Datastoria visualization

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

install
source · Clone the upstream repo
git clone https://github.com/FrankChen021/datastoria
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FrankChen021/datastoria "$T" && mkdir -p ~/.claude/skills && cp -r "$T/resources/skills/visualization" ~/.claude/skills/frankchen021-datastoria-visualization && rm -rf "$T"
manifest: resources/skills/visualization/SKILL.md
source content

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:

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

Pie Chart example:

{
  "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.