tlc-spec-driven

Transform project requirements into adaptive planning and execution workflows.

Updated May 25, 2026

Search Tags:#git workflow #software development #project planning #ai agents #task breakdown #feature specification #codebase analysis

Ready to run

npx skills add https://github.com/Yairama/mine-rs --skill tlc-spec-driven-yairama

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tlc-spec-driven
Source: https://github.com/Yairama/mine-rs/tree/main/.github/skills/tlc-spec-driven
Command: npx skills add https://github.com/Yairama/mine-rs --skill tlc-spec-driven-yairama

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps AI agents avoid chaotic software development by turning vague project requests into structured, traceable workflows with the right amount of planning for each complexity level.

Core Features & Use Cases

Adaptive Project Planning: Guides projects through Specify, Design, Tasks, and Execute phases while automatically reducing ceremony for simpler work.
Implementation Discipline: Creates atomic tasks, verification criteria, requirement traceability, and focused commits to improve delivery quality.
Use Case: A development team can use this Skill to map an existing codebase, define a new feature specification, break work into executable tasks, and continue implementation across sessions with persistent project context.

Quick Start

Use the tlc-spec-driven skill to initialize my project, define its roadmap, and guide the implementation of my next feature.

Frequently Asked Questions about tlc-spec-driven

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

FAQPage Schema

How do I structure AI agent workflows for software development to avoid chaotic execution?▼

Spec-driven software development structures AI agent workflows by transforming vague project requirements into adaptive planning phases—Specify, Design, Tasks, and Execute—while automatically reducing ceremony for simpler work and ensuring requirement traceability.

What is the best way to break down feature specifications into executable coding tasks?▼

Breaking down feature specifications into executable coding tasks requires creating atomic tasks with explicit verification criteria and requirement traceability, ensuring disciplined execution and focused commits throughout the implementation process.

Can I use this structured planning workflow for both new projects and existing codebases?▼

Yes, this structured planning workflow applies to new projects, existing codebases, feature planning, bug fixes, and session continuity scenarios by mapping codebase context and maintaining persistent project context across development sessions.

How do I maintain project context and implementation tracking across multiple AI coding sessions?▼

Maintaining project context across multiple AI coding sessions requires context-aware documentation and session continuity practices, allowing development teams to pause and resume implementation with persistent project state and requirement traceability.

Does adaptive project planning reduce workflow ceremony for simpler software development tasks?▼

Adaptive project planning reduces workflow ceremony for simpler software development tasks by automatically adjusting the planning depth across Specify, Design, Tasks, and Execute phases based on the complexity level of the requested work.

When should I avoid using a full spec-driven workflow for my software project?▼

You should avoid using a full spec-driven workflow when your software project requires minimal planning overhead, as the adaptive planning mechanism automatically reduces ceremony for simpler work rather than enforcing rigid process steps.