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.
This skill provides a comprehensive workflow for transforming data into visual charts. It handles chart selection, parameter extraction, and image generation.
Workflow
To visualize data, follow these steps:
1. Intelligent Chart Selection
Analyze the user's data features to determine the most appropriate chart type. Use the following guidelines (and consult references/ for detailed specs):
Time Series: Use generate_line_chart (trends) or generate_area_chart (accumulated trends). Use generate_dual_axes_chart for two different scales.
Comparisons: Use generate_bar_chart (categorical) or generate_column_chart. Use generate_histogram_chart for frequency distributions.
Part-to-Whole: Use generate_pie_chart or generate_treemap_chart (hierarchical).
Relationships & Flow: Use generate_scatter_chart (correlation), generate_sankey_chart (flow), or generate_venn_chart (overlap).
Maps: Use generate_district_map (regions), generate_pin_map (points), or generate_path_map (routes).
Hierarchies & Trees: Use generate_organization_chart or generate_mind_map.
generate_spreadsheet: Tabular data or pivot tables for structured data display and cross-tabulation.
2. Parameter Extraction
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.
3. Chart Generation
Invoke the scripts/generate.js script with a JSON payload.
The script will output the URL of the generated chart image.
Return the following to the user:
The image URL.
The complete args (specification) used for generation.
Reference Material
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.
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
Reviews DeerFlow skill packages for readiness, triggers, safety boundaries, resources, and evidence. Invoke when users ask to audit, grade, or production-check an existing skill.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke test deployment", "verify installation", "test service availability", "end-to-end test", or similar.
Use when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review comments, review PR or issue batches, compare competing PRs that target the same issue, give fix strategy, risk classification, and validation guidance. Intended for maintainers and trusted local agents, not general contributors.
Ensure async-path backend code that could block the asyncio event loop is protected by a teeth-verified runtime anchor in tests/blocking_io/. Use when changing backend Python under app/, packages/harness/deerflow/, or scripts/, when running a blocking-IO triage round over the whole repo, or when a reviewer/CI asks for blocking-IO coverage. Runs a deterministic scan (changed-lines or full-repo), routes each candidate, drafts/extends an anchor, and proves it fails when the blocking IO regresses.
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".
Use this skill when the user requests to generate, create, or make presentations (PPT/PPTX). Creates visually rich slides by generating images for each slide and composing them into a PowerPoint file.
Create a delightful, unexpected "wow" experience for the user by dynamically discovering and creatively combining other enabled skills. Triggers when the user says "surprise me" or any request expressing a desire for an unexpected creative showcase. Also triggers when the user is bored, wants inspiration, or asks for "something interesting".
