niallyoung

Agentic Engineers — AI skill for Claude Code

AI community

portable sub-agent orchestration "AGENTS with SKILLS" (Orchestrator delegates 1..N specialist AGENTS (model+skill/s) optimising for token usage, quality and speed ♻️self-improving♻️ make install ~/.

How to install Agentic Engineers

This entry records only its repository, not the path inside it, so there is no exact command to give. Open niallyoung/agentic-engineers and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Agentic Engineers does

portable sub-agent orchestration "AGENTS with SKILLS" (Orchestrator delegates 1..N specialist AGENTS (model+skill/s) optimising for token usage, quality and speed ♻️self-improving♻️ `make install` ~/ configs for CLI harnesses: Claude, Copilot, Codex, OpenCode, Pi

Alternatives in AI

  • Paul — Plan-Apply-Unify Loop — Structured AI-assisted development for Claude Code 1.2k ★
  • Pilotfish — Multi-model orchestration layer for Claude Code — the frontier model plans, cheaper models execute, verificati 688 ★
  • Agentic SEO Skill — An LLM-first SEO analysis skill for Antigravity, Codex, Claude with 16 specialized sub-skills, 10 specialist a 419 ★

README

Agentic Engineers

A **multi-agent orchestration framework** for coordinating specialized AI agents through structured handoffs, quality gates, and cost-aware model selection. Designed for integration with coding CLIs: **OpenCode**, **Copilot**, **Claude**, **Codex**.

What It Is

Agentic Engineers solves the multi-agent coordination problem: how do you route work to the right specialist, enforce quality consistently, and keep cost proportional to task complexity — through an elegant, minimal orchestration layer?

**The answer:** an ORCHESTRATOR-FIRST architecture built on **direct sub-agent spawning**:

  1. Work is expressed as a DELEGATE task (structured YAML: scope, context, plan, success criteria)
  2. The Orchestrator spawns the right specialist directly (Agent/Task tool) and reads the HANDBACK back as that spawn call's result synchronously, in-context
  3. The specialist executes and returns a HANDBACK with results + metrics
  4. The harness session transcript itself — every DELEGATE as a spawn prompt, every HANDBACK as that spawn's result — is the durable audit record
  5. Metrics feed back into model selection and routing for future tasks

Goals

The framework is built to be **minimal, portable, and self-reducing**:

  • Small AGENTS + SKILLS mechanisms — a portable orchestration layer that works across harnesses (Claude, Copilot, OpenCode, Codex) without proprietary integrations
  • Framework self-reduction — as base and frontier models improve, LOC and complexity are meant to decrease, not grow
  • Eventual redundancy — when harnesses compose and delegate work well by default, this coordination layer should fade into standard practice
  • Harness comparative analysis — the src/ → make render → dist/ → make install → ~/. pipeline lets the same agent/skill roster be compared across harnesses for feature parity and quality trade-offs

Positioning

Agentic-engineers is one layer in a three-tier orchestration landscape: **heavy frameworks**