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 is an extremely weak description that essentially only provides the skill's name and category without any substantive information about what it does or when to use it. The trigger terms are the skill name duplicated, offering no useful matching keywords. This description would be nearly useless for Claude to differentiate this skill from others in a multi-skill environment.
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 wants to structure a data story, create a narrative from analytics results, outline a data presentation, or organize insights into a compelling storyline.'
Diversify trigger terms to include natural variations users would say, such as 'data narrative', 'story from data', 'analytics presentation outline', 'insight storyline', 'data-driven story structure'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description provides no concrete actions. 'Data Story Outliner' is a name, not a description of capabilities. There is no mention of what specific actions the skill performs (e.g., creating outlines, structuring narratives, generating visualizations). | 1 / 3 |
Completeness | The description fails to answer both 'what does this do' and 'when should Claude use it'. There is no explanation of capabilities and no explicit 'Use when...' clause. The 'Triggers on' line is just the skill name repeated, not meaningful trigger guidance. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated twice ('data story outliner, data story outliner'). These are not natural keywords a user would say. Missing terms like 'narrative', 'data storytelling', 'outline', 'presentation structure', 'insights summary', etc. | 1 / 3 |
Distinctiveness Conflict Risk | Being categorized under 'Data Analytics' is extremely broad and would overlap with many other data-related skills. Nothing distinguishes this from other data analytics skills since no specific niche or unique capability is described. | 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 actual content. It consists entirely of boilerplate meta-descriptions that repeat 'data story outliner' without ever defining what a data story outline is, how to create one, or providing any concrete guidance, templates, or examples. It provides zero value to Claude beyond what the skill's title already conveys.
Suggestions
Replace the meta-description sections with an actual data story outline template or framework (e.g., situation → complication → resolution structure with data-backed sections).
Add concrete, executable examples showing how to structure a data story outline from a sample dataset, including specific SQL queries or visualization recommendations.
Include a step-by-step workflow for creating a data story outline: e.g., 1) Identify key metric, 2) Pull supporting data, 3) Structure narrative arc, 4) Select visualizations, 5) Validate findings.
Remove the 'When to Use', 'Example Triggers', and 'Capabilities' sections entirely—these are routing metadata that waste tokens and provide no instructional value.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely filler and meta-description. It explains what the skill does in abstract terms without providing any actual actionable content. Every section restates the same vague idea ('data story outliner') without adding substance. | 1 / 3 |
Actionability | There is zero concrete guidance—no code, no commands, no examples of data story outlines, no templates, no specific steps. The skill describes rather than instructs, offering only vague claims like 'provides step-by-step guidance' without actually providing any. | 1 / 3 |
Workflow Clarity | No workflow is defined at all. There are no steps, no sequence, no validation checkpoints. The 'Capabilities' section promises step-by-step guidance but delivers none. | 1 / 3 |
Progressive Disclosure | The content is a flat, repetitive document with no meaningful structure. There are no references to detailed materials, no linked resources, and the sections are redundant rather than progressively disclosing useful information. | 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
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- Reviewed
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