Content
56%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill has a solid executable core — a real script, a thorough parameter table, quick-check validation, and genuine bundle files — but the body is bloated with auto-generated template boilerplate (repeated description, empty sections, circular cross-references, generic governance sections) that wastes context. References exist but are vaguely signaled at directory level, and content that belongs in them is inlined.
Suggestions
Cut the verbatim description repeats in 'When to Use' and 'Key Features', remove the empty 'Dependencies' section and the circular 'See ## Usage/## Workflow above' cross-references, and delete generic template sections (Output Requirements, Response Template, Risk Assessment, Lifecycle Status) or fold them into a short Error Handling section.
Replace directory-level reference pointers with specific file links, e.g. '**Best practices**: See [best_practices.md](references/best_practices.md)', '**Example DEG data**: [example_deg_data.csv](references/example_deg_data.csv)', and move the inlined Input Requirements / interpretation details into best_practices.md.
Fix concrete execution gaps: add the missing requirements.txt (or list dependencies directly), correct the nonsensical audit input sample to a real DEG CSV invocation (e.g. --input references/example_deg_data.csv), and fence the usage snippet as ```bash.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~250-line body is noticeably padded: the frontmatter description is repeated verbatim in both "When to Use" ("Generate R/Python code for volcano plots from DEG (Differentially Expressed Genes) analysis results. Triggered when user needs visualization...") and again in "Key Features" ("Scope-focused workflow aligned to: Generate R/Python code for volcano plots..."); the "Dependencies" section is empty; "Example Usage" and "Implementation Details" contain circular self-references ("See `## Usage` above", "See `## Workflow` above"); and generic template sections ("Output Requirements", "Response Template", "Risk Assessment", "Lifecycle Status") add tokens without volcano-plot-specific value. This matches anchor 2 (several unnecessary/padded sections) rather than anchor 3's 'mostly efficient with some trimming possible'. | 2 / 5 |
Actionability | Guidance is mostly executable and concrete: a real packaged script ("python scripts/main.py --input deg_results.csv --output volcano_plot.png"), a complete parameter table with column names, defaults, and hex colors ("--log2fc-thresh | Log2 FC threshold for significance | 1.0"), runnable audit commands, and verified example data in references/. Minor gaps keep it below anchor 5: "pip install -r requirements.txt" references a nonexistent requirements.txt, the audit command's input sample ("Audit validation sample with explicit symptoms, history, assessment...") is leftover template text unrelated to DEG CSV input, and the bash usage snippet is fenced as ```python. | 4 / 5 |
Workflow Clarity | A clear sequence exists with most checkpoints present: the Workflow's 5 steps include up-front validation ("Validate that the request matches the documented scope and stop early"), the "Quick Check" section provides a py_compile verification gate before deeper execution, the Example run plan gives 4 concrete steps, and "Error Handling" defines a fallback path with failure reporting. This matches anchor 4; it falls short of anchor 5 because some Workflow steps are generic template language ("Use the packaged script path or the documented reasoning path") rather than explicit volcano-plot-specific checkpoints with fix-and-retry loops. | 4 / 5 |
Progressive Disclosure | The bundle is real and structurally sound (scripts/main.py, references/best_practices.md, references/example_deg_data.csv, references/markers.txt, assets/example_volcano.R all exist), but the body signals it poorly: references are pointed at directory level ("Reference guidance: `references/` contains supporting rules, prompts, or checklists"), the References section links a bare directory ("[Example datasets and templates](references/)") plus two unlinked bullet descriptions ("Best practices for volcano plot visualization", "Color schemes for accessibility"), and much content that belongs in the existing reference files is inlined instead. This matches anchor 3 (references present but not clearly signaled, content that should be separate is inline) rather than anchor 4's clearly-signaled one-level-deep references. | 3 / 5 |
Total | 13 / 20 Passed |