nacl-tl-full

Orchestrate end-to-end TL workflows from Neo4j graph plans.

23|2|Updated Apr 10, 2026
One-click install
npx skills add https://github.com/ITSalt/NaCl --skill nacl-tl-full
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: nacl-tl-full
Source: https://github.com/ITSalt/NaCl/tree/main/nacl-tl-full
Command: npx skills add https://github.com/ITSalt/NaCl --skill nacl-tl-full

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates end-to-end lifecycle orchestration for software projects by coordinating TeamLead (TL) skills across infrastructure, development, review, QA, and documentation, using a Neo4j-backed plan as the single source of truth.

Core Features & Use Cases

  • Orchestrates full TL workflow across waves and UCs, delegating tasks to specialized skills (dev-be, dev-fe, review, sync, QA, docs) while maintaining graph-based progress and dual-write status to .tl/status.json.
  • Supports two-gate autonomy (plan approval and end-of-run report), robust retry loops with per-phase failure handling, and resume capabilities from Neo4j state.
  • Enables parallel execution for independent UCs within a wave and provides comprehensive final reporting including unresolved issues and stubs/QA results.

Quick Start

Initiate the autonomous full lifecycle orchestration using the Neo4j plan and run all TL tasks from infrastructure to documentation.

Frequently Asked Questions about nacl-tl-full

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

FAQPage Schema
How do I orchestrate full DevOps workflows using a Neo4j graph?

You can orchestrate full DevOps workflows by reading waves and tasks directly from a Neo4j graph, delegating execution to specialized skills, and tracking progress with dual-write status updates for autonomous recovery.

What is graph-aware progress tracking for automated software lifecycles?

Graph-aware progress tracking uses a Neo4j database as the single source of truth to monitor autonomous execution across development waves, enabling robust resume capabilities and per-phase failure handling.

How do I automate retry and resume capabilities for failed workflow tasks?

Automated retry and resume capabilities are handled through robust retry loops that process per-phase failures and restore execution state directly from the Neo4j graph, ensuring continuous workflow progression.

Can I run parallel execution for independent tasks within an orchestration wave?

Yes, autonomous orchestration supports parallel execution for independent tasks within a single wave, allowing multiple specialized skills to operate concurrently while maintaining graph-based progress.

Do I need Neo4j to autonomously orchestrate end-to-end project workflows?

Yes, Neo4j is required because the orchestration reads waves and tasks from the graph database to serve as the single source of truth for planning, execution, and graph-aware state recovery.

What are the limitations of gate-based autonomous workflow orchestration?

Gate-based autonomous orchestration relies on two specific approval gates for plan approval and end-of-run reporting, meaning manual intervention is required at these checkpoints before proceeding to the next phase.