great_cto
You already have the agent. This is everything around it. great_cto runs Claude Code as a pipeline of 70 specialist agents — an independent model checks each stage before the next builds on it, spending caps refuse rather than warn, and three decisions stay yours: what gets built, how, and whether it ships.
No outside reports on file
This tool trades simplicity for control and auditability—use it when you value staged review and cost caps over speed, and monitor agent decisions closely since you can't easily undo them mid-pipeline.
Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionNo shell command runner notedLOW
- Network reachConnects to outside service APINOTED
- CredentialsNo API token requiredLOW
- Package sourcenpm (great-cto)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
npx -y great-ctoEverything known
We found nothing about this project in the sources we read (last checked 2026-10-30). That does not mean it has no problems.
0 incidents · 0 advisories · 0 news articles · 0 community threads · checked 2026-10-30
Popularity grade: C (from public signals such as stars and downloads, not a code review). Graded 2026-10-24.
Sources we read: OSV, GitHub Advisory Database, CISA Known Exploited Vulnerabilities, 44 security news feeds and our incident library. Last checked 2026-10-30.
About Great Cto
great_cto is a system that breaks down coding tasks into a pipeline of 70 specialized AI agents, with independent verification at each step. It enforces spending limits that stop work rather than just warn, and keeps three key choices with you: what to build, how to build it, and whether to deploy it.
Who it’s for
Developers and teams who want AI-assisted code generation with built-in checkpoints and cost control. It's for people who want quality reviews between stages rather than a single AI pass.
Alternatives
- Claude API with prompt chaining: Direct API calls with your own verification logic between steps.
- GitHub Copilot Workspace: AI-assisted coding with human review built into the UI.
- Cursor or Windsurf editors: IDE-integrated AI agents with inline code review and approval.
- LangChain or LlamaIndex pipelines: Custom orchestration frameworks for multi-stage AI workflows.
Setup
Check these steps against the project’s own instructions before running anything.
Install via npm:
npm install great-cto
Or use directly from GitHub. Follow the project's README for configuration details on budget caps, specialist agent roles, and verification settings.
Why this grade
Signal-based grade (3/7 points): listed in several sources, public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 108
- Weekly npm downloads
- 1.4k
- Listing last refreshed
- 2026-10-30
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Risks to watch for
- Code quality checks depend on AI reviewers: Each verification stage uses AI judgment; subtle bugs or security flaws could pass through if the checking agents miss them.
- Spending limits are hard stops: If you hit your budget mid-project, work halts without a clear recovery path; ensure caps are realistic for your task.
- Complex pipeline = hard to debug: With 70 agents in sequence, tracing where a bad decision came from is difficult; one agent's mistake compounds through later stages.
- External dependencies unknown: The system may call external APIs or models; review what services are called and what data flows through them.
- Prompt injection in code reviews: If agents analyze untrusted code or user input, attackers could craft malicious comments or strings to trick the reviewing agents.
How to lower the risk
Least-privilege permissions
- Run agents with read-only access to code repos where possible.
- Limit API keys to the minimum scopes needed for each stage.
Network isolation
- Keep the pipeline on trusted infrastructure; don't expose agent outputs to untrusted networks.
- Log all inter-agent communication for audit trails.
Monitoring
- Watch spending in real time; alert when approaching budget caps.
- Review each verification stage's decision before the next agent starts work.
Red flags to watch for
- Agents approving code without clear reasoning or traces.
- Unexpected API calls or outbound network traffic.
- Spending anomalies or budgets depleting faster than expected.
Questions
How do I install Great Cto?
Install Great Cto with npm install great-cto or run it directly with npx -y great-cto. For agent integration and configuration flags, see the documentation at github.com/avelikiy/great_cto. Pin an exact version and pass --ignore-scripts if you want to block post-install hooks.
Are there security reports about Great Cto?
No reports found for this package in our research (last checked 2026-10-30). Great Cto currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include code quality checks depend on ai reviewers, spending limits are hard stops, complex pipeline = hard to debug.
Is Great Cto actively maintained?
Great Cto has 108 GitHub stars and 1.4k weekly npm downloads. Our directory data was last refreshed on 2026-10-30. Check recent commit activity, release tags, and open issues at github.com/avelikiy/great_cto before pinning it in production.
What are alternatives to Great Cto?
Notable alternatives to Great Cto include Claude API with prompt chaining (Direct API calls with your own verification logic between steps), GitHub Copilot Workspace (AI-assisted coding with human review built into the UI), Cursor or Windsurf editors (IDE-integrated AI agents with inline code review and approval), LangChain or LlamaIndex pipelines (Custom orchestration frameworks for multi-stage AI workflows). You can also compare Great Cto side by side with other skills in the Related tools section on this page.
README badge and team notes
Maintain or use Great Cto? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.
GitHub README Markdown:
[](https://agentarmorhq.com/skills/avelikiy-great-cto)HTML embed:
<a href="https://agentarmorhq.com/skills/avelikiy-great-cto"><img src="https://agentarmorhq.com/api/badge/avelikiy-great-cto" alt="AgentArmorHQ Risk Grade for Great Cto" height="20" /></a>Terminal check:
curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "avelikiy-great-cto"Share with your security lead
Need sign-off to use great_cto? Copy this note for Slack, a ticket or a pull request.
### AgentArmorHQ Security Review Memo: great_cto
- **Listing URL:** https://agentarmorhq.com/skills/avelikiy-great-cto
- **Type:** AI agent skill
- **Risk Grade:** Grade C (Moderate risk signals)
- **Outside Security Advisories on File:** 0
- **Public Adoption:** 108 GitHub stars, 1.4k weekly npm downloads
#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** No shell command runner noted
- **Network reach:** Connects to outside service API
- **Credentials:** No API token required
- **Package source:** npm (great-cto)
#### Recommended Hardened Setup
- **Command:** `npx -y --ignore-scripts great-cto`
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.
_Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee._Key facts
- Type
- AI agent skill
- Publisher
- avelikiy
- Source code
- github.com/avelikiy/great_cto
- Install command
- npm install great-cto
- Est. context load
- ~103 tokens idle · ~500 tokens when active (on-demand skill)
- Popularity
- 108 GitHub stars, 1.4k weekly npm downloads
- Last updated
- 2026-10-30
- Last graded
- 2026-10-24
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