CodeNib

_{The Requests Wiki. Each node on the map is a page, and the heavy lines are references the code index recorded between areas. The page cites a file and line range for each claim.}

New in 0.2.6: Wikis open as a map of their pages and lead with the main path through the code, faster graph builds, and first C/C++ and JavaScript/TypeScript builds that leave the checkout alone. Read the release notes.

A Wiki you can follow down to the source

CodeNib indexes a repository, groups its code into areas, and writes a Wiki page for each one. The map and the call paths come from the code index, so you can check every arrow against the source.

• Start from the map. Pages are nodes. Drag to pan, scroll to zoom, and click a node to read its page. Click a heavy line to read an example of the references behind it.
• Follow one path through the code. The Overview opens on the main path through the repository, one sentence per recorded call. The most important detail pages draw their longest recorded call path. No model chooses the arrows.
• Check each claim. Sentences end with the file and line range they come from, and each page lists its callers and calls in the code graph.
• Ask a follow-up. Ask this repository answers a question with source citations, using the model you configure.

_{The gin Wiki opens on one recorded path, from GET() to node.insertChild().}

Open a Wiki

To build a Wiki with the map on your machine:

python -m pip install "codenib[graph]"
codenib wiki /path/to/your/repo --preset graph

This builds a search index and a symbol graph, then opens the Wiki at http://localhost:3000. Pages are written from the index without a model. Add --generate --model <provider/model> for model-written pages. Local Wiki guide

Use it with your coding agent

Build the same index for Claude Code or Codex. Your agent can then find definitions, follow callers and read the source in your own checkout.

_{One recorded Claude Code session on Requests: 14.1 s, 3 turns, 2 CodeNib tools. ▶ Watch it replay · Pinned source, transcript and setup details}

Requires Python 3.10+, Git, and Claude Code or Codex. Initialization accepts uncommitted edits and preserves the checkout.

python -m pip install "codenib[graph,mcp]"
codenib codegraph init /path/to/your/repo

Then ask your agent: “Use CodeNib's explore_context to find where request retry behavior is implemented. Cite the files and lines.”

This builds local search and a typed symbol graph, then connects installed agent clients. CodeNib needs no model, API key, or GPU of its own; your agent uses its own model. Language toolchain and project prerequisites vary.

In Claude Code you can install the plugin instead. It connects every Git checkout you open and adds /codenib:explain, /codenib:impact, /codenib:setup and /codenib:wiki:

claude plugin marketplace add sysevol-ai/CodeNib
claude plugin install codenib@codenib

Grok Build reads the same plugin, and DeepSeek Harness installs it as a bundle:

dsh plugin add "git+https://github.com/sysevol-ai/CodeNib.git#main&path:/plugins/dsh"

Grok Build setup · DeepSeek Harness setup

Setup and troubleshooting · Source exclusions · All MCP tools · Change guard (preview, Python: lists the tests a change reaches before your agent finishes)

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.

Languages

CodeNib registers 14 languages, 12 of them with a code graph.

These are registered capabilities, not the tools on your machine; codenib toolchain status shows those. The product currently reuses or rebuilds views; file-level delta repair is not enabled. The language matrix lists each backend and its prerequisites.

Results and reproductions

• #1 in line recall and Pass@1 on ContextBench's Agent systems leaderboard: 77.90% line recall and 388 of 500 tasks resolved (77.60% Pass@1), as of October 23, 2026 (UTC). This is our research agent, not the Wiki or the code graph: two Claude Haiku 5.5 workers search with glob, grep and reads, then Claude Opus 5.5 repairs. How it works · Scope and evidence
• 71.4% code-block Recall@5 on 100 real issues with model-planned grep → Jev, 12.8 percentage points above the same grep candidates without reranking. This is an experimental retrieval route, separate from the model-free CodeGraph. Method and limitations

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:

@misc{yu2026codenibmultiviewdataserving,
      title={CodeNib: A Multi-View Data System for Serving Repository Context to Coding Agents},
      author={Zhongming Yu and Hengjia Yu and Boqin Yuan and Shuting Zhao and Yizhao Chen and Aryan Dokania and Mihir Jagtap and Jiayu Chang and Yitong Ma and Yash Jayswal and Wentao Ni and Hejia Zhang and Zhaoling Chen and Gangda Deng and Jishen Zhao},
      year={2026},
      eprint={2607.25431},
      archivePrefix={arXiv},
      primaryClass={cs.SE},
      url={https://arxiv.org/abs/2607.25431},
}

CodeNib is licensed under Apache 2.0.