The body is mostly efficient with executable commands and no conceptual padding, but the five capabilities are restated three times (intro paragraph, the 'When to Use' list, and the 'Script Reference' table), which could be tightened. Not 3 due to that redundancy; not 1 because there is no explanatory fluff about concepts Claude already knows.

Each workflow gives fully executable, copy-paste-ready commands with concrete flags (e.g. '--input plasmid.gb --output plasmid_map.png --linear --figsize 10x10 --dpi 300'). Not 2 because the examples are complete and runnable rather than pseudocode.

Each task is a single unambiguous command, which per the simple-skills note can score 3; the operations are non-destructive (rendering outputs) so no validation checkpoint is required. Not 2 because the single action per workflow is explicit and unambiguous.

The body is organized into clear sections (When to Use, Installation, Core Workflows, Script Reference, Input Formats, Style Guide) and references real one-level-deep bundle files (scripts/draw_plasmid.py, draw_sequence_logo.py, etc., all verified present). Not 2 because references are clearly signaled and shallow, with no nested .md chains.

Lists multiple concrete actions — 'Plasmid maps (circular/linear), sequence logos, restriction enzyme maps, GC content plots, and gene feature annotation tracks' — matching the score-3 anchor that enumerates several specific capabilities.

'What' is explicit (the five visualization types and input formats) but there is no 'Use when...' clause or equivalent trigger guidance, so per the rubric guideline completeness is capped at 2. Not 3 because the 'when' is entirely absent; not 1 because the 'what' is clearly and concretely stated.

Natural domain terms a user would say are well covered: 'DNA/RNA visualizations', 'plasmid maps', 'sequence logos', 'restriction enzyme maps', 'GC content plots', 'GenBank', 'FASTA'. Not score-2 because it goes beyond a single keyword to the full set of common variations a molecular-biology user would utter.

The niche is clearly DNA/RNA sequence visualization with GenBank/FASTA inputs, unlikely to collide with other skills; the body further disambiguates against SMILES-based molecule-visualization. Not 2 because the domain and input formats are specific enough to avoid overlap.