Convert complex Venn diagrams with more than 4 sets to clearer Upset plots
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill upset-plot-converter65
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Dict-based multi-set upset plot
Correct import path
0%
0%
Uses convert_venn_to_upset
0%
100%
Dict input format
0%
100%
More than 4 sets
50%
100%
PNG output path
50%
100%
Title provided
50%
100%
Requirements installed
0%
0%
Output file produced
100%
100%
Does not use Venn library
100%
100%
Script self-contained
50%
50%
Without context: $1.1601 · 4m 34s · 49 turns · 55 in / 14,295 out tokens
With context: $0.3344 · 1m 12s · 20 turns · 228 in / 3,656 out tokens
List-based upset plot with subset filtering
Correct import path
0%
0%
Uses upset_from_lists
0%
100%
Parallel list arguments
0%
100%
More than 4 sets
0%
100%
min_subset_size used
0%
100%
PNG output path
0%
100%
Title provided
0%
100%
Requirements installed
0%
37%
Output file produced
100%
100%
Does not use Venn library
100%
100%
Without context: $1.4398 · 4m 37s · 47 turns · 54 in / 15,429 out tokens
With context: $0.6027 · 1m 56s · 32 turns · 68 in / 5,917 out tokens
Intersection statistics and max_intersections cap
Correct import path
0%
100%
Uses print_intersection_stats
0%
100%
Stats output file present
83%
100%
Uses convert_venn_to_upset
0%
100%
max_intersections used
0%
100%
More than 4 sets
100%
100%
PNG output path
0%
100%
Requirements installed
0%
50%
Output PNG produced
100%
100%
Does not use Venn library
100%
100%
Without context: $0.7738 · 3m 5s · 34 turns · 39 in / 9,653 out tokens
With context: $0.5614 · 2m 12s · 27 turns · 150 in / 7,215 out tokens
Table of Contents
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