# Skaftor vs Trae

Skaftor records 0 monthly visits with 0% month-over-month growth and Paid, Contact for Pricing pricing. Trae records 702,366 monthly visits with -7.8% growth and Freemium pricing.

| Metric | [Skaftor](https://openaitools.app/tool/skaftor) | [Trae](https://openaitools.app/tool/trae) |
| :--- | :--- | :--- |
| Website URL | https://skaftor.com | https://www.trae.ai |
| Categories | AI Workflow, AI Agent, AI Developer Tools, AI Project Management | AI Code Assistant, AI Code Generator, AI Agent, AI Developer Tools |
| Pricing Model | Paid, Contact for Pricing | Freemium |
| Monthly Visits | 0 | 702,366 |
| MoM Growth Rate | 0% | -7.8% |
| Primary Market | Global | China |
| Direct Visits | 0 | 373,236 |
| Review Score | 4.4 | 4.7 |
| Saved Count | 0 | 6 |
| Supported Platforms | Website | Website |

## 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)

## Trae

Trae is an AI development platform that puts a coding agent at the centre of the editing experience. Its main product, TraeCode, is a full IDE with an integrated AI panel: instead of merely completing the next line, the assistant can inspect your project, reason about the change you want, edit several files at once, and run commands to verify the result. The diff-based review flow keeps you in charge of what is applied.

The stated positioning is "Collaborate with Intelligence" — the assistant works alongside you rather than replacing the editor. Practical uses include generating boilerplate and new modules, refactoring messy code, explaining an unfamiliar repository, fixing failing tests, and translating a plain-language task into working changes. Because the agent has project context, results tend to be more coherent across a codebase than single-file completion.

Alongside TraeCode, TraeWork applies the same assistant model to general work tasks, so the platform covers both engineering and everyday productivity. Trae ships as a desktop download and can also be used in the browser, making it easy to adopt without disrupting a whole toolchain.

**Pricing & Plans:** Free to start, with paid upgrades that increase usage limits for premium models; enterprises can purchase through BytePlus. Usage is measured per AI request and varies by model, so heavy users should review the pricing page for current allowances before committing.

- **Project-aware code context:** Trae reads your project files and dependencies, so its suggestions account for how the codebase is actually structured rather than treating each file in isolation.
- **Agentic code generation and edits:** Describe a task and the agent plans and applies multi-file edits, shows a diff for review, and can run terminal commands as part of the change.
- **Debugging and code explanation:** Ask questions about unfamiliar code, get inline explanations, and have bugs or failing tests diagnosed and fixed with context.
- **TraeCode plus TraeWork:** TraeCode covers the coding workflow, while TraeWork applies an AI assistant to everyday knowledge tasks — both download for desktop, with a web option.
- **Free start with upgradable limits:** You can try it for free and scale up by choosing the plan that raises your usage limits, with enterprise options available.

**Strengths:** Free tier makes it easy to evaluate before paying; Agentic workflow handles multi-file changes and tests, not just autocomplete; Deep project context improves the relevance of suggestions; Covers both coding (TraeCode) and general work (TraeWork)

**Limitations:** Heavy usage of premium models quickly hits plan limits; It is a newer entrant, so some integrations and plugins are still maturing; Most of the polish is in the coding flow; other workflows are less developed; Usage-based limits can be confusing to predict for large teams

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

## Frequently Asked Questions

### How do Skaftor and Trae compare in monthly traffic?

Skaftor has 0 monthly visits, while Trae has 702,366. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Skaftor has a month-over-month growth rate of 0%; Trae has -7.8%.

### How does pricing compare?

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. Trae: Freemium. Free to start, with paid upgrades that increase usage limits for premium models; enterprises can purchase through BytePlus. Usage is measured per AI request and varies by model, so heavy users should review the pricing page for current allowances before committing.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Claude](https://openaitools.app/tool/claude-2) | 1,253,439,413 | +23.8% | Freemium | Anthropic's frontier AI workspace powered by Claude 5.5 for agentic coding, analysis, and nuanced writing. | [.md](https://openaitools.app/tool/claude-2.md) |
| 2 | [Cursor](https://openaitools.app/tool/cursor) | 23,297,751 | +8.4% | Freemium | Offers much deeper IDE integration and superior multi-file editing, but requires a paid subscription for full features. | [.md](https://openaitools.app/tool/cursor.md) |
| 3 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Google's agent-first development platform for building and shipping software with AI agents | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 4 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Excels at instant browser-based cloud deployment and full-stack app generation, but is less suited for heavy local multi-repo workflows. | [.md](https://openaitools.app/tool/replit.md) |
| 5 | [VS Code](https://openaitools.app/tool/vs-code) | 7,397,370 | -3.8% | Freemium | Provides ultimate extensibility and open-source flexibility, but requires assembling your own extension stack to match Trae's native AI features. | [.md](https://openaitools.app/tool/vs-code.md) |
| 6 | [Qoder](https://openaitools.app/tool/qoder) | 5,145,040 | +81.8% | Freemium, Free Trial, Free | Provides powerful codebase-wide agentic planning and completion, but operates primarily as a plugin rather than a dedicated IDE. | [.md](https://openaitools.app/tool/qoder.md) |
| 7 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | Uses rigorous spec-driven engineering plans to verify changes, though with a more structured and rigid workflow than Trae. | [.md](https://openaitools.app/tool/kiro.md) |
| 8 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Operates as a fully autonomous software engineer that opens pull requests, but is much more expensive and task-oriented. | [.md](https://openaitools.app/tool/devin.md) |
| 9 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | Focuses on terminal-first workflows with open-weight models, but lacks the graphical multi-file interface of Trae. | [.md](https://openaitools.app/tool/command-code.md) |
| 10 | [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) |

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Source: https://openaitools.app/compare/skaftor-vs-trae

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