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tlc-spec-driven — how to use tlc-spec-driven how to use tlc-spec-driven, tlc-spec-driven alternative, tlc-spec-driven setup guide, what is tlc-spec-driven, tlc-spec-driven vs traditional development methods, installing tlc-spec-driven for Plesk extensions

v1.0.0
GitHub

About this Skill

Ideal for AI Agents like Cursor and AutoGPT requiring structured project planning with granular tasks and clear dependencies tlc-spec-driven is a skill that facilitates spec-driven development for Plesk extensions using AI-powered semantic search and vector embeddings.

Features

Utilizes RAG for AI-powered semantic search in Plesk extension development documentation
Employs vector embeddings for efficient project planning and implementation
Follows a structured project plan with SPECIFY, DESIGN, TASKS, and IMPLEMENT+VALIDATE stages
Organizes project structure using .specs/ directory with PROJECT.md, ROADMAP.md, and STATE.md files

# Core Topics

barateza barateza
[0]
[0]
Updated: 3/7/2026

Quality Score

Top 5%
62
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add barateza/mcp-plesk-extension-guide/references/code-analysis.md

Agent Capability Analysis

The tlc-spec-driven MCP Server by barateza is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use tlc-spec-driven, tlc-spec-driven alternative, tlc-spec-driven setup guide.

Ideal Agent Persona

Ideal for AI Agents like Cursor and AutoGPT requiring structured project planning with granular tasks and clear dependencies

Core Value

Empowers agents to utilize RAG and vector embeddings for AI-powered semantic search in project development documentation, streamlining spec-driven development with tools like Plesk extensions, and implementing projects with precision using SPECIFY, DESIGN, TASKS, and IMPLEMENT+VALIDATE workflows

Capabilities Granted for tlc-spec-driven MCP Server

Planning projects with precision using granular tasks and clear dependencies
Implementing spec-driven development with tools like Plesk extensions
Utilizing RAG and vector embeddings for AI-powered semantic search in project documentation

! Prerequisites & Limits

  • Requires project documentation structure as specified in .specs/ directory
  • Dependent on vector embeddings and RAG for semantic search functionality
Project
SKILL.md
3.9 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

[No tags]
SKILL.md
Readonly

Tech Lead's Club - Spec-Driven Development

Plan and implement projects with precision. Granular tasks. Clear dependencies. Right tools.

┌──────────┐   ┌──────────┐   ┌─────────┐   ┌───────────────────┐
│ SPECIFY  │ → │  DESIGN  │ → │  TASKS  │ → │ IMPLEMENT+VALIDATE│
└──────────┘   └──────────┘   └─────────┘   └───────────────────┘

Project Structure

.specs/
├── project/
│   ├── PROJECT.md      # Vision & goals
│   ├── ROADMAP.md      # Features & milestones
│   └── STATE.md        # Memory between sessions
├── codebase/           # Brownfield analysis (existing projects)
│   ├── STACK.md
│   ├── ARCHITECTURE.md
│   ├── CONVENTIONS.md
│   ├── STRUCTURE.md
│   ├── TESTING.md
│   └── INTEGRATIONS.md
└── features/           # Feature specifications
    └── [feature]/
        ├── spec.md
        ├── design.md
        └── tasks.md

Workflow

New project:

  1. Initialize project → PROJECT.md
  2. Create roadmap → ROADMAP.md
  3. Specify features → existing workflow

Existing codebase:

  1. Map codebase → 6 brownfield docs
  2. Initialize project → PROJECT.md + ROADMAP.md
  3. Specify features → existing workflow

Context Loading Strategy

Base load (~15k tokens):

  • PROJECT.md (if exists)
  • ROADMAP.md (when planning/working on features)
  • STATE.md (persistent memory)

On-demand load:

  • Codebase docs (when working in existing project)
  • spec.md (when working on specific feature)
  • design.md (when implementing from design)
  • tasks.md (when executing tasks)

Never load simultaneously:

  • Multiple feature specs
  • Multiple architecture docs
  • Archived documents

Target: <40k tokens total context Reserve: 160k+ tokens for work, reasoning, outputs Monitoring: Display status when >40k (see context-limits.md)

Commands

Project-level:

Trigger PatternReference
Initialize project, setup projectproject-init.md
Create roadmap, plan featuresroadmap.md
Map codebase, analyze existing codebrownfield-mapping.md
Record decision, log blockerstate-management.md
Pause work, end sessionsession-handoff.md
Resume work, continuesession-handoff.md

Feature-level:

Trigger PatternReference
Specify feature, define requirementsspecify.md
Design feature, architecturedesign.md
Break into tasks, create taskstasks.md
Implement task, buildimplement.md
Validate, verify, testvalidate.md

Tools:

Trigger PatternReference
Code analysis, search patternscode-analysis.md

Output Behavior

Model guidance: After completing lightweight tasks (validation, state updates, session handoff), naturally mention once that such tasks work well with faster/cheaper models. Track in STATE.md under Preferences to avoid repeating. For heavy tasks (brownfield mapping, complex design), briefly note the reasoning requirements before starting.

Be conversational, not robotic. Don't interrupt workflow—add as a natural closing note. Skip if user seems experienced or has already acknowledged the tip.

Code Analysis

Use available tools with graceful degradation. See code-analysis.md.

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