by banteg · Codex Skill · ★ 166
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
bn is a coding agent-first CLI for Binary Ninja. It gives a shell session or tool-calling agent stable commands, structured output, and access to the same live Binary Ninja database you already have open in the GUI. Headline Features Query live Binary Ninja state from the shell: targets, functions, callsites, decompile text, IL, disassembly, xrefs, types, strings, imports, and reusable bundles. Execute Python inside the Binary Ninja process instead of maintaining a separate headless workflow. Apply mutations with , capture decompile diffs, and verify the live post-state before reporting success. Emit structured or output, auto-spill large results to files, and return token counts so agents can budget context intelligently. Install Recommended setup: install the CLI, the Binary Ninja companion plugin, and the bundled Codex skill. Install the CLI on your PATH: Install the Binary Ninja companion plugin: That links into your Binary Ninja plugins directory. Install the bundled Codex skill: That symlinks into by default. Use if you want a standalone copy instead. Restart Codex to pick up a new or renamed skill. If the plugin code changes, reload Binary Ninja Pytho
| Stars | 166 |
| Forks | 12 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 67.6694659521302/100 |
| Last Updated | 2026-05-06 |
| Created | 2026-03-08 |
| Platforms | cli, codex, python |
| Est. Tokens | ~10k |
These tools work well together with bn for enhanced workflows:
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bn is binary ninja cli for coding agents. It is categorized as a Codex Skill with 166 GitHub stars.
bn is primarily written in Python. It covers topics such as agents, binary-ninja, codex.
You can find installation instructions and usage details in the bn GitHub repository at github.com/banteg/bn. The project has 166 stars and 12 forks, indicating an active community.
The top alternatives to bn on Agent Skills Hub include unbrowse, perplexity-web-api-mcp, context-space. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.