| 能力 | Codna | 纯智能体工具（Cursor、Copilot、Devin） | 静态代码搜索 |
|---|---|---|---|
| 仓库理解 | 确定性图 · 0 token | 模型读文件 | 关键词 / AST |
| 修复前的 token | 0 | 模型上下文 | 0 |
| 缺陷定位 | 图 + 证据 | 提示词探索 | 手动 |
| 修复附带 | 根因 · 置信度 · 风险 | 不一 | 无 |
| 补丁生成 | 智能体 · 限定上下文 | 智能体 · 宽泛上下文 | 无 |
| 每个已验证修复的模型成本 | 平均约 $0.02 · 87 个案例 | 不一 | — |
| PR 审查与修复 PR | App · Action · CLI | 不一 | 无 |
| 隐私模式 | 你的机器 + 你的密钥 | 不一 | 本地 |
Head-to-head
Compare Codna directly.
Codna vs Codex CLI →
The Codex CLI is an agent you drive from the terminal. Codna understands the repository first, for zero tokens, then fixes from evidence and explains the result.
Codna vs Gemini CLI →
The Gemini CLI is an agent you drive from the terminal. Codna maps the repository first, for zero tokens, then fixes from evidence with root cause and risk attached.
Codna vs Cursor →
On 87 matched bug-fix cases, Codna used 5× fewer tokens and ran 1.7× faster than Cursor. Both verified 87 of 87. Codna also runs inside Cursor as an MCP server.
Codna vs Claude Code →
Claude Code is an agent. Codna is the understanding it works from: a deterministic map for zero tokens, an evidence bundle scoped to the issue, and a fix that explains itself. It plugs in over MCP.
Codna vs Devin →
Devin is an autonomous agent. Codna is a deterministic understanding layer with a scoped agent behind it: zero tokens to map, a fix that explains itself, and a pull request you merge.
Codna vs Windsurf →
Windsurf is an agentic editor. Codna maps the repository deterministically for zero tokens, fixes from evidence, and reports root cause, confidence and regression risk on every fix.
Codna vs Augment Code →
Augment Code is an AI coding platform. Codna is a deterministic understanding layer with a scoped agent: zero tokens to map, evidence instead of the whole repo, and a fix that explains itself.
Codna vs Sourcegraph Amp / Cody →
Amp and Cody are coding agents with code search behind them. Codna maps the repository deterministically for zero tokens, fixes from evidence, and reports root cause, confidence and regression risk.
Codna vs Greptile →
Greptile is a pull request review tool. Codna reviews every pull request with severity, confidence and a clear verdict, and opens the fix when you ask.
Codna vs CodeRabbit →
CodeRabbit is a pull request review tool. Codna reviews every pull request with a clear verdict and opens the fix when you ask, from the same deterministic map it uses to fix bugs.
Codna vs Aider →
Aider is a pair programmer in the terminal. Codna is a deterministic understanding layer with a scoped agent: zero tokens to map, a fix that explains itself, and a pull request you review.
常见问题
大多数工具通过模型读你的代码库。Codna 以零 token 确定性地绘制仓库地图，然后把限定在 issue 范围内的证据包交给智能体。在 87 个配对案例中对比 Cursor，这意味着 token 少 5 倍、速度快 1.7 倍，87 个修复中 87 个通过验证。
自主智能体用模型自身探索代码库。Codna 把理解和修复分开：确定性引擎先构建依赖与影响范围图，然后智能体只凭证据修复，并报告根因、置信度和回归风险。
在基准测试中，只有修复通过验证的案例才计入：Codna 是 87 个中的 87 个。在你的机器上，codna fix --tests --apply 在沙箱中运行你的测试并反复修复直到通过。每条写入路径都先经过风险闸门。
理解在你的机器上运行。只有证据包或 diff 会通过你的密钥送达模型提供商。在 codna.yaml 中把 privacy.egress 设为 fail-closed，Codna 就只在内核级网络拒绝之下运行你的测试。除非你选择加入，你的代码不会被用于训练模型。
仓库地图基于导入模式构建，因此不绑定某一种语言。设备端回忆覆盖 Python、JavaScript、TypeScript、Go、Rust、Java、C、C++、C#、PHP 和 Ruby。你自己的测试命令验证修复。
在 87 个测量案例中，每个已验证修复的模型花费平均约 $0.02。用你自己的密钥时直接向提供商付费；CLI 本身在你的机器上免费。