data-analytics-reporter
Expert data analyst transforming raw data into actionable business insights. Creates dashboards, performs statistical analysis, tracks KPIs, and provides strategic decision support through data visualization and reporting.
28
12%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./specialized-data-analytics/skills/SKILL.mdQuality
Discovery
25%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 lists several capabilities but relies heavily on buzzwords like 'actionable business insights' and 'strategic decision support' without grounding them in concrete actions. It completely lacks a 'Use when...' clause, making it difficult for Claude to know when to select this skill. The broad scope covering multiple data-related domains creates high conflict risk with other skills.
Suggestions
Add an explicit 'Use when...' clause with trigger terms like 'Use when the user asks for data analysis, dashboard creation, KPI tracking, statistical summaries, or data-driven business recommendations.'
Replace vague phrases like 'actionable business insights' and 'strategic decision support' with concrete actions such as 'calculates trends, generates summary statistics, builds bar/line/pie charts'.
Narrow the scope or add file-type specificity (e.g., 'CSV, Excel, SQL query results') to reduce overlap with other data-related skills and improve distinctiveness.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (data analysis) and lists several actions (creates dashboards, performs statistical analysis, tracks KPIs, data visualization and reporting), but some terms like 'actionable business insights' and 'strategic decision support' are vague buzzwords rather than concrete actions. | 2 / 3 |
Completeness | Describes what the skill does but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and since the 'when' is entirely absent, this scores at the lower end. | 1 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'dashboards', 'statistical analysis', 'KPIs', 'data visualization', and 'reporting' that users might naturally say. However, it misses common variations like 'charts', 'graphs', 'metrics', 'CSV', 'Excel', 'spreadsheet', or 'data analysis'. | 2 / 3 |
Distinctiveness Conflict Risk | Very broad scope covering dashboards, statistical analysis, KPIs, visualization, and reporting could easily overlap with dedicated visualization skills, reporting skills, statistics skills, or general data processing skills. The description lacks a clear niche. | 1 / 3 |
Total | 6 / 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 content is essentially a role description or job posting rather than an actionable skill file. It lists capabilities, tools, and success metrics but provides zero concrete guidance on how to actually perform any data analytics task. There are no code examples, no workflow steps, no templates, and no references to detailed resources.
Suggestions
Replace the capability lists with concrete, executable examples: show actual Python/SQL code for common analytics tasks like loading data, computing KPIs, and generating visualizations.
Add a clear workflow for the most common use case (e.g., 'Analyzing a dataset and producing a report') with numbered steps and validation checkpoints.
Remove the 'Success Metrics' and 'Decision Framework' sections entirely—these describe organizational goals, not instructions Claude can follow.
Add example templates for outputs (e.g., a dashboard layout, a report structure, a SQL query pattern) so Claude knows exactly what to produce.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with no actionable content. Lists capabilities, skills, metrics, and decision frameworks that Claude already knows or that provide no executable guidance. Every section is padded with generic descriptions rather than specific instructions. | 1 / 3 |
Actionability | Contains zero concrete code, commands, examples, or executable guidance. The entire content describes what the agent does in abstract terms (e.g., 'Statistical analysis, trend identification, predictive modeling') without ever showing how to do anything. No code snippets, no specific workflows, no templates. | 1 / 3 |
Workflow Clarity | No workflows, steps, or sequences are defined. The skill describes capabilities and metrics but never outlines how to actually perform any analysis, create a report, or build a dashboard. There are no validation checkpoints or process flows. | 1 / 3 |
Progressive Disclosure | Monolithic wall of bullet points with no references to external files, no navigation structure, and no layered content organization. All sections are at the same level of abstraction (high-level descriptions) with no path to deeper detail. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- OpenRoster-ai/awesome-openroster
- Commit
09aef5d
- Reviewed
Table of Contents
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