FuXi Terminal AI Coding Agent
Fast, self-contained AI coding agent in your terminal with cost-aware model routing.
Evidence shows permission modes (default/plan/bypassPermissions), --auto classifier-gated, --dangerously-skip-permissions warning, audit logging, AST safety classifier, rollback/checkpoints, update checksum verification. However, implementation details are missing; permission granularity, user confirmation flow, data flow transparency, sensitive data handling (e.g., key storage) are not detailed. Dependency security has no evidence (no dependency manifest or vulnerability scan). External effects (shell commands, network updates) are mentioned but without specific controls. Rollback has checkpoints but no detailed mechanism. Source attribution has copyright notice but no contributor guidelines.
Self-consistency: README description aligns with docs, but no code verification. Dependency availability: no dependency manifest or third-party library info, cannot assess. Failure messages: fuxi doctor and verify commands exist, but no specific error handling examples.
Audience clear (developers, terminal users), scenarios diverse (code editing, command running, tool driving). Capability boundaries have tool list and permission modes, but not explicit limits. Trigger precision: slash commands and CLI flags exist, but no detailed trigger conditions. Environment fit: supports multiple platforms (macOS/Linux/Windows), environment variable configuration.
Information architecture clear (README TOC, docs folder). Install notes detailed (curl, PowerShell, CMD). Naming stability: version numbers but no API stability promise. Examples and FAQ exist (docs/faq.md). Known limitations: only mentions benchmark is self-run small-scale, no other limitations. License: proprietary, but no standard license identifier. Versioning changelog exists (CHANGELOG.md). Maintenance responsibility: SECURITY.md and SUPPORT.md exist, but no explicit maintainers.
Output usability: TUI and CLI exist, but no specific output format examples. Marginal value: cost-aware routing, multi-provider support, but no independent verification. Cost-benefit: /cost and /usage commands exist, but no specific cost data.
Claim traceability: benchmark report and doc links exist, but no specific data. Cross-source corroboration: no third-party verification. Fact-inference separation: README distinguishes claims and benchmarks, but some claims lack evidence.
- Repository contains only documentation and benchmarks; product source code is not published, so actual implementation cannot be verified.
- License is proprietary with no standard license identifier, which may affect compliance.
- No evidence of dependency security, supply chain risk cannot be assessed.
- Benchmark is self-run, not third-party independent verification, results may be biased.
What does this agent do, and when should you use it?
FuXi is a terminal-first AI coding agent built in Go, shipped as a single static binary with no runtime dependencies. It provides a Think → Act → Verify agentic loop and supports multiple providers including OpenAI-compatible, Gemini, Bedrock/Vertex, with cost-aware routing and automatic failover. It includes 50+ built-in tools for file operations, shell, ripgrep search, LSP diagnostics, Jupyter, browser use, and parallel sub-agents. Safety guardrails include an AST safety classifier and fine-grained permissions. Sessions and memory persist to disk, with checkpoints and automatic compaction. It is extensible as an MCP client with hooks, skills, plugins, and slash commands. Installation is via scripts, and a wide range of commands are available in the `fuxi` CLI. The product is proprietary; source code is not public.
FuXi reads and edits code files, executes shell commands via bash or PowerShell, uses ripgrep for search, fetches web pages with web fetch, uses LSP diagnostics, runs Jupyter notebooks, drives browsers through tools, manages background tasks, and launches parallel sub-agents. It interacts with OpenAI-compatible APIs through built-in tools and MCP servers. The agent loop includes thinking, acting, and verification steps, with cost-aware routing and automatic failover. It generates configuration via fuxi init, checks environment with fuxi doctor and fuxi verify, authenticates via fuxi login, and proxies binaries via fuxi proxy. Session transcripts persist to disk, allowing resume, rollback, or forking.
- A developer wants to fix failing tests in a project by instructing the agent in natural language, letting it edit code and run the test suite.
- An engineer prefers to use different LLM providers from a single interface and automatically route requests based on cost.
- A user with MCP servers wants to interact with their tools through an agent that supports MCP.
- Teams in security-sensitive environments require command classification and permission controls to manage autonomous operations.
- Users working on long sessions want to retain context across sessions, with checkpoints and automatic compaction.
- A team wants to integrate a terminal agent in CI environments, using
setup-tokenfor headless authentication.
What are this agent's strengths and limitations?
- Offers 50+ built-in tools covering file ops, shell, search, LSP, browser, and Jupyter.
- Cost-aware routing and automatic failover leverage multiple providers efficiently.
- Safety guardrails like AST classifier and fine-grained permissions enhance secure autonomous operation.
- Single static binary with no runtime dependencies simplifies deployment.
- Proprietary license; source code unavailable, limiting modification and forking.
- No scores on third-party benchmarks like SWE-bench, requiring self-evaluation.
- Benchmarks are self-run task sets, not third-party validated, so treat cautiously.
- No explicit documentation on required API keys or specific provider setup steps; users must infer from config examples.
How do you install or deploy this agent?
curl -fsSL https://fuxicode.com/install.sh | bash # macOS / Linux
irm https://fuxicode.com/install.ps1 | iex # Windows PowerShellVerify with fuxi --version and fuxi doctor.
How do you use this agent?
First configure a model: run fuxi wizard or edit ~/.fuxi/config.yaml. Launch the TUI with fuxi. Use slash commands like /model, /compact, /cost within a session. Run fuxi doctor for environment checks, fuxi verify to test connection, and fuxi update for updates. Full guide: docs/usage.md.
How does this agent compare with similar options?
FuXi positions itself as a provider-agnostic alternative to Claude Code, offering a Think → Act → Verify loop and cost routing.
FAQ
Is FuXi free to use?
Do I need a specific API key?
fuxi login to use FuXi-managed models.How does FuXi handle permissions and security?
What happens if a provider goes down?
What if my session context is full?
/compact command to compress conversation history, or rely on automatic compaction to save tokens.