Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
This skill provides a comprehensive workflow for transforming data into visual charts. It handles chart selection, parameter extraction, and image generation.
To visualize data, follow these steps:
Analyze the user's data features to determine the most appropriate chart type. Use the following guidelines (and consult references/ for detailed specs):
generate_line_chart (trends) or generate_area_chart (accumulated trends). Use generate_dual_axes_chart for two different scales.generate_bar_chart (categorical) or generate_column_chart. Use generate_histogram_chart for frequency distributions.generate_pie_chart or generate_treemap_chart (hierarchical).generate_scatter_chart (correlation), generate_sankey_chart (flow), or generate_venn_chart (overlap).generate_district_map (regions), generate_pin_map (points), or generate_path_map (routes).generate_organization_chart or generate_mind_map.generate_radar_chart: Multi-dimensional comparison.generate_funnel_chart: Process stages.generate_liquid_chart: Percentage/Progress.generate_word_cloud_chart: Text frequency.generate_boxplot_chart or generate_violin_chart: Statistical distribution.generate_network_graph: Complex node-edge relationships.generate_fishbone_diagram: Cause-effect analysis.generate_flow_diagram: Process flow.generate_spreadsheet: Tabular data or pivot tables for structured data display and cross-tabulation.Once a chart type is selected, read the corresponding file in the references/ directory (e.g., references/generate_line_chart.md) to identify the required and optional fields.
Extract the data from the user's input and map it to the expected args format.
Invoke the scripts/generate.js script with a JSON payload.
Payload Format:
{
"tool": "generate_chart_type_name",
"args": {
"data": [...],
"title": "...",
"theme": "...",
"style": { ... }
}
}
Execution Command:
node ./scripts/generate.js '<payload_json>'
The script will output the URL of the generated chart image. Return the following to the user:
args (specification) used for generation.Detailed specifications for each chart type are located in the references/ directory. Consult these files to ensure the args passed to the script match the expected schema.
This SKILL.md is provided by antvis/chart-visualization-skills.
Licensed under the MIT License.
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Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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