← ClaudeAtlas

orchestrate-workflowlisted

Wire a generate-review-fix multi-agent workflow (one implementer, N adversarial reviewers, a fixer) from agentstack profiles — models per role, skills per role, secrets injected at start — and run it in your executor of choice (sandcastle, Claude Code workflows, or plain Docker). agentstack provisions and governs the agents; it never runs the loop.
Tarekkharsa/agentstack · ★ 2 · AI & Automation · score 75
Install: claude install-skill Tarekkharsa/agentstack
# Orchestrate a governed multi-agent workflow Use when you want the Bun-in-Rust shape — an implementer writes, independent adversarial reviewers attack the diff, a fixer applies feedback — with each agent's capabilities, model, and secrets managed by agentstack instead of hand-assembled per run. The division of labor is fixed: **an executor runs the loop** (sandcastle, Claude Code workflows, your own script); **agentstack defines and provisions the agents** the loop spawns. Don't blur it in either direction. ## 1 — Define roles as profiles A role is a profile: which skills, which servers, and (by convention) which model. In `.agentstack/agentstack.toml`: ```toml [profiles.implementer] skills = ["porting-guide"] # the task's context artifacts servers = ["github"] [profiles.reviewer] skills = ["adversarial-review"] # ships in this catalog servers = [] # reviewers judge the diff; no tools needed ``` Keep reviewer profiles minimal on purpose — a reviewer with no servers can't be tool-poisoned, and the diff is all it should trust anyway. ## 2 — Bind models to roles Pick per role, not per run: bulk/mechanical implementation → a cheap strong coder; review → a different model family than the implementer when possible (diverse failure modes). Record the binding wherever the executor configures each agent (sandcastle's `agent:` option, a Workflow `model:` param, a `--model` flag). If the route-by-cost skill is loaded, apply its ladder. ## 3 —