Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
83
75%
Does it follow best practices?
Impact
100%
2.77xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/denario/SKILL.mdAutomated research pipeline
Correct import statement
0%
100%
Journal import
0%
100%
project_dir parameter
0%
100%
Detailed data description
0%
100%
set_data_description called first
0%
100%
get_idea() called
0%
100%
get_method() called
0%
100%
get_results() called
0%
100%
Journal.APS used
0%
100%
Correct workflow order
0%
100%
Hybrid workflow with custom inputs
Correct import
0%
100%
Journal import
0%
100%
project_dir parameter
0%
100%
set_data_description called
0%
100%
set_idea() used
0%
100%
get_idea() NOT called
100%
100%
set_method() used
0%
100%
get_method() NOT called
100%
100%
get_results() called
0%
100%
Journal.APS in get_paper
0%
100%
Installation and API key configuration
uv install command
100%
100%
uv init step
100%
100%
Python 3.12 requirement
100%
100%
OPENAI_API_KEY env var
100%
100%
Google credentials env var
100%
100%
.env file approach
100%
100%
load_dotenv() usage
0%
100%
.gitignore for secrets
100%
100%
No hardcoded keys
100%
100%
LaTeX or Docker for paper generation
100%
100%
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Table of Contents
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.