Codebuff
Basic information
Website: https://web.archive.org/web/20241125222625/https://www.codebuff.com/
Short description: Codebuff is a command-line interface (CLI) tool that automates code writing by acting as a coding agent within your terminal. It uses natural language commands to execute tasks such as installing packages, running tests, analyzing your codebase, and streamlining development workflows efficiently [source]
Intended uses: What does the developer say it’s for? It’s intended to assist in various coding tasks, including building features, writing unit tests, refactoring code, creating scripts, and providing advice, all while understanding the entire codebase context. The developers emphasize that Codebuff allows users to focus more on high-level architecture and design rather than implementation details, potentially increasing productivity and creativity in software development [source].
Date(s) deployed: November 7, 2024 [source]
Developer
Website: https://web.archive.org/web/20241125222625/https://www.codebuff.com/
Legal name: Codebuff, Inc [source]; Manicode (old name; [source])
Entity type: Corporation
Country (location of developer or first author’s first affiliation): Incorporation: Delaware, USA (Manicode Inc. 5231734) [source]
Safety policies: What safety and/or responsibility policies are in place? Unknown
System components
Backend model: What model(s) are used to power the system? Uses Claude 3.5 Sonnet for coding and Haiku for file search. Also, uses a combination of Claude 3.5 Sonnet and GPT-4o-mini to rewrite files with an intended edit [source]
Publicly available model specification: Is there formal documentation on the system’s intended uses and how it is designed to behave in them? None
Reasoning, planning, and memory implementation: How does the system ‘think’? Codebuff’s works by first analyzing and caching the entire codebase structure using Claude Haiku 3.5. When processing user requests, it uses this cached context to quickly understand the relevant code. The system then employs Claude 3.5 Sonnet to select files and generate edits, while combining it with GPT-4o-mini for efficient code patching [source].
Observation space: What is the system able to observe while ‘thinking’? Codebuff observes the entire codebase structure, file contents, project-specific knowledge to make decisions and code [source]
Action space/tools: What direct actions can the system take? Codebuff can parse a codebase, edit files, generate new code, and execute terminal commands [source]
User interface: How do users interact with the system? Users interact with Codebuff through a command-line interface in their terminal, typing natural language instructions to request code changes, which Codebuff then processes and executes across the codebase [source]
Development cost and compute: What is known about the development costs? Unknown
Guardrails and oversight
Accessibility of components:
- Weights: Are model parameters available? N/A; backends external model(s) via API
- Data: Is data available? N/A; backends external model(s) via API
- Code: Is code available? Closed source
- Scaffolding: Is system scaffolding available? Closed source
- Documentation: Is documentation available? Available [source]
Controls and guardrails: What notable methods are used to protect against harmful actions? Unknown
Customer and usage restrictions: Are there know-your-customer measures or other restrictions on customers? None
Monitoring and shutdown procedures: Are there any notable methods or protocols that allow for the system to be shut down if it is observed to behave harmfully? The user can type ‘undo’ to remove edits [source]
Evaluation
Notable benchmark evaluations: N/A; backends external model(s) via API
Bespoke testing: Demo [source]
Safety: Have safety evaluations been conducted by the developers? What were the results? None
Publicly reported external red-teaming or comparable auditing:
- Personnel: Who were the red-teamers/auditors? None
- Scope, scale, access, and methods: What access did red-teamers/auditors have and what actions did they take? None
- Findings: What did the red-teamers/auditors conclude? None
Ecosystem information
Interoperability with other systems: What tools or integrations are available? Codebuff integrates with any development environment, including VSCode, Vim, Emacs, Replit, or plain text editors. It also autonomously utilizes existing tools, scripts, and packages (e.g., terminal commands, package managers like pip) without requiring explicit user approval [source]
Usage statistics and patterns: Are there any notable observations about usage? Only detailed usage in a post when Codebuff was first launched — “The day after our Hacker News launch was our biggest yet, with >700 million tokens burned!” [source]
Additional notes
None