
CodeNib
ai.codenib由 codenib.ai 發布v0.2.5更新於 Nov 4, 2026
Source-linked CodeGraph exploration, ranked search, and static navigation for coding agents.
概覽
CodeNib 為程式碼倉庫建立本機、可追溯至原始碼的程式碼圖譜,讓編碼助理能檢索排序後的程式碼脈絡並跳轉定義與參照。
- 可以做什麼
- 檢索附檔案與行號參照的有限範圍程式碼脈絡
- 跳轉定義與靜態參照,包含傳入與傳出關係
- 一次呼叫取得相依子圖,深度最多 8 層
- 為多種語言建立索引,圖後端涵蓋 Python、Go、Rust、C/C++、C#、Java、Ruby、PHP、Kotlin、Scala、JavaScript 與 TypeScript
- 匯出附原始碼引用的倉庫 Wiki
- 適用情境
- 適合編碼助理在較大的多語言倉庫中定位某段行為的實作位置,並沿呼叫路徑追蹤超過一跳的關係,而不只依賴 grep 與逐一讀檔。對已在本機檢出程式碼上使用 Claude Code 或 Codex 的團隊最有用。
- 執行需求
- 以 stdio 在本機執行,需要 Python 3.10+、Git,以及 Claude Code 或 Codex。從 PyPI 安裝 codenib 的 graph 與 mcp 附加元件,再對每個倉庫執行 codegraph init 初始化。核心 CodeGraph 路徑不需要模型、API 金鑰或 GPU;各語言工具鏈與前置條件不同。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 CodeNib,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
Find the right code. Follow its references.
Give Claude Code and Codex source context and typed graph navigation across languages.
71.4% code-block Recall@5 on 100 real issues.
Model-planned grep → Jev: +12.8 percentage points over the same grep candidates without reranking.
Experimental result · Method and limitations
Use with your agent · Browse a Wiki · Languages · Reproductions · Releases
[CI] [PyPI version] [Latest GitHub Release] [arXiv paper] [Hugging Face: #1 Paper of the Day] [Apache 2.0 license]
▶ Watch the 15-second replay · real CLI output · waits condensed · Pinned source, transcript and setup details.
New in 0.2.5: saved repository Wikis and portable OKF export, Pyrefly-backed Python graphs, static entry-path navigation and call-path rule checks. Read the release notes.
Quickstart
Requires Python 3.10+, Git, and Claude Code or Codex. Initialization accepts uncommitted edits and preserves the checkout.
Then ask your agent: “Use CodeNib's explore_context to find where request
retry behavior is implemented. Cite the files and lines.”
This shipping path builds local search and a typed symbol graph, then connects installed agent clients. It needs no model, API key, or GPU for CodeNib; your agent uses its own model. It is separate from the grep/Jev experiment above. Language toolchain and project prerequisites vary.
Setup and troubleshooting · Source exclusions · All MCP tools · Local Wiki
Why CodeNib
- Inspect the evidence. Retrieve bounded code context with file and line references, then navigate definitions and static references. Read the source at each reference before describing a call path.
- Use the same tools across languages. The registry tracks 14 language entries, including 12 with graph backends. Check capability and setup differences in the language matrix.
- Compare methods on the same source. Pinned agent contracts, datasets, and scorer checks make the reproduction surface inspectable.
- Share what you found. Export a Wiki with source citations to your own GitHub Pages, or browse the public examples.
How it compares
What an agent can ask each tool. Peer interfaces were checked against upstream docs on 2026-09-28. This compares capabilities, not benchmark scores.
CodeNib's indexed references can include calls, fields, type uses and function values. Inspect the source to establish which references invoke a function; external and dynamic relationships may be missing. For a known string or file, your agent's native search and reads remain useful. Include indexing and rebuild costs when assessing graph navigation on your own tasks.
None of these repository tools needs its own model or API key; your agent uses its own model. Detailed comparison, sources and boundaries. CodeNib also includes an optional grep → Jev route using OpenRouter for planning and reranking; selected code goes to remote models. Authorization previews remain opt-in. The historical research result above is separate from the product evaluation and the model-free CodeGraph row.
Languages
Graph backends: Python, Go, Rust, C/C++, C#, Java, Ruby, PHP, Kotlin, Scala, JavaScript, and TypeScript. Swift and Lua support chunking/retrieval. Provider prerequisites and coverage differ by language.
The generated language matrix separates chunking, graph backends, incremental-backend support, and decoder parity. The product currently reuses or rebuilds views; file-level delta repair is not enabled.
Results and reproductions
Documentation and community
Documentation · Architecture · Contributing · CI and testing · Changelog · Discord
CodeNib is in beta; public interfaces may change before a stable release. Historical research artifacts retain their published dataset identifiers.
Citation
If you use CodeNib in your research, please cite our arXiv paper:
CodeNib is licensed under Apache 2.0.
來源:README.md,提交 35f2fea
工具
0版本歷史
3- v0.2.5最新Nov 4, 2026
- v0.2.4Sep 27, 2026
- v0.2.3Sep 16, 2026
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