business-analyst
Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations.
Install with Tessl CLI
npx tessl i github:sickn33/antigravity-awesome-skills --skill business-analyst47
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 87%
↑ 1.03xAgent success when using this skill
Validation for skill structure
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.
This description relies heavily on marketing buzzwords ('AI-powered', 'data-driven', 'master modern') rather than concrete capabilities. It lacks the critical 'Use when...' clause needed for skill selection, and its generic analytics terminology creates high conflict risk with other data-related skills. The description would benefit from removing fluff and adding explicit trigger conditions.
Suggestions
Add an explicit 'Use when...' clause with trigger terms like 'business metrics', 'KPI tracking', 'executive dashboard', 'quarterly analysis', or 'business performance'
Replace vague buzzwords ('AI-powered analytics', 'data-driven insights') with concrete actions like 'calculate revenue metrics', 'build executive summary reports', or 'analyze sales performance'
Narrow the scope to distinguish from general data analysis skills - specify if this is for executive reporting, financial analysis, or operational metrics
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names domain (business analysis) and some actions (KPI frameworks, predictive models, strategic recommendations), but uses buzzword-heavy language like 'AI-powered analytics' and 'data-driven insights' that lacks concrete specificity about what actions are actually performed. | 2 / 3 |
Completeness | Describes what it does (analytics, dashboards, KPIs) but completely lacks any 'Use when...' clause or explicit trigger guidance. There is no indication of when Claude should select this skill over others. | 1 / 3 |
Trigger Term Quality | Contains some relevant keywords like 'KPI', 'dashboards', 'predictive models', and 'business analysis', but missing common user variations like 'metrics', 'reporting', 'forecasting', 'business intelligence', or 'BI'. Terms like 'AI-powered' and 'data-driven' are marketing fluff rather than natural user language. | 2 / 3 |
Distinctiveness Conflict Risk | Very generic terms like 'analytics', 'dashboards', 'data-driven insights', and 'predictive models' could easily overlap with data science skills, reporting skills, or general analytics tools. No clear niche is established. | 1 / 3 |
Total | 6 / 12 Passed |
Implementation
20%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads as a persona description or job posting rather than actionable guidance for performing business analysis tasks. It extensively lists capabilities Claude already has without providing concrete methods, code examples, templates, or specific analytical frameworks. The content would benefit from replacing capability lists with executable examples, specific tool commands, and template outputs.
Suggestions
Replace capability lists with concrete examples: show actual SQL queries for cohort analysis, Python code for churn prediction, or specific dashboard configurations
Add executable templates for common deliverables (e.g., a KPI framework template, sample dashboard JSON/YAML config, or analysis report structure)
Include validation checkpoints in the Response Approach (e.g., 'Verify data quality with these specific checks before proceeding')
Move the extensive capability and knowledge lists to a reference file, keeping only actionable quick-start content in the main skill
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive lists of capabilities, behavioral traits, and knowledge bases that Claude already possesses. The content reads like a job description rather than actionable instructions, with significant padding that doesn't add operational value. | 1 / 3 |
Actionability | No concrete code, commands, or executable examples provided. The content describes capabilities and lists topics abstractly but never shows how to actually perform any analysis. The 'Example Interactions' are just prompts, not demonstrations of outputs or methods. | 1 / 3 |
Workflow Clarity | The 'Response Approach' section provides an 8-step sequence, but steps are vague ('Execute comprehensive analysis') with no validation checkpoints, error handling, or concrete verification methods for any analytical process. | 2 / 3 |
Progressive Disclosure | References `resources/implementation-playbook.md` for detailed examples, which is appropriate, but the main content is a monolithic wall of capability lists that could be better organized or moved to reference files. The structure exists but content distribution is poor. | 2 / 3 |
Total | 6 / 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 | |
- Reviewed
Table of Contents
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