* feat(agent-core): feed AskUserQuestion answers back as question text and option labels
The flattened answers record the model receives was keyed by synthesized
ids (q_0 / opt_0_1), forcing a cross-message positional lookup against the
original tool call to understand what the user picked — both unreadable in
transcripts and a real model-misreads-the-choice badcase.
- toAgentCoreResponse now takes the original broker request and translates
wire ids back to question text (keys) and option labels (values);
unknown ids are kept verbatim, missing request falls back to raw ids
- wire protocol unchanged: clients still answer with option ids; the
resolve route reads the pending request before settling it
- question texts must be unique per call and option labels unique per
question, enforced in the tool execution path (AJV cannot express the
zod refine) and mirrored on the exported schemas
- web transcript card resolves both the new label form and legacy id
transcripts; TUI and ACP paths already produced the text form
* fix(agent-core): align multi-select answer join across clients and harden question schema
- Join multi-select labels with ', ' in the server translator, matching
what the TUI reverse-RPC path already emits, so the model sees one
format regardless of which client answered
- Trim segments in the web transcript resolver before label matching:
TUI-answered multi-select transcripts (', '-joined) previously lost
their highlight to a spurious leading-space Other row
- Move the question-text/legacy-q_<i> answer lookup out of the SFC into
askUserToolParse as answerFor(), per that module's testability intent
- Require non-empty question text and option labels (.min(1)) so empty
strings are rejected by AJV at the tool boundary instead of failing
deeper in the protocol layer
* fix(agent-core): resolve option ids only within the answered question
The translator's option-id lookup was a single flat map across all
questions, so a stale or malformed response pairing one question with
another question's option id (q_1 + opt_0_0) was silently translated
into a label that was never offered for that question. Scope the lookup
to the answered question's own options; cross-question and unknown ids
now both pass through verbatim, staying diagnosable.
|
||
|---|---|---|
| .agents/skills | ||
| .changeset | ||
| .github | ||
| apps | ||
| build | ||
| docs | ||
| packages | ||
| plugins | ||
| scripts | ||
| .editorconfig | ||
| .gitattributes | ||
| .gitignore | ||
| .npmrc | ||
| .nvmrc | ||
| .oxfmtrc.json | ||
| .oxlintrc.json | ||
| AGENTS.md | ||
| CLAUDE.md | ||
| composer-toolbar-designs.html | ||
| CONTRIBUTING.md | ||
| flake.lock | ||
| flake.nix | ||
| HANDOVER-kimi-web-table-width.md | ||
| LICENSE | ||
| Makefile | ||
| package.json | ||
| pnpm-lock.yaml | ||
| pnpm-workspace.yaml | ||
| README.md | ||
| README.zh-CN.md | ||
| SECURITY.md | ||
| tsconfig.json | ||
| vitest.config.ts | ||
Kimi Code CLI
Documentation · Issues · 中文
What is Kimi Code CLI
Kimi Code CLI is an AI coding agent that runs in your terminal — it can read and edit code, run shell commands, search files, fetch web pages, and choose the next step based on the feedback it receives. It works out of the box with Moonshot AI’s Kimi models and can also be configured to use other compatible providers.
Install
Install with the official script. No Node.js required.
- macOS or Linux:
curl -fsSL https://code.kimi.com/kimi-code/install.sh | bash
- Homebrew (macOS/Linux):
brew install kimi-code
- Windows (PowerShell):
irm https://code.kimi.com/kimi-code/install.ps1 | iex
On Windows, install Git for Windows before first launch because Kimi Code CLI uses the bundled Git Bash as its shell environment. If Git Bash is installed in a custom location, set
KIMI_SHELL_PATHto the absolute path ofbash.exe.
Then, run it with a new shell session:
kimi --version
For npm install, upgrade, uninstall, see Getting Started.
Quick Start
Open a project and start the interactive UI:
cd your-project
kimi
On first launch, run /login inside Kimi Code CLI and choose either Kimi Code OAuth or a Moonshot AI Open Platform API key. After login, try your first task:
Take a look at this project and explain its main directories.
Key Features
- Single-binary distribution. Install with one command: no Node.js setup, PATH gymnastics, or global module conflicts.
- Blazing-fast startup. The TUI is ready in milliseconds, so starting a session never feels heavy.
- Purpose-built TUI. A carefully tuned interface, optimized end to end for long, focused agent sessions.
- Video input. Drop a screen recording or demo clip into the chat and let the agent watch what is hard to describe in words — turn a reference clip into a LUT, a long video into a short, a screen recording into working code, and more.
- AI-native MCP configuration. Add, edit, and authenticate Model Context Protocol servers conversationally with
/mcp-config, without hand-editing JSON. - Rich plugin ecosystem. Install skills, MCP servers, and data sources from the marketplace or any GitHub repo, with each install's trust level surfaced up front.
- Subagents for focused, parallel work. Dispatch built-in
coder,explore, andplansubagents in isolated contexts while keeping the main conversation clean. - Lifecycle hooks. Run local commands at key points to gate risky tool calls, audit decisions, trigger desktop notifications, or connect to your own automation.
- Editor & IDE integration (ACP). Drive a Kimi Code CLI session straight from Zed, JetBrains, or any Agent Client Protocol client with
kimi acp.
Use it in your editor (ACP)
Kimi Code CLI speaks the Agent Client Protocol, so ACP-compatible editors and IDEs (Zed, JetBrains, …) can drive a session over stdio. Log in once, then point your editor at the kimi acp subcommand — no extra login needed.
For Zed, add this to ~/.config/zed/settings.json:
{
"agent_servers": {
"Kimi Code CLI": {
"type": "custom",
"command": "kimi",
"args": ["acp"],
"env": {}
}
}
}
Then open a new conversation in Zed's Agent panel. See Using in IDEs for JetBrains setup and troubleshooting, and the kimi acp reference for the full capability matrix.
Docs
- Getting Started
- Interaction and approvals
- Sessions
- Using in IDEs (ACP)
- Configuration
- Command reference
Develop
Requirements: Node.js ≥ 24.15.0, pnpm 10.33.0.
git clone https://github.com/MoonshotAI/kimi-code.git
cd kimi-code
pnpm install
pnpm dev:cli # run the CLI in dev mode
pnpm test # run tests
pnpm typecheck # TypeScript check
pnpm lint # oxlint
pnpm build # build all packages
See CONTRIBUTING.md for the full contribution guide.
Community
- Issues
- For security vulnerabilities, see SECURITY.md.
Acknowledgements
Our TUI is built on top of pi-tui. We thank the authors of pi-tui for their valuable work.
License
Released under the MIT License.
