Visualization logo

Visualization

Community
FrankChen021
visualization

Rules for charts and visualization. Use when the user asks for charts, graphs, plots, or visual representations (line, bar, pie, timeseries).

Overview

PublisherFrankChen021
Repositorydatastoria
Skill namevisualization
Stars
327
Forks
18
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by FrankChen021 on GitHub. Read the source before you install it.

Installation

Install the Visualization AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/FrankChen021/datastoria/tree/master/resources/skills/visualization
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/FrankChen021/datastoria.git /tmp/datastoria
mkdir -p .claude/skills
cp -r /tmp/datastoria/resources/skills/visualization .claude/skills/visualization
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Visualization in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Visualization on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Visualization is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

WORKFLOW (MANDATORY ORDER)

a) Generate or obtain SQL:

  • CHECK CONTEXT FIRST: If valid SQL exists in the context (explicitly provided by the user or from a previous message), USE IT DIRECTLY and skip to step (b).
  • IF NO SQL FOUND: You must generate it.
    • Dependency: Valid SQL generation REQUIRES the sql-expert skill.
    • Action: Check if sql-expert skill is loaded.
      • If NOT loaded: Call the skill tool with ['sql-expert'] IMMEDIATELY. Do not proceed to generate SQL until the skill is loaded.
      • If ALREADY loaded: Generate the SQL strictly following the rules in the sql-expert skill (including Schema Discovery, Schema Fidelity, ProfileEvents handling, and Performance Optimization).
  • For system.query_log visualization requests: Do NOT call search_query_log. Load the clickhouse-system-queries skill, then load references/system-query-log.md via skill_resource, generate the SQL, and validate it.

b) VALIDATION (MANDATORY):

  • ALWAYS call validate_sql with the SQL before including the chart spec in your response.
  • RETRY LOGIC: If validation fails, retry up to 3 times by fixing the SQL (referring to sql-expert skill rules) and validating again.
  • Only proceed to step (c) if validation returns success: true.

c) After validation passes:

  • Include the full chart spec in your response using a markdown code block with language chart-spec. The content must be valid JSON matching the OUTPUT FORMAT below, and must include datasource: { "sql": "<the validated SQL>" }. Derive type, titleOption, legendOption, etc. from the CHART TYPE RULES and OUTPUT FORMAT above. Do not call any tool for this—put the complete spec in your reply.

d) Execution:

  • PROHIBITED: Do NOT call execute_sql. The chart component in the client will automatically execute the query found in the chart-spec. Calling it here wastes tokens and causes duplicate execution.

CHART TYPE RULES

STEP 1: CHECK USER'S EXPLICIT CHART REQUEST (HIGHEST PRIORITY)

If user question contains ANY of these keywords, use the corresponding chart type:

  • "line chart" → type: "line" (MANDATORY)
  • "bar chart" → type: "bar" (MANDATORY)
  • "pie chart" → type: "pie" (MANDATORY)
  • "timeseries" or "time series" → type: "line" (MANDATORY)
  • "trend" → type: "line" (MANDATORY)

STEP 2: ANALYZE SQL (Only if no explicit chart request in Step 1)

  • "line" - Time-based data with trends (DateTime/Date + GROUP BY time dimension; "over time", "by day/month/hour").
  • "bar" - Categorical comparisons (GROUP BY categories; "compare", "by category").
  • "pie" - Categorical distribution, proportions (single categorical dimension; "distribution", "breakdown", "proportion"; 2 columns: category + numeric value; best for 3-15 categories).
  • "table" - Raw data listing (LAST RESORT): user asks for "table" or "list" with NO chart keywords; no numeric aggregations.

CRITICAL RULES

  • When legendOption.placement is "bottom" or "right", you MUST include a "values" array: base ["min", "max"]; add "sum"/"count" if SQL uses SUM/COUNT; add "avg" if SQL uses AVG.
  • Line/Bar: Use "bottom" for GROUP BY with non-time dimensions, "none" for single metric.
  • Pie: legendOption.placement "right"|"bottom"|"inside" (no "none"); omit legendOption.values; use labelOption (show, format) and valueFormat as needed.

OUTPUT FORMAT (include in your response as a chart-spec code block)

Put the full chart spec in a markdown code block with language chart-spec. The JSON must include datasource.sql (the validated SQL). The client parses this block to render the chart.

Line/Bar Chart example:

chart
{
  "type": "line",
  "titleOption": { "title": "Descriptive chart title", "align": "center" },
  "width": 6,
  "legendOption": { "placement": "bottom", "values": ["min", "max", "sum"] },
  "datasource": { "sql": "SELECT ..." }
}

Pie Chart example:

chart
{
  "type": "pie",
  "titleOption": { "title": "Distribution by Category", "align": "center" },
  "width": 6,
  "legendOption": { "placement": "right" },
  "labelOption": { "show": true, "format": "name-percent" },
  "valueFormat": "short_number",
  "datasource": { "sql": "SELECT ..." }
}
  • ❌ NEVER include a chart spec before validate_sql has succeeded.
  • ❌ NEVER skip SQL generation if no SQL exists in context.
  • ❌ NEVER write SQL in your text response—ALWAYS use the instructions in sql-expert skill.
  • ✅ ALWAYS follow: Check for SQL → If missing, Load sql-expert Skill → Validation → Include chart spec in response.
  • ✅ If validation fails, retry up to 3 times.

Frequently asked questions

What does the Visualization AI skill do?

Rules for charts and visualization. Use when the user asks for charts, graphs, plots, or visual representations (line, bar, pie, timeseries).

Why use Visualization on TypingMind?

Because you install it once and use it with any model. Visualization is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Visualization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/FrankChen021/datastoria/tree/master/resources/skills/visualization. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Visualization?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Visualization?

As many as you like. As long as a model supports skills, you can use Visualization with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Visualization AI skill free?

It is published on GitHub by FrankChen021. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇