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. Use PROACTIVELY for business intelligence or strategic analysis.
45
Quality
35%
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 ./docs/v19.7/configuration/agent/skills_external/antigravity-awesome-skills-main/skills/business-analyst/SKILL.mdQuality
Discovery
50%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 attempts to cover business analysis capabilities but relies heavily on buzzwords ('AI-powered', 'data-driven', 'master modern') that add little discriminative value. While it includes a trigger clause, the guidance is too broad to help Claude distinguish this skill from related analytics or data skills. The description would benefit from more concrete actions and specific user-facing trigger terms.
Suggestions
Replace vague buzzwords with concrete actions (e.g., 'Calculate ROI, analyze revenue trends, build financial forecasts' instead of 'AI-powered analytics, data-driven insights')
Expand the 'Use when...' clause with specific trigger terms users would say: 'Use when user mentions business metrics, revenue analysis, market trends, competitive analysis, or asks for executive summaries'
Add distinguishing details that separate this from general data/analytics skills, such as specific business domains (finance, marketing, operations) or output types (executive reports, board presentations)
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names domain (business analysis) and some actions (KPI frameworks, predictive models, strategic recommendations), but uses vague buzzwords like 'AI-powered analytics' and 'data-driven insights' without concrete specifics on what actions are actually performed. | 2 / 3 |
Completeness | Has a 'what' (analytics, dashboards, KPI frameworks) and includes 'Use PROACTIVELY for...' which provides some trigger guidance, but the 'when' is vague ('business intelligence or strategic analysis') rather than explicit user-facing triggers. | 2 / 3 |
Trigger Term Quality | Includes some relevant terms like 'business intelligence', 'strategic analysis', 'KPI', 'dashboards', but missing common user variations like 'metrics', 'reports', 'forecasting', 'business metrics', or specific file types users might mention. | 2 / 3 |
Distinctiveness Conflict Risk | Terms like 'analytics', 'dashboards', and 'data-driven insights' could easily overlap with data science, reporting, or general analytics skills. 'Business analysis' is somewhat distinctive but not clearly differentiated from adjacent domains. | 2 / 3 |
Total | 8 / 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 content functions more as a persona description or job posting than an actionable skill guide. It extensively lists capabilities Claude already has without providing concrete implementation guidance, executable code, or specific methodologies. The content would benefit from dramatic reduction and replacement with actual analytical frameworks, code examples, and step-by-step procedures.
Suggestions
Replace capability lists with 2-3 concrete, executable examples (e.g., actual Python code for cohort analysis, SQL for KPI queries, or a specific dashboard design template)
Add validation checkpoints to the Response Approach (e.g., 'Verify data quality before proceeding: check for nulls, outliers, date ranges')
Remove behavioral traits and knowledge base sections entirely - these describe Claude's existing capabilities and waste tokens
Convert 'Example Interactions' from prompts into worked examples showing actual analytical outputs or frameworks
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive lists of capabilities, knowledge bases, and behavioral traits 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 abstractly ('Advanced dashboard creation with Tableau') rather than providing specific steps or copy-paste ready guidance. Example interactions are prompts, not solutions. | 1 / 3 |
Workflow Clarity | The 'Response Approach' section provides an 8-step sequence that is reasonably clear, but lacks validation checkpoints, error handling, or feedback loops. Steps are high-level descriptions rather than concrete actions with verification points. | 2 / 3 |
Progressive Disclosure | References `resources/implementation-playbook.md` for detailed examples, which is appropriate. However, the main content is a monolithic wall of capability lists that should be restructured or moved to reference files, making the overview bloated. | 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 |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- duclm1x1/Dive-Ai
- Commit
20ba150
- Reviewed
Table of Contents
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