| name | quickplot |
| description | Quick honest terminal distribution plots (sparkline histogram + box-and-whisker) of numeric data. Use when the user wants a fast in-terminal look at the distribution/spread of some values (e.g. coherence/alignment scores across models) — "histogram of these", "show me the distribution", "plot these numbers", "box plot of", "what do these look like". For throwaway terminal viz, NOT publication plots. |
quickplot
Turn raw numbers into a compact unicode sparkline histogram + box-and-whisker
plot, plus a full numeric summary, printed in the terminal. For
quick-and-dirty "what does this distribution look like" checks — real/paper
plots happen elsewhere.
Group name on the left, graphics (histogram over box-&-whisker) on the right,
all on a shared fixed x-axis; the full numeric summary is a column-aligned list
below. The histogram is 2 character rows tall by default (16 levels of vertical
resolution, linear — bar heights stay proportional), which makes low-count tail
bins visible without distorting anything; --rows 1 drops to a compact single
row.
200 samples each
Normal ▃ ▂█
▁ ▁▂▁▃▄▆▆█▆██████▄█▅▁▂▅ ▃ ▁▁ ▁ <- histogram (2 rows)
├──────────[==┃==]───────────┤ <- box & whisker
Exponential █
█▃▆█▅▅▄▃▄▄▃▃▁▂▁▁▂ ▁▁ ▁ ▁
├─[==┃===]─────────────────────┤
Uniform ▃ ▁ ▄▃ ▁ ▃ ▆ ▁▃ ▁▃ ▁█ ▁ ▃▁▁ ▁▃▄
▅█▇█▄██▅█▇▇▇█▄▄▇█▇▅▅██▇██▇▇██▅▅▇▅▂▇▄▅█▄███▅███
├──────────[===========┃==========]──────────┤
└──────────┴──────────┴───────────┴──────────┴ <- shared axis (once)
0.16 24.6 49 75.6 100
Normal: n=200 min 18.6 q1 41.5 med 49.9 q3 56 max 82.6 mean 49.5 sd 11.2
Exponential: n=200 min 0.16 q1 4.31 med 10.8 q3 21 max 69.9 mean 14.5 sd 13.6
Uniform: n=200 min 1.22 q1 24.6 med 50.1 q3 75 max 100 mean 50.2 sd 29.5
Box & whisker reads ├ min · [ q1 · ┃ median · ] q3 · ┤ max. Stacking
several groups lets you eyeball-compare spreads since every box sits on the
same axis.
The contract — why this is a script, not eyeballing
plot.py is the only thing allowed to turn the data into a picture or a
summary. It computes the histogram, the box plot, and the full seven-number
summary itself. You run it and paste its output verbatim.
Do NOT, separately, describe the distribution in prose ("looks roughly
normal", "Olmo is worse", "tightly clustered"), round the numbers, or report a
subset of them. The user explicitly does not want that layer — the script's
output is the answer. The plot is only a visual aid; the authoritative numbers
are the text summary line, which prints n, min, q1, median, q3, max, mean, and
std for every group. Unparseable values are counted and flagged (⚠ N unparseable), never silently dropped. If they ask a follow-up about the
numbers, answer from that printed summary.
How to run
Self-contained uv script (only dep: numpy) — nothing to install. Pass a
file or pipe via stdin:
~/.claude/skills/quickplot/plot.py data.json
echo '{"Gemma":[...],"Olmo":[...],"Qwen":[...]}' | ~/.claude/skills/quickplot/plot.py --title coherence
cat scores.csv | ~/.claude/skills/quickplot/plot.py
Typical flow: the data already exists (a list in the conversation, a column in
a CSV/parquet, an array in a script). Get it into one of the input formats
below — usually by writing a small JSON object to /tmp or piping — then run
the script and show what it prints.
Input formats (auto-detected)
| Input | Result |
|---|
JSON object {"Gemma":[..],"Olmo":[..]} | one panel per key |
JSON array [1,2,3,...] | a single panel |
| CSV/TSV with a header row of names | one panel per column |
| plain whitespace/newline numbers | a single panel |
For the common "models × metrics" case (Gemma/Olmo/Qwen each scored on
coherence + alignment), the cleanest input is a flat JSON object with one key
per group, e.g. {"Gemma coherence":[...], "Gemma alignment":[...], ...}. All
groups share the same fixed x-range so the panels are directly comparable.
Flags
--width N — plot width in characters (default 46)
--rows N — histogram height in character rows (default 2; 1 = compact)
--title TEXT — title printed once above the panels
--summary-only — print just the numeric summary lines, no plot
Out of scope
Scatter, line, or time-series plots, and anything headed for a paper or slide
deck. This is terminal distribution-at-a-glance only.