Content
57%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 content is rich in concrete, adaptable templates and examples (its main strength), but it reads as a 450-line monolithic reference catalog: generic writing advice and full worked reports belong in separate reference files, there is no sequenced workflow for actually producing a data story, and the matplotlib example is not directly executable. Restructuring around a lean process plus offloaded examples would lift most dimensions.
Suggestions
Move the three full worked report examples (Problem-Solution, Trend, Comparison stories) and the presentation templates into references/ files (e.g. references/frameworks.md, references/templates.md), keeping only a compact summary of each framework's structure in SKILL.md — this improves both progressive_disclosure and conciseness.
Add a short sequenced workflow section (e.g. 1. identify audience and decision, 2. pick a matching framework, 3. extract the hook and headline from the data, 4. choose visualization technique, 5. assemble and verify the narrative flows to the call-to-action) so the skill instructs how to produce a story, not just what good stories look like.
Trim sections Claude can generate unaided — Transition Phrases, Handling Uncertainty phrase lists, and the boilerplate matplotlib annotation snippet — to the few non-obvious specifics (e.g. the headline formula, the progressive-reveal technique), improving conciseness and token efficiency.
Make the matplotlib example executable by defining or loading sample data (or explicitly noting placeholder variables must be bound to the user's dataset).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient — no tutorial-style concept explanations — but sections like "Transition Phrases" ("The data reveals...", "Based on this analysis..."), "Headlines That Work", and the matplotlib annotation boilerplate restate writing knowledge Claude already has, and three full worked report templates inflate the file to ~450 lines. Fits anchor 3 ('mostly efficient but includes some unnecessary explanation or could be tightened'); not 2 because there is no padded filler explaining basic concepts, not 4 because the generic phrase lists and boilerplate code could clearly be trimmed. | 3 / 5 |
Actionability | Three complete, concrete worked frameworks with real numbers ($2.4M churn, Q3/Q4 metric tables), a headline formula, slide templates, and specific visualization techniques provide mostly executable guidance. Fits anchor 4 rather than 5 because the matplotlib example uses undefined variables (dates, revenue, launch_date, target) and is not copy-paste runnable; not 3 because the templates are fully concrete rather than pseudocode. | 4 / 5 |
Workflow Clarity | The body is organized as a reference catalog (concepts → frameworks → techniques → templates) rather than an operating procedure; the Narrative Arc sequences the story artifact itself but there is no step-by-step process for producing a story (pick framework → extract hook → draft headline → build visuals → assemble) and no validation checkpoints. Fits anchor 3 ('sequence present but checkpoints missing or implicit'); not 4 because a usage-level workflow with checkpoints is absent, not 2 because the arc and framework structures do give a coherent sequence. | 3 / 5 |
Progressive Disclosure | At 453 lines everything is inlined in SKILL.md — three full example reports, all techniques, and all templates — with no references/ split despite the size; header-based section structure is good but content that clearly belongs in separate reference files (the worked example reports) is inline. Fits anchor 3 ('some structure... content that should be separate is inline'); not 2 because organization and navigation via headers are real, not 4 because nothing is offloaded to one-level-deep reference files. | 3 / 5 |
Total | 13 / 20 Passed |