data-story-outliner
Data Story Outliner - Auto-activating skill for Data Analytics. Triggers on: data story outliner, data story outliner Part of the Data Analytics skill category.
33
0%
Does it follow best practices?
Impact
97%
1.02xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/12-data-analytics/data-story-outliner/SKILL.mdQuality
Discovery
0%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is essentially a placeholder with no substantive content. It repeats the skill name as its only trigger term, provides no concrete actions or capabilities, and lacks any explicit guidance on when Claude should select it. It would be nearly impossible for Claude to correctly choose this skill from a pool of similar analytics skills.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Creates structured outlines for data-driven narratives, organizes key insights into storylines, and suggests visualization sequences for presenting analytical findings.'
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks to outline a data story, structure an analytics narrative, create a presentation flow from data insights, or organize findings into a compelling storyline.'
Include varied natural keywords users might say, such as 'data narrative', 'story from data', 'analytics presentation outline', 'insight storyline', 'data-driven report structure'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description provides no concrete actions. It only names itself ('Data Story Outliner') and its category ('Data Analytics') without describing what it actually does—no mention of outlining, structuring narratives, generating insights, or any specific capabilities. | 1 / 3 |
Completeness | Neither 'what does this do' nor 'when should Claude use it' is meaningfully answered. There is no 'Use when...' clause, and the description fails to explain the skill's purpose beyond its name and category. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated twice ('data story outliner, data story outliner'). There are no natural user keywords like 'narrative', 'data storytelling', 'insight summary', 'presentation outline', or 'analytics report'. | 1 / 3 |
Distinctiveness Conflict Risk | The description is extremely generic—'Data Analytics skill category' could overlap with dozens of analytics-related skills. Nothing distinguishes this from other data analysis, visualization, or reporting skills. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is an empty shell with no substantive content. It contains only generic boilerplate describing what the skill could do without providing any actual instructions, examples, frameworks, or actionable guidance for creating data story outlines. It fails on every dimension because it teaches Claude nothing it doesn't already know.
Suggestions
Add a concrete data story outline framework (e.g., a template with sections like Context → Key Findings → Supporting Visualizations → Recommendations → Call to Action) with a worked example.
Include specific, executable code examples for common data story tasks such as generating summary statistics, creating narrative-ready visualizations, or structuring SQL queries that support storytelling.
Define a clear multi-step workflow for building a data story (e.g., 1. Identify audience, 2. Extract key metrics, 3. Build narrative arc, 4. Select visualizations, 5. Validate coherence) with validation checkpoints.
Remove all generic boilerplate (trigger phrases, activation mechanics, capability claims) and replace with domain-specific knowledge that Claude doesn't already possess.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic filler that tells Claude nothing useful. Phrases like 'Provides step-by-step guidance' and 'Follows industry best practices' are vague platitudes. It explains trigger phrases and activation mechanics that Claude already knows, and the entire body contains zero domain-specific knowledge about data story outlining. | 1 / 3 |
Actionability | There is no concrete guidance whatsoever—no code, no commands, no specific steps, no examples of data story outlines, no frameworks, no templates. The skill describes what it could do rather than instructing Claude how to do anything. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps, no sequence, no validation checkpoints. The skill merely claims it 'provides step-by-step guidance' without actually containing any steps. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of generic text with no structure pointing to deeper resources, no referenced files, and no meaningful organization. There are no bundle files to support it either. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
3a2d27d
- Reviewed
Table of Contents
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