* feat(agent-core): align model-facing prompts with actual tool behavior
A hunk-by-hunk accuracy pass over every model-visible prompt surface
(system.md, tool .md descriptions, zod describes, profile role prompts,
and injected reminder strings), with each claim verified against the
implementation and, where possible, empirically (ripgrep semantics).
Fix descriptions that drifted from the code:
- Grep `glob` matches against each file's absolute path, so
`src/**/*.ts` silently matches nothing — document the working forms
- Glob `path` accepts relative paths; results are files-only
- FetchURL no longer promises a content-type-to-mode mapping the
default provider does not honor
- cron: a pinned-date 5-field expression repeats yearly unless
`recurring: false`; drop a bench-only env knob from cron-list
- skill `args` expansion covers $NAME/$1/$ARGUMENTS and the trailing
ARGUMENTS: line; goal reminder no longer cites a nonexistent
developer-message channel
Disclose enforced-but-silent behavior:
- cron fires deliver only while the session is idle; expressions with
no fire within 5 years are rejected at create time
- VCS metadata directories are always excluded from Glob/Grep, even
with include_ignored; sensitive-file guard exemptions
(.env.example/.env.sample/.env.template, public SSH keys)
- large images may be downsampled while the <system> block reports
original dimensions; subagent summaries under the length floor are
sent back for expansion; background-disabled Agent calls are
rejected before launch; AGENTS.md beyond ~32 KB triggers a
performance warning (surfaced in the /init prompt)
Resolve cross-surface contradictions:
- AskUserQuestion background describe/envelope no longer teach polling
- AgentSwarm subagent_type documents that resume keeps original types
- bash.md scopes &&-chaining to dependent commands and steers
independent read-only commands to parallel calls
- the shared system prompt no longer names tools that read-only
subagent profiles lack
Add missing guidance:
- denied/rejected tool calls mean the user declined that action —
adjust, don't retry or route around (root agent)
- plan subagent now knows it is read-only; coder subagent knows its
final message is the entire handoff; explore subagent knows web
tools are in scope
- gh CLI routing for GitHub-hosted work; FetchURL login-wall note;
a dual-use content-safety boundary; scope discipline,
surrounding-idiom, and dependency-verification norms; file:line
citation convention; progress notes on long multi-phase tasks
* fix(agent-core): let the model fetch a background answer after the completion notice
In sessions with background persistence (any agent with a homedir), a
background question's answer is flushed to output.log and the completion
notification carries an <output-file> pointer, not the answer text. The
previous envelope wording ("use TaskOutput only to re-read the answer if
you missed the notification") gated the normal post-completion fetch
behind a missed-notification condition, so a model could acknowledge the
notice and continue without ever reading the user's answer.
Reword the envelope to state that the completion notice may carry a
pointer and to direct the model to read that file (or call TaskOutput
once) for the answer, while still forbidding polling before the user
responds. Align the background param describe the same way ("notified
automatically" rather than "the answer arrives", polling scoped to the
pending window).
* fix
|
||
|---|---|---|
| .agents/skills | ||
| .changeset | ||
| .github | ||
| apps | ||
| build | ||
| docs | ||
| packages | ||
| plan | ||
| plugins | ||
| scripts | ||
| .editorconfig | ||
| .gitattributes | ||
| .gitignore | ||
| .npmrc | ||
| .nvmrc | ||
| .oxfmtrc.json | ||
| .oxlintrc.json | ||
| AGENTS.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.
