Denario Skill
Skill by jmanhype
Why use this skill?
Automate your scientific research workflow with the Denario Skill for OpenClaw. Generate ideas, methods, and papers effortlessly using the power of the Denario framework.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/jmanhype/denario-skillWhat This Skill Does
The Denario Skill is a powerful OpenClaw agent component designed to automate the lifecycle of scientific research. Developed by jmanhype, it leverages the Denario framework to provide a structured, programmatic approach to discovery and documentation. By utilizing a wrapper script (scripts/wrapper.sh), the skill abstracts away complex environment configurations, including the automatic management of a virtual Python environment at ~/.denario_skill_env and seamless Z.ai integration. It acts as an autonomous assistant capable of navigating the complex stages of academic inquiry, from the initial ideation phase through methodology formulation, analytical results, and final manuscript compilation.
Installation
To integrate this skill into your OpenClaw environment, execute the following command in your terminal:
clawhub install openclaw/skills/skills/jmanhype/denario-skill
Ensure that your OpenClaw instance is properly configured with your API credentials. You must set your Z.ai or Zhipu API key to enable the agent to interface with the necessary models for text generation and research analysis:
clawdbot config set env.OPENAI_API_KEY <your-key>
Use Cases
- Academic Research Automation: Ideal for students and researchers who need to generate initial hypotheses or refine experimental designs using a structured Maker/Hater loop.
- Data Analysis Pipelines: Automatically generate methodological frameworks based on specific research objectives and map them to actionable experimental steps.
- Paper Drafting: Streamline the transition from data results to full manuscript submission by automating the generation of analysis summaries and citation management.
Example Prompts
- "Denario idea, please suggest three novel research topics regarding climate model efficiency."
- "Denario methods, apply the standard optimization methodology to the previous hypothesis."
- "Denario paper, compile all previous results and methodologies into a structured LaTeX document format."
Tips & Limitations
- Environment Stability: Always ensure the virtual environment is clean. If you encounter dependency issues, verify that
scripts/wrapper.shhas the correct execution permissions. - State Persistence: The skill relies on local directory structure. Keep the skill root directory free of clutter to ensure the generator can locate previous research outputs effectively.
- API Costs: As this skill automates research generation, it can make significant API calls. Monitor your Z.ai or OpenAI usage to avoid unexpected costs during long-form paper compilation tasks.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-jmanhype-denario-skill": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-write, file-read, external-api, code-execution