About this skill

Problem

Data-analysis work often stalls on unclear goals, skipped steps, missing checks, and gut-driven comparisons. A business-analysis deliverable may lack an acceptance criterion, or a team may need to choose among data definitions and tools without a stable evaluation path.

How It Works

The skill routes common requests into five capabilities: task breakdown, template generation, checklists, option comparison, and retrospective improvement.

When triggered by how to do / breakdown / steps, it takes goal + constraints and returns steps + deliverables + acceptance checks.
When triggered by template / format / example, it takes a scenario and returns a reusable template.
When triggered by check / checklist / pitfalls, it takes items and returns prioritized checks.
When triggered by choose / compare / tradeoff, it takes options and returns a pros/cons table with a recommendation.
When triggered by retrospective / summary / optimization, it takes result data and returns a retrospective sheet plus improvement items.

The core workflow requires writing acceptance criteria first, then decomposing work into steps with explicit inputs and outputs, and finally validating with quality self-checks and a priority matrix. For comparisons, it lists dimensions, scores them, checks sensitivity, and decides with a fallback.

Boundaries

It outputs methodology, templates, and checklists for structuring analysis tasks. It does not replace professional judgment, and it does not use external accounts, keys, or paid services. Seek professional advice for legal, safety, or medical decisions.

Screenshots

Use Cases

When receiving a monthly business analysis goal but unsure where to start, use task breakdown to split scoping, data pulls, analysis, and delivery.
When producing a reusable data report template, enter the business scenario and audience to generate a structured layout.
Before launching a data dashboard, use checklists to verify metric definitions, permissions, and outliers.
When choosing between two attribution analysis options, compare cost, timeline, risk, and benefit with a recommendation.

Best For

Data analysts writing weekly business reports who need to turn scattered analysis requests into verifiable steps.
Growth operations leads who need to compare metric definitions and analysis options for experiments.
Engineers delivering data dashboards who want pre-launch checks for metrics, permissions, and risks.
Team leads reviewing experiment results who need to turn summaries into improvement actions.