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sprint-1-executor

Execute sprint tasks with dependency validation and progress tracking.

Updated Aug 23, 2026
Search Tags:#workflow automation#task automation#dbt#GitHub Actions#data ingestion#project execution#sprint management
One-click install
npx skills add https://github.com/zazu-22/ff_data_analytics --skill sprint-1-executor
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sprint-1-executor
Source: https://github.com/zazu-22/ff_data_analytics/tree/main/.claude/skills/sprint-1-executor
Command: npx skills add https://github.com/zazu-22/ff_data_analytics --skill sprint-1-executor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires uv, dbt-duckdb, polars, requests, pandas, numpy, scikit-learn, jupyter, sqlfluff, mypy, ruff, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the execution of complex sprint tasks, eliminating manual errors, accelerating development cycles, and providing clear, actionable updates on project milestones. It ensures precise adherence to task specifications, thorough validation, and accurate progress tracking, allowing teams to focus on strategic thinking rather than task management.

Core Features & Use Cases

  • Automated Task Execution: Execute specific sprint tasks (e.g., cap space parsing, Sleeper integration, FASA target marts, valuation model training) with built-in validation.
  • Dependency-Aware Workflow: Automatically check and manage task dependencies, guiding users through sequential workflows and preventing premature execution.
  • Comprehensive Reporting & Tracking: Generate precise commit messages, update sprint plans, and report task status, ensuring transparent and up-to-date project progress.
  • Use Case: You're ready to start Sprint 1 Task 1.1: Cap Space Foundation. This Skill will automatically modify Python parsers, create dbt models, run all associated tests, and, upon success, generate the commit message and update the sprint's progress tracking.

Quick Start

Execute Sprint 1 Task 1.1: Cap Space Foundation, and report the results.

Frequently Asked Questions about sprint-1-executor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate sprint task execution with validation and progress tracking?▼

Sprint task automation executes prescribed steps sequentially, validates dependencies, runs validation commands, commits changes with specified messages, and updates progress tracking—eliminating manual errors and accelerating development cycles while ensuring precise adherence to task specifications.

Can I use workflow automation with dbt and GitHub Actions for task management?▼

Yes. This automates sprint tasks using dbt for data transformation, GitHub Actions for CI/CD workflows, and dependency-aware execution. It orchestrates complex task pipelines—cap space parsing, data ingestion, model training—with built-in validation across your stack.

What dependencies do I need to run sprint task automation?▼

Sprint task automation requires uv, dbt-duckdb, polars, pandas, numpy, scikit-learn, requests, jupyter, sqlfluff, mypy, and ruff. These tools enable data processing, SQL linting, type checking, code quality analysis, and dependency management across your workflow pipeline.

How do I prevent execution errors when sprint tasks have dependencies?▼

Dependency-aware workflow validation automatically checks task prerequisites, guides sequential execution, and prevents premature task runs. This ensures upstream tasks complete successfully before downstream tasks begin, eliminating cascading failures and rework.

What happens after a sprint task completes successfully?▼

Upon success, the Skill generates a precise commit message with changes, updates sprint progress tracking in your repository, and reports task status. This provides transparent, up-to-date visibility into project milestones and team progress.

Does this work for multi-phase sprint planning across FASA optimization and trade analytics?▼

Yes. The Skill supports Phase 1–3 tasks with current focus on Phase 2 FASA Intelligence (Tasks 11–13, Task 1.4). It executes sprint tasks for cap space parsing, Sleeper integration, FASA target marts, and valuation model training across your analytics workflow.

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