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ascii-mini-charts skill

/skills/ascii-mini-charts

This skill generates compact ASCII charts from numeric series, delivering clear sparklines, bars, or lines with optional annotations and ASCII-only output.

npx playbooks add skill partme-ai/full-stack-skills --skill ascii-mini-charts

Review the files below or copy the command above to add this skill to your agents.

Files (4)
SKILL.md
1.7 KB
---
name: ascii-mini-charts
description: Generate ASCII mini charts (sparkline/bar/simple line) for plain-text trend inspection, with minimal + annotated variants and normalization notes.
license: Complete terms in LICENSE.txt
dependencies:
  - python>=3.8
---


## When to use this skill
**CRITICAL TRIGGER RULE**
- Use this skill ONLY when the user explicitly mentions the exact skill name: `ascii-mini-charts`.

**Trigger phrases include:**
- "ascii-mini-charts"
- "use ascii-mini-charts"
- "用 ascii-mini-charts 生成 sparkline / 火花线"
- "使用 ascii-mini-charts 标注 min/max/current"

## Boundary
- No statistical inference. Visualization only.
- Default output is ASCII-only. Unicode blocks are optional and MUST include an ASCII-only fallback.
- Default output width should stay <= 60 columns. For longer series, provide a compression strategy (sampling/bucketing).

## How to use this skill
### Inputs
- series (required numeric list)
- type (sparkline | bar | line, default sparkline)
- width (default min(len(series), 30))
- height (default 10 for bar/line)
- normalize (linear | log, default linear)
- showLabels (default true)

### Outputs (required)
- chartMinimal
- chartAnnotated (with min/max/current)
- scaleNotes (normalization + outlier strategy)

## Script
- `scripts/mini_charts.py`: generate ASCII mini charts from JSON stdin

## Examples
- `examples/sparkline.md`

## Quality checklist
1. Trend is clear; labels are short and non-spammy
2. ASCII-only output copy/pastes cleanly
3. Provide a compression strategy for long series

## Keywords
**English:** ascii-mini-charts, sparkline, ascii chart, bar chart, line chart, trend, normalize
**中文:** ascii-mini-charts, 火花线, ASCII 图表, 柱状图, 折线图, 趋势, 归一化

Overview

This skill generates compact ASCII mini charts (sparkline, bar, or simple line) for quick plain-text trend inspection. It produces both a minimal ASCII-only chart and an annotated variant highlighting min, max, and current values. It includes normalization notes and a compression strategy for long series.

How this skill works

It accepts a numeric series and rendering options (type, width, height, normalize, showLabels) and produces two outputs: chartMinimal and chartAnnotated. The default output is pure ASCII; optional Unicode blocks are available but always include an ASCII fallback. For long inputs the skill compresses data via sampling or bucketing and documents the approach in scaleNotes.

When to use it

  • When you explicitly request the exact skill name: ascii-mini-charts
  • When you need quick inline trend visuals in plain-text environments (logs, terminals, emails)
  • When you want annotated pointers for min, max, and current values
  • When full plotting libraries are unavailable or copy-paste friendly ASCII is required
  • When you need a compact overview with optional normalization notes

Best practices

  • Keep width <= 60 columns for readability; default uses min(len(series), 30)
  • Choose sparkline for dense series, bar for magnitude comparison, line for shape detail
  • Use linear normalization by default; use log only for heavy skew or exponential growth
  • Enable showLabels for short non-spammy labels; keep them concise
  • For very long series, prefer bucketing with mean/median aggregation to preserve trend shape

Example use cases

  • Embed a sparkline in a CLI status report to show recent metric trend
  • Attach an annotated ASCII chart to an automated alert showing current/min/max
  • Include a compact bar chart in plain-text email summaries for daily totals
  • Inspect time-series snippets in code review or chat without graphical tools
  • Quickly compare small series inline where images are not supported

FAQ

What outputs does the skill always return?

chartMinimal, chartAnnotated (with min/max/current), and scaleNotes documenting normalization and compression strategy.

Does it perform statistical inference?

No. The skill only visualizes provided numbers; it does not infer or predict values.