work directions
11. Compile the bibliography from all cited papers
12. Assemble the full LaTeX document using `generate_latex`
13. Compile to PDF using `compile_pdf` and verify the output

## Output
Produces `papers/draft/` directory containing:
- `main.tex`: Complete LaTeX source of the paper
- `references.bib`: Bibliography file with all citations
- `figures/`: Generated figures in PDF or PNG format
- `tables/`: LaTeX table source files
- `main.pdf`: Compiled PDF of the paper draft
nanoresearch-experimentSkill

Generate a Python code skeleton from an experiment blueprint

nanoresearch-ideationSkill

Search academic literature and generate research hypotheses

nanoresearch-planningSkill

Produce an experiment blueprint from a research hypothesis

autoresearchSkill

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

academic-plottingSkill

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

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brainstorming-research-ideasSkill

Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.

creative-thinking-for-researchSkill

Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.