You're the CTO. You're also the bottleneck. GreatCTO is 34 specialist agents that handle architecture, review, QA, security, and deploy — while you make two decisions per feature. Same plugin works in Claude Code, Cursor, OpenAI Codex CLI, Aider, and Continue via AGENTS.md + MCP.
Run npx great-cto adapt --platform all once. The same archetype + compliance gates flow into every assistant your team uses — no re-onboarding, no duplicated rules.
packages/cursor-ext/.great-cto ci.great-cto mcp --stdio or --sse.great_cto/PROJECT.md once. Re-run adapt. Every consumer updates.npx great-cto ci ./ drops into GitHub Actions with auto-detected ::error:: annotations + SARIF.— until now.
No prompt-engineering. No agent-orchestration tutorial. No YAML.
Detects archetype from manifests (15 signals → 14 archetypes), wires the gates, loads the right agents.
Architect drafts the architecture doc. You approve, refine, or reject. That's decision one.
Performance, security, SQL safety, concurrency, privacy, API contracts. Every finding rated. P0 blocks the gate.
5% → 20% → 100%. RELEASE doc auto-written. On-call notified. Memory updated for next time.
great-cto board at localhost:3141. Inbox · Kanban · Metrics · Agents · Memory · Public report. Vanilla HTML, zero deps — no Electron, no Tauri, no SaaS.
Gates · Backlog · In Progress · Done · Blocked. Cards are priority-coded, agent-tagged, with inline status / priority edit. ⌘K search across title / id / agent / labels. Live SSE — bd-CLI changes appear in the UI in <1s.
Tasks shipped · LLM spend · cost-savings vs FTE · cycle time · QA pass rate · security blocks. 30-day daily-burn chart with budget alerts. A separate Agents tab shows per-agent time, LLM cost, and human-equivalent dollars at $150/hr.
docs/plans/.
29 specialist agents, each with its own time budget, LLM cost, and tasks-done counter. Compare to a human team at $150/hour and see the multiplier. Activity feed surfaces APPROVED / BLOCKED / FAIL verdicts with the agent that issued them.
Open a session — three columns greet you: In progress (your WIP tasks), Recent verdicts (what your agents finished while you slept), Decisions (every gate approval is logged with reasoning). Stop re-explaining your project to Claude.
~/.great_cto/decisions.md — query across all your projects.
PROJECT.md (archetype, goals) · lessons.md (per-project retros) · decisions.md (every gate approval with rationale) · verdicts/ (every agent verdict logged). Agents query memory before reading source files — solved problems stay solved.
Cursor and Copilot run one review pass. We run twelve. Every finding rated P0 / P1 / P2. P0 blocks the gate. You can't accidentally ship a SQL injection.
We scan your package.json, pyproject.toml, Cargo.toml, README, and code structure. Then we pick the right agent set, security tier, and compliance checklists.
Detection uses heuristics + (when low confidence) an Anthropic Haiku second-opinion call (~$0.001). You can override with --archetype NAME.
Cursor and Copilot are great editors. They are not SDLC pipelines. Here's what each does — honestly.
| great_cto our pick | Cursor | Copilot Workspace | Claude Projects | |
|---|---|---|---|---|
| SDLC orchestration | ||||
| Multi-agent SDLC pipeline | ✓ 29 specialists | ✕ | ✕ | ✕ |
| Auto archetype detection | ✓ 17 types | ✕ | ✕ | ✕ |
| 12-angle code review | ✓ | ⚠ single-pass | ⚠ single-pass | ✕ |
| Compliance gates (PCI / HIPAA / SOX / EU AI Act) | ✓ | ✕ | ✕ | ✕ |
| Memory & visibility | ||||
| Persistent memory | ✓ decisions.md + verdicts | ⚠ chat-only | ✕ | ✓ chat scope |
| Multi-project view | ✓ | ✕ | ✕ | ⚠ |
| Public sharable reports | ✓ | ✕ | ✕ | ✕ |
| Ownership & cost | ||||
| Open source | ✓ MIT | ✕ | ✕ | ✕ |
| Runs locally | ✓ | ⚠ partial | ✕ | ✕ |
| Pay your own API | ✓ | ✕ | ✕ | ✕ |
| Pricing | $0 + your API | $20/mo | $39/mo | $20/mo |
We're not an editor — we orchestrate the process around your editor. Use Cursor inside the loop if you want.
Cursor forgets your project the moment you close the tab. GreatCTO synthesizes — into a 10–50 KB local memory that travels across sessions, machines, and projects.
Archetype, size, compliance frameworks, owners, team patterns. Set on first /start.
.great_cto/PROJECT.md
God-nodes, entry points, public API surface, routing. Built in 30s by zero-dep bash — no LLM cost.
.great_cto/CODEBASE.md
Patterns in use, what failed, decisions made. Synthesized weekly + after every postmortem.
.great_cto/brain.md
Promoted via /crystallize after a P0. Surfaces in every agent's Step 0 — across every project, forever.
~/.great_cto/global-patterns/
GreatCTO is open source (MIT). You pay your own Anthropic API tokens. We don't see them. We don't bill you. Nothing to subscribe to.
$ npx great-cto ci ./ \
--sarif results.sarif
$ npx great-cto mcp
$ npx great-cto serve
npx great-cto adapt --platform cursor generates .cursorrules, --platform aider generates .aider.conf.yml, etc. — same archetype, same gates, every tool.AGENTS.md verbatim; we generate it. Continue reads .continue/rules.md; we generate that too. Plus the great-cto mcp server exposes 5 tools (scan, list_rules, detect_archetype, estimate_cost, query_decisions) over stdio + SSE — any MCP-aware host can call them. Setup snippets in the README →npx great-cto ci ./ drops into GitHub Actions / GitLab / any CI as a single step. Auto-detects $GITHUB_ACTIONS and emits inline ::error file=... annotations on PR diffs. Outputs SARIF for the GitHub Security tab + JUnit XML for test reporters. Exit 0 clean, 1 findings, 2 setup error./audit reads the repo, builds CODEBASE.md, generates a backlog of gaps. Tested on JS/TS, Python, Rust, Go. ~2 minutes for 100k LOC..great_cto/. You can .gitignore them or commit them — your call..great_cto/PROJECT.md → agents: [...]. Or override at runtime: /start "feature" --agents=architect,senior-dev,qa.PROJECT.md. Worst case: it costs 2× for 6 weeks until we add the next provider. The plugin is MIT — you can fork.