Gin is a Go workable choice for healthcare. GreatCTO auto-detects both — adds the healthcare archetype overlay, wires healthcare-specific gates, and runs 34 specialist agents around your existing Gin workflow.
GreatCTO reads your go.mod and detects gin + healthcare archetype from signals: imports, file structure, env vars, README hints.
Attaches the healthcare archetype overlay: HIPAA gates, BAA tracking, PHI encryption review, 21 CFR Part 11 audit-trail. Override if your specifics differ; the defaults are sensible for Gin-style projects.
qa-engineer runs go vet / staticcheck / go test -race -cover; security-officer reviews context cancellation + goroutine leaks; performance-engineer profiles pprof CPU + heap.
Bugs you've hit before in other Gin projects (connection-pool exhaustion, ORM N+1 queries, retry storms) — the agent's Step 0 includes the prior detection order. MTTR drops 94 % on second occurrence (methodology).
$ cd my-gin-app && npx great-cto init ✓ scanning manifests… found manifest ✓ stack: gin (Go) ✓ archetype: healthcare ⚠ archetype + stack combo is unusual — review overlay manually ✓ 34 agents ready $ /start "add HL7 patient resource endpoint" ▸ architect drafting ARCH-healthcare.md… ▸ pm decomposing into beads tasks… ⚐ gate:plan — your approval needed
Approve → 3 senior-devs run in parallel worktrees → 5 reviewers fan out in parallel → gate:ship → deploy. One real run walked stage-by-stage: /proof.
Gin (Go) is not a typical fit for healthcare. The archetype overlay still attaches, but you may want to override defaults more aggressively. Check the healthcare archetype page for the typical stack list and decide if your case is the right tool / right archetype.
No black-box "AI does it all" loop. GreatCTO is a deterministic state machine — 8 stages, 22 nodes, 2 human gates. Every node maps to a real agent on GitHub. Inspect the state machine →
$ npx great-cto init
Free, MIT, runs locally. Works in Claude Code, Cursor, OpenAI Codex CLI, Aider, and Continue.