/**
 * Chart renderer: PNG output for MCP image content blocks.
 *
 * Used by tools that produce time series or bar-shaped data to emit a real
 * chart (alongside the JSON envelope) so hosts that render image content
 * — Claude Desktop, ChatGPT Desktop — surface a visual the user can scan
 * in one glance. Hosts that don't render images ignore the block.
 *
 * Tech choice: chart.js + chartjs-node-canvas. Chart.js is the most-trained-
 * on charting library in LLM corpora; its output looks conventional to
 * agents and humans. The node-canvas dependency requires Cairo on Linux
 * (one-time install pain); on Mac it Just Works. When init fails, rendering
 * falls back to ASCII sparklines so a missing Cairo doesn't block tool
 * execution.
 *
 * All renderers return base64-encoded PNG so callers can drop the result
 * straight into a `{ type: 'image', data, mimeType: 'image/png' }` MCP
 * content block.
 */
export interface TimeseriesPoint {
    t: string | number;
    value: number;
}
export interface RenderResult {
    /** Base64-encoded PNG ready for an MCP image content block. */
    base64: string;
    /** `image/png` literal so callers don't memorize it. */
    mimeType: 'image/png';
}
/**
 * Render a single-series timeseries chart. Used by `pattern_trend` and
 * the trend sparkline in `top_patterns` cards.
 */
export declare function renderTimeseries(points: TimeseriesPoint[], opts?: {
    title?: string;
    yLabel?: string;
    lineColor?: string;
}): Promise<RenderResult | null>;
export interface BarRow {
    label: string;
    value: number;
}
/**
 * Render a horizontal bar chart. Used by `top_patterns` (top N patterns by
 * cost) and `services` (services by share).
 */
export declare function renderHorizontalBar(rows: BarRow[], opts?: {
    title?: string;
    xLabel?: string;
    barColor?: string;
}): Promise<RenderResult | null>;