Tlc Spec Driven

A structured approach to feature planning that auto-sizes itself based on complexity. Small changes skip straight to implementation, while larger features get full specs with requirement IDs, architecture decisions, and atomic task breakdowns. The workflow is always Specify then Execute, with optional Design and Tasks phases in between that only kick in when scope demands it. Keeps project state, decisions, and blockers in persistent memory across sessions. Works for both greenfield projects and mapping existing codebases. The context loading strategy is thoughtful, keeping base load around 15k tokens and using sub-agents for research and parallel task execution. Opinionated but flexible enough to get out of your way when you're just fixing a bug.

skills.sh installs: 1.3K
GitHub stars: 7.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add tech-leads-club/agent-skills --skill tlc-spec-driven --agent claude-code

Installs into .claude/skills of the current project.

Files

Tech Lead's Club - Spec-Driven Development

Plan and implement features with precision. Granular tasks. Clear dependencies. Right tools. Zero ceremony.

┌──────────┐   ┌──────────┐   ┌─────────┐   ┌─────────┐
│ SPECIFY  │ → │  DESIGN  │ → │  TASKS  │ → │ EXECUTE │
└──────────┘   └──────────┘   └─────────┘   └─────────┘
   required      optional*      optional*     required

* Agent auto-skips when scope doesn't need it

Critical Rules (read before acting)

Loading this skill's files. Reference files live under references/ in this skill's own directory (where this SKILL.md resides). Resolve them relative to the skill directory, never the workspace root. When a step tells you to read a reference, read it to the end before acting.

SKILL.md on GitHub

Details

Repository: github.com/tech-leads-club/agent-skills
Categories: Testing & QA, Code Review & Quality, AI & Agent Building, Productivity & Planning, Python, Design & UI/UX
First seen: Jun 3, 2026