# Augment Code vs Skaftor

Augment Code records 326,215 monthly visits with +24.1% month-over-month growth and Freemium, Free Trial, Contact for Pricing pricing. Skaftor records 0 monthly visits with 0% growth and Paid, Contact for Pricing pricing.

| Metric | [Augment Code](https://openaitools.app/tool/augment-code) | [Skaftor](https://openaitools.app/tool/skaftor) |
| :--- | :--- | :--- |
| Website URL | https://www.augmentcode.com | https://skaftor.com |
| Categories | AI Agent, AI Code Assistant, AI Code Generator, AI Developer Tools | AI Workflow, AI Agent, AI Developer Tools, AI Project Management |
| Pricing Model | Freemium, Free Trial, Contact for Pricing | Paid, Contact for Pricing |
| Monthly Visits | 326,215 | 0 |
| MoM Growth Rate | +24.1% | 0% |
| Primary Market | United States | Global |
| Direct Visits | 137,070 | 0 |
| Review Score | 4.5 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Augment Code

Augment Code is an AI coding platform aimed at engineering organisations rather than individual autocomplete users. Its foundation is the Context Engine, which builds a structured understanding of an existing repository — dependencies, architecture, conventions — so that AI suggestions and generated changes fit the codebase instead of reading like generic boilerplate. The product works inside common IDEs and also in the terminal via a CLI.

The platform's recent focus is Cosmos, an agent orchestration layer for the software development lifecycle. Instead of a single assistant answering prompts, Cosmos runs connected loops: a ticket becomes a reviewed pull request, every new PR gets a first-pass code review, failed CI runs get diagnosed, Dependabot and Snyk alerts get triaged into prioritised issues, and on-call engineers inherit a completed investigation. Each loop hands its outcome to the next, and quality gates pause work for human review rather than shipping automatically.

Agents can be deployed in managed cloud sandboxes, on your own machines for code that cannot leave the building, or a mix of both. Native triggers cover GitHub, GitLab, Slack, Linear, Jira, schedules and typed webhooks, with integrations for CI systems. There is a free tier for individuals to try the assistant, while team and enterprise adoption is quote-based; the company has announced it is joining Harness to push the autonomous SDLC from idea to production.

**Pricing & Plans:** Freemium with a free tier for individual developers to start, plus paid team plans and enterprise/contact-for-pricing options. Enterprise deployment includes self-hosted and hybrid agent execution; exact seat and usage pricing is quoted by sales.

- **Context Engine codebase understanding:** Indexes architecture, dependencies and conventions across large repositories so generated code and reviews match how your team actually writes software.
- **Cosmos agent orchestration:** Runs connected SDLC loops — code review, ticket-to-PR, incident triage, dependency upgrades and security remediation — where each agent hands its result to the next.
- **Human-in-the-loop quality gates:** Work pauses at defined checkpoints so engineers approve plans and consequential actions instead of letting agents ship unreviewed changes.
- **Deploy anywhere:** Execute agents in managed cloud sandboxes, on local machines and dev VMs for sensitive code, or in your own AWS and GCP environments.
- **Expert registry and shared memory:** Choose from shipped agents, fork them, or build your own; corrections and shared knowledge improve future runs for the whole team.

**Strengths:** Deep codebase context means suggestions fit existing architecture and conventions; Loops connect across the SDLC instead of solving one isolated task; Quality gates keep humans in control of consequential changes; Flexible deployment including local and self-hosted execution for sensitive code

**Limitations:** Enterprise pricing is quote-based, which makes budgeting harder before a trial; The full value depends on wiring up integrations and triggers across your toolchain; Small teams and solo developers may find the orchestration layer heavier than needed

[Profile (Markdown)](https://openaitools.app/tool/augment-code.md)

## Skaftor

Skaftor targets the gap that opens up once AI agents write most of the code: requirements live in a document, decisions live in chat threads, and approvals live in someone's head. The platform takes a product requirements document and turns it into accept/reject requirements with acceptance criteria, a technical design tied to each requirement, and work orders each sized to roughly one pull request and mapped to the repository it changes.

Agents then build those work orders. You can run Claude Code, Codex, Gemini or DeepSeek on a managed cloud workstation with pricing shown before the run starts, or keep your own editor and wire in context over MCP (for example Cursor). Every run is metered against per-run and per-month budget caps.

Governance is the second half of the product. A gate reads each pull request against its acceptance criteria and names the evidence; CI can block, the clause check can block, and an AI review advises. Named roles approve each stage and approvals are written to an append-only audit trail, so an auditor can reconstruct how a change reached production. Skaftor integrates with GitHub, GitLab and Bitbucket as well as Jira, Linear, Notion, Confluence, Google Docs, SharePoint, AWS, Google Cloud and Azure.

**Pricing & Plans:** Skaftor is positioned as a paid enterprise platform (listed as Paid / contact for pricing). Agent runs are billed against your own AI keys with per-run and per-month budget caps, and the site states that runs are priced before they start. Exact plan tiers are not published on the public site — teams should contact Skaftor for a quote.

- **Requirements & design generation:** Drop in a PRD; Skaftor surfaces open questions, drafts requirements with acceptance criteria you include or exclude line by line, and generates a technical design section by section, each tied to the requirements it covers.
- **Work order orchestration:** Work is split into pull-request-sized work orders, each carrying its repository, branch, service and acceptance criteria, ordered by dependency and confirmed by a human before an agent starts.
- **Multi-agent build on cloud or local:** Run Claude Code, Codex, Gemini or DeepSeek on a fresh Skaftor Cloud workstation, or use your own editor with context wired in over MCP, with cost visible as the run proceeds.
- **Gates and evidence:** CI and a clause check read each pull request against its acceptance criteria and can block a merge, while an AI review advises with a score and findings. Deployment gates are proposed from your own code and set per stage.
- **Organizational memory & audit trail:** The why stays attached to the code — requirement, design decision, pull request and approver — while an append-only audit trail records named-role approvals, RBAC, SSO/SAML, SCIM and cost visibility.

**Strengths:** Covers the whole AI-native delivery loop from PRD to canary deploy rather than one step; Gate evidence is tied to acceptance criteria, so 'done' is defined rather than asserted; Works with popular agents (Claude Code, Codex, Gemini, DeepSeek) and mainstream repos (GitHub, GitLab, Bitbucket); Append-only audit trail, RBAC and SSO/SAML/SCIM make it credible for regulated environments

**Limitations:** Aimed at teams; there is no obvious lightweight free tier for individuals; Setup and governance configuration are heavier than a single-purpose coding assistant; Public pricing tiers are not published, so costs require a sales conversation

[Profile (Markdown)](https://openaitools.app/tool/skaftor.md)

## Frequently Asked Questions

### How do Augment Code and Skaftor compare in monthly traffic?

Augment Code has 326,215 monthly visits, while Skaftor has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Augment Code has a month-over-month growth rate of +24.1%; Skaftor has 0%.

### How does pricing compare?

Augment Code: Freemium, Free Trial, Contact for Pricing. Freemium with a free tier for individual developers to start, plus paid team plans and enterprise/contact-for-pricing options. Enterprise deployment includes self-hosted and hybrid agent execution; exact seat and usage pricing is quoted by sales. Skaftor: Paid, Contact for Pricing. Skaftor is positioned as a paid enterprise platform (listed as Paid / contact for pricing). Agent runs are billed against your own AI keys with per-run and per-month budget caps, and the site states that runs are priced before they start. Exact plan tiers are not published on the public site — teams should contact Skaftor for a quote.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Offers powerful parallel agentic workflows and dedicated IDE tools, but with less focus on proprietary enterprise codebase context. | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 2 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Streamlines cloud-based full-stack app building and deployment from natural language, but less tailored for large legacy enterprise repos. | [.md](https://openaitools.app/tool/replit.md) |
| 3 | [Cursor](https://openaitools.app/tool/cursor-sh) | 4,790,129 | +6.5% | Freemium | Integrates directly into VS Code as a daily coding editor, but lacks enterprise-wide multi-agent SDLC orchestration. | [.md](https://openaitools.app/tool/cursor-sh.md) |
| 4 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | Focuses on spec-driven engineering and automated verification from AWS, whereas Augment targets broader multi-agent SDLC automation. | [.md](https://openaitools.app/tool/kiro.md) |
| 5 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Operates as a fully autonomous software engineer tackling complex tickets independently, whereas Augment focuses on developer-in-the-loop workflows. | [.md](https://openaitools.app/tool/devin.md) |
| 6 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | Delivers a terminal-first workflow optimized for open-weight models, but offers less graphical enterprise management tooling. | [.md](https://openaitools.app/tool/command-code.md) |
| 7 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder for custom AI agents and workflows | [.md](https://openaitools.app/tool/mindstudio.md) |
| 8 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Provides an open-source agent development environment running parallel CLI coding agents, but requires manual configuration and setup. | [.md](https://openaitools.app/tool/orca.md) |
| 9 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 10 | [Trae](https://openaitools.app/tool/trae) | 702,366 | -7.8% | Freemium | An AI IDE and coding agent that works on your project, not just your cursor | [.md](https://openaitools.app/tool/trae.md) |

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Source: https://openaitools.app/compare/augment-code-vs-skaftor

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