Design charts, maps, and dashboards around the question readers need answered. Choose suitable chart forms, communicate findings through titles and labels, and check custom colors with a local palette validator to support clear visual distinctions.
Design guidance for charts, graphs, dashboards, maps, and data visualizations, including a local palette validator.
Review the instructions the agent will receive before you install.
Use this skill before producing a chart, dashboard, map, or data visualization.
references/choosing-a-form.md when the form is not obvious.references/palette.md, or validate any custom palette with
the script below.references/anti-patterns.md before finalizing the design.Resolve paths relative to the skill base directory shown above this skill body.
Do not assume $QWEN_SKILL_ROOT is set for normal shell commands.
Run:
node <skill-base-directory>/scripts/validate_palette.js '#1d4ed8,#b45309,#166534' --mode light
Treat FAIL as a required palette change. Treat WARN as acceptable only when
the chart also uses labels, shape, texture, ordering, or another secondary
encoding.
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Write clear briefs for subagents and conversation forks, agents that inherit conversation history. Specify purpose, known findings, scope, and expected output while respecting each agent's existing role and separating research requests from implementation.
Compare a feature implemented in Qwen Code with Codex or Claude Code under the same scenario. Capture communication and terminal records, inspect tool definitions and outputs, and guide fixes toward matching observable behavior.
Reproduce a Codex or Claude Code feature in Qwen Code or another command-line agent. Capture requests, terminal output, and state changes, then use that evidence to implement focused behavior and add a verification path.
Review local uncommitted changes, verify findings, and repeat focused repairs until the review converges or a blocker remains. Also supports Qwen Code issue fixes and review responses within workflows run through GitHub Actions.
Apply the same operation across multiple files using parallel worker agents. The skill finds matching files, divides the work, and reports successes, failures, and skipped files, with a preview option before edits.
Prepare shared instructions for translating, rewriting, or extracting information from many independent files, then submit a plan through the DashScope Batch API. Processing runs asynchronously at half the realtime list price and delivers new files later.