data-storytelling
Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
76
47%
Does it follow best practices?
Impact
95%
1.06xAverage score across 6 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/business-analytics/skills/data-storytelling/SKILL.mdQuality
Discovery
67%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description has good structural completeness with a clear 'what' and 'when' clause, which is its strongest aspect. However, it leans toward abstract language ('compelling narratives', 'persuasive structure') rather than listing concrete, specific actions. The trigger terms cover some key scenarios but miss common user phrasings, and the scope is broad enough to potentially conflict with adjacent skills like data visualization or presentation creation.
Suggestions
Replace abstract phrases like 'compelling narratives' and 'persuasive structure' with concrete actions such as 'annotate charts with insights', 'write executive summaries', 'structure findings into slide narratives'.
Expand trigger terms to include common user phrases like 'dashboard', 'KPIs', 'metrics deck', 'board presentation', 'data insights', or 'quarterly review'.
Add distinguishing details that separate this from general visualization or presentation skills, e.g., 'Focuses on narrative framing and audience-appropriate context rather than raw chart generation'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (data storytelling) and some actions ('visualization, context, and persuasive structure'), but these are more abstract concepts than concrete actions. It doesn't list specific tasks like 'create charts', 'write narrative summaries', or 'build slide decks'. | 2 / 3 |
Completeness | Clearly answers both 'what' (transform data into compelling narratives using visualization, context, and persuasive structure) and 'when' (presenting analytics to stakeholders, creating data reports, building executive presentations) with an explicit 'Use when' clause. | 3 / 3 |
Trigger Term Quality | Includes some useful trigger terms like 'analytics', 'stakeholders', 'data reports', 'executive presentations', but misses common variations users might say such as 'dashboard', 'charts', 'KPIs', 'metrics', 'insights', 'data summary', or 'board deck'. | 2 / 3 |
Distinctiveness Conflict Risk | Could overlap with general data visualization skills, report generation skills, or presentation creation skills. The focus on 'narrative' and 'storytelling' provides some distinction, but 'data reports' and 'executive presentations' are broad enough to conflict with other skills. | 2 / 3 |
Total | 9 / 12 Passed |
Implementation
27%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like a comprehensive blog post or training manual on data storytelling than a lean, actionable skill file for Claude. It contains substantial amounts of general knowledge (headline writing tips, transition phrases, do's/don'ts) that Claude already possesses, while lacking executable workflows, validation steps, and proper content organization across files. The example frameworks are its strongest element but are buried in excessive surrounding content.
Suggestions
Cut the content by 60-70%: remove 'Writing Techniques' section (transition phrases, headline formulas), 'Best Practices' do's/don'ts, and 'Core Concepts' (story structure, narrative arc, three pillars) — Claude already knows these.
Split remaining content: keep a brief overview with one framework example in SKILL.md, then reference separate files like FRAMEWORKS.md, TEMPLATES.md, and VISUALIZATION.md for the detailed templates.
Add a concrete workflow with validation: e.g., '1. Identify key insight → 2. Draft narrative using framework → 3. Verify all numbers are sourced → 4. Check that every chart has a clear takeaway → 5. Confirm call-to-action is specific and measurable'.
Make the matplotlib example more complete and add more executable code for common data storytelling tasks (e.g., generating comparison tables, computing metrics, formatting output).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~300+ lines. Much of this is general storytelling advice, presentation templates, and writing tips that Claude already knows. Transition phrases, headline formulas, and 'do's and don'ts' of data storytelling are common knowledge for an LLM. The content reads like a blog post or textbook chapter rather than a lean skill file. | 1 / 3 |
Actionability | The frameworks provide structured markdown templates with concrete examples (churn analysis, Q4 review, market comparison), and there's one executable matplotlib code snippet. However, most content is descriptive markdown templates and ASCII art rather than executable code or specific tool commands. The guidance is more illustrative than directly actionable for Claude to execute. | 2 / 3 |
Workflow Clarity | The story frameworks provide clear sequential structures (Hook → Context → Problem → Insight → Solution → Impact → CTA), and the slide flow template gives a logical sequence. However, there are no validation checkpoints, no feedback loops for iterating on the narrative, and no guidance on how to verify the story is effective or the data is accurate before presenting. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of text with everything inline. There are no references to external files for detailed templates, visualization guides, or framework deep-dives. The content would benefit enormously from splitting frameworks, visualization techniques, and writing tips into separate referenced files, keeping only a concise overview in the main skill. | 1 / 3 |
Total | 6 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- wshobson/agents
- Commit
70444e5
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.