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Agent Skill · 开发

openclaw-kirocli-coding-agent(OpenClaw kirocli coding Agent CLI)

openclaw-kirocli-coding-agent 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

openclaw-kirocli-coding-agent 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 1,062。

总安装 41,748周安装 1,775GitHub Stars 公开资料未说明下载 14,626核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.5.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-kirocli-coding-agent(OpenClaw kirocli coding Agent CLI)
来源仓库:https://github.com/dandysuper/openclaw-kirocli-coding-agent
安装命令:
openclaw skills install openclaw-kirocli-coding-agent
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install openclaw-kirocli-coding-agent

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

通过后台进程运行 Codex CLI、Claude Code、Kiro CLI、OpenCode 或 Pi Coding Agent 以进行编程控制。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install openclaw-kirocli-coding-agent;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openclaw-kirocli-coding-agent 怎么安装?

在终端执行 openclaw skills install openclaw-kirocli-coding-agent。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openclaw-kirocli-coding-agent 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openclaw-kirocli-coding-agent 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install openclaw-kirocli-coding-agent 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

openclaw-kirocli-coding-agent 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

openclaw-kirocli-coding-agent 用的人多吗?

公开数据是累计安装 41,748 次,近一周安装 1,775 次,下载 14,626 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openclaw-kirocli-coding-agent 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
openclaw-kirocli-coding-agent

OpenClaw kirocli coding Agent CLI · 本页

41,748—执行命令MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
coding-agent
description
Run Codex CLI, Claude Code, Kiro CLI, OpenCode, or Pi Coding Agent via background process for programmatic control.
metadata

Coding Agent

Launch and manage AI coding agents (Codex, Claude Code, Kiro CLI, OpenCode, Pi) from OpenClaw using bash with background process control.

PTY Mode Required

Coding agents are interactive terminal applications that need a pseudo-terminal (PTY). Without it, output breaks or the agent hangs.

Always set pty:true:

# Correct — with PTY
bash pty:true command:"codex exec 'Your prompt'"

# Wrong — agent may break or hang
bash command:"codex exec 'Your prompt'"

Tool Reference

Bash Parameters

ParameterTypeDescription
commandstringShell command to run
ptybooleanAllocate a pseudo-terminal (required for coding agents)
workdirstringWorking directory (agent sees only this folder)
backgroundbooleanRun in background; returns sessionId for monitoring
timeoutnumberTimeout in seconds (kills process on expiry)
elevatedbooleanRun on host instead of sandbox (if allowed)

Process Actions (background sessions)

ActionDescription
listList all running/recent sessions
pollCheck if a session is still running
logGet session output (optional offset/limit)
writeSend raw data to stdin (no newline)
submitSend data + newline (like typing and pressing Enter)
send-keysSend key tokens or hex bytes
pastePaste text (optional bracketed mode)
killTerminate the session

Quick Start: One-Shot Tasks

# Codex needs a git repo — create a temp one for scratch work
SCRATCH=$(mktemp -d) && cd $SCRATCH && git init && codex exec "Your prompt"

# Run inside an existing project (with PTY)
bash pty:true workdir:~/project command:"codex exec 'Add error handling to the API calls'"

Core Pattern: workdir + background + pty

For longer tasks, combine all three:

# 1. Start the agent
bash pty:true workdir:~/project background:true command:"codex exec --full-auto 'Build a snake game'"
# → returns sessionId

# 2. Monitor progress
process action:log sessionId:XXX

# 3. Check completion
process action:poll sessionId:XXX

# 4. Send input if the agent asks a question
process action:submit sessionId:XXX data:"yes"     # text + Enter
process action:write sessionId:XXX data:"y"         # raw keystroke

# 5. Kill if stuck
process action:kill sessionId:XXX

Why workdir? The agent starts in a focused directory and won't wander into unrelated files.


Codex CLI

Default model: gpt-5.2-codex (set in ~/.codex/config.toml)

Flags

FlagEffect
exec "prompt"One-shot execution, exits when done
--full-autoSandboxed, auto-approves within workspace
--yoloNo sandbox, no approvals (fastest, most dangerous)

Building / Creating

# One-shot with auto-approve
bash pty:true workdir:~/project command:"codex exec --full-auto 'Build a dark mode toggle'"

# Background for longer work
bash pty:true workdir:~/project background:true command:"codex --yolo 'Refactor the auth module'"

Reviewing PRs

Never review PRs in OpenClaw's own project folder. Clone to a temp directory or use a git worktree.

# Clone to temp
REVIEW_DIR=$(mktemp -d)
git clone https://github.com/user/repo.git $REVIEW_DIR
cd $REVIEW_DIR && gh pr checkout 130
bash pty:true workdir:$REVIEW_DIR command:"codex review --base origin/main"

# Or use git worktree (keeps main intact)
git worktree add /tmp/pr-130-review pr-130-branch
bash pty:true workdir:/tmp/pr-130-review command:"codex review --base main"

Batch PR Reviews

# Fetch all PR refs
git fetch origin '+refs/pull/*/head:refs/remotes/origin/pr/*'

# Launch one Codex per PR (all background + PTY)
bash pty:true workdir:~/project background:true command:"codex exec 'Review PR #86. git diff origin/main...origin/pr/86'"
bash pty:true workdir:~/project background:true command:"codex exec 'Review PR #87. git diff origin/main...origin/pr/87'"

# Monitor
process action:list

# Post results
gh pr comment <PR#> --body "<review content>"

Claude Code

# One-shot
bash pty:true workdir:~/project command:"claude 'Your task'"

# Background
bash pty:true workdir:~/project background:true command:"claude 'Your task'"

Kiro CLI (AWS)

AWS AI coding assistant with session persistence, custom agents, skills, hooks, steering, subagents, planning mode, and MCP integration.

Install: https://kiro.dev/docs/cli/installation

Basic Usage

kiro-cli                           # Interactive chat (default)
kiro-cli chat "Your question"      # Direct question
kiro-cli --agent my-agent          # Use a specific agent
kiro-cli chat --resume             # Resume last session (per-directory)
kiro-cli chat --resume-picker      # Pick from saved sessions
kiro-cli chat --list-sessions      # List all sessions

Non-Interactive Mode

For scripting and automation — outputs a single response to STDOUT, then exits.

# Single response
kiro-cli chat --no-interactive "Show current directory"

# Trust all tools (no confirmation prompts)
kiro-cli chat --no-interactive --trust-all-tools "Create hello.py"

# Trust specific tools only
kiro-cli chat --no-interactive --trust-tools "fs_read,fs_write" "Read package.json"

Tool trust: --trust-all-tools for full automation. For untrusted input, use --trust-tools "fs_read,fs_write,shell" to limit scope.

OpenClaw Integration

# Interactive session (background)
bash pty:true workdir:~/project background:true command:"kiro-cli"

# One-shot query (non-interactive)
bash pty:true workdir:~/project command:"kiro-cli chat --no-interactive --trust-all-tools 'List all TODO comments in src/'"

# With a specific agent
bash pty:true workdir:~/project background:true command:"kiro-cli --agent aws-expert 'Set up Lambda'"

# Resume previous session
bash pty:true workdir:~/project command:"kiro-cli chat --resume"

Skills (Agent Skills)

Skills are portable instruction packages that extend what Kiro knows. When a request matches a skill's description, Kiro automatically loads and follows its instructions — no slash command needed.

Skill Locations
LocationScopeNotes
.kiro/skills/<name>/Workspace (project)Shared via version control
~/.kiro/skills/<name>/Global (all projects)Personal workflows

Workspace skills take priority when names collide.

Creating a Skill

A skill is a folder with a SKILL.md file:

my-skill/
├── SKILL.md          # Required — frontmatter + instructions
└── references/       # Optional — detailed docs loaded on demand
    └── guide.md

SKILL.md format:

---
name: pr-review
description: Review pull requests for code quality, security issues, and test coverage.
---

## Review checklist

1. Check for vulnerabilities, injection risks, exposed secrets
2. Verify edge cases and failure modes are handled
3. Confirm new code has appropriate tests

For detailed patterns, see `references/guide.md`.
  • name — Unique identifier for the skill.
  • description — Determines when Kiro activates the skill. Be specific; include keywords that match how you'd phrase requests.
  • Reference files — Stored in references/. Kiro loads them only when the instructions direct it to.
Skills in Custom Agents

The default agent auto-discovers skills. Custom agents need explicit resource declarations:

{
  "name": "my-agent",
  "resources": [
    "skill://.kiro/skills/*/SKILL.md",
    "skill://~/.kiro/skills/*/SKILL.md"
  ]
}
Skill Best Practices
  • Precise descriptions — "Review pull requests for security vulnerabilities and test coverage" activates reliably; "Helps with code review" does not.
  • Keep SKILL.md actionable — Put lengthy reference material in references/ files.
  • Right scope — Global skills for personal workflows; workspace skills for team/project conventions.
  • Version control — Commit .kiro/skills/ so the team shares the same workflows.
  • Check availability — Use /context show to see which skills are loaded in the current session.

Planning Mode (Plan Agent)

Plan Agent is a built-in read-only agent for structured planning before execution. It transforms ideas into detailed implementation plans through an interactive workflow.

When to Use
  • Complex multi-step features (e.g., "build a user authentication system")
  • Unclear or evolving requirements that need refinement
  • Large features that benefit from task breakdown before coding
When NOT to Use
  • Simple queries or single-step tasks
  • User already has clear, specific instructions
  • Quick fixes or small changes
How to Enter Planning Mode
# Slash command
> /plan

# With an immediate prompt
> /plan Build a REST API for user authentication

# Keyboard shortcut (toggles plan ↔ execution)
Shift + Tab

When active, the prompt shows a [plan] indicator.

Plan Workflow (4 phases)
  1. Requirements gathering — Structured multiple-choice questions to refine your idea. Answer with 1=a, 2=b syntax or free-text.
  2. Research & analysis — Explores your codebase using code intelligence, grep, and glob tools.
  3. Implementation plan — Produces a task breakdown with clear objectives, implementation guidance, and demo descriptions for each task.
  4. Approval & handoff — You review the plan. On approval (y), the plan transfers automatically to the execution agent.

Plan Agent is read-only: it can read files, search code, and research, but cannot write files or execute commands until handoff.

OpenClaw Integration for Planning Mode

For interactive planning sessions, run Kiro in background mode and relay the /plan command:

# Start interactive Kiro session
bash pty:true workdir:~/project background:true command:"kiro-cli chat --trust-all-tools"

# Enter planning mode
process action:submit sessionId:XXX data:"/plan Build a REST API for user authentication"

# Relay the user's answers to requirement questions
process action:submit sessionId:XXX data:"1=a, 2=d I'm using Rust with Axum"

# Approve the plan
process action:submit sessionId:XXX data:"y"

# Monitor output
process action:log sessionId:XXX
Example Planning Session
> /plan Add user authentication to my web app

[plan] > I understand you want to add user authentication.
[1]: What authentication method?
  a. Email/Password   b. OAuth   c. Magic Links   d. Multi-factor
> 1=a

[plan] > Great! Email/password it is.
[2]: What's your tech stack?
  a. React + Node.js   b. Next.js   c. Django/Flask   d. Other
> 2=d, I'm using Rust with Axum

[plan] > Researching Axum authentication patterns...

**Implementation Plan — User Authentication System**
[Detailed task breakdown...]

Does this plan look good? Ready to exit [plan] agent? [y/n]: y
[default] > Implement this plan: [Plan transferred]

Hooks

Hooks execute custom commands at specific points during agent lifecycle and tool execution. Defined in the agent configuration file.

Hook Types
HookTriggerCan Block?
AgentSpawnAgent startsNo
UserPromptSubmitUser sends a promptNo
PreToolUseBefore a tool runsYes (exit code 2)
PostToolUseAfter a tool runsNo
StopAgent finishes a turnNo
Exit Codes
  • 0 — Success. STDOUT captured (added to context for AgentSpawn/UserPromptSubmit).
  • 2 — (PreToolUse only) Block tool execution; STDERR returned to the LLM.
  • Other — Failure. STDERR shown as warning to user.
Tool Matching

Use the matcher field to target specific tools:

MatcherMatches
"fs_write" or "write"Write tool
"execute_bash" or "shell"Shell execution
"@git"All tools from git MCP server
"@git/status"Specific MCP tool
"*"All tools (built-in + MCP)
"@builtin"Built-in tools only
Configuration
  • timeout_ms — Default 30,000ms (30s).
  • cache_ttl_seconds — 0 = no caching (default); > 0 = cache successful results. AgentSpawn hooks are never cached.

See Agent Configuration Reference for full syntax.

Subagents

Kiro can delegate tasks to subagents — independent agents with their own context that run autonomously and return results.

> Use the backend agent to refactor the payment module

Key capabilities:

  • Autonomous execution with isolated context
  • Live progress tracking
  • Parallel execution for multiple tasks
  • Custom agent configurations for specialized workflows

Available tools in subagents: read, write, shell, code intelligence, MCP tools. Not available: web_search, web_fetch, use_aws, grep, glob, thinking, todo_list.

Custom Agents

Pre-define tool permissions, context resources, and behaviors:

kiro-cli agent list              # List available agents
kiro-cli agent create my-agent   # Create new agent
kiro-cli agent edit my-agent     # Edit agent config
kiro-cli agent validate ./a.json # Validate config file
kiro-cli agent set-default my-agent

Benefits: Pre-approved tool trust, limited tool access, auto-loaded project docs, shareable team configs.

Steering (Project Context)

Provide persistent project knowledge via markdown files:

PathScope
.kiro/steering/Workspace — this project only
~/.kiro/steering/Global — all projects

Example structure:

.kiro/steering/
├── product.md           # Product overview
├── tech.md              # Tech stack
├── structure.md         # Project structure
└── api-standards.md     # API conventions

Also supports AGENTS.md in the project root or ~/.kiro/steering/.

In custom agents: Add "resources": ["file://.kiro/steering/**/*.md"] to config.

MCP Integration

Connect external tools and data sources via Model Context Protocol:

kiro-cli mcp add --name my-server --command "node server.js" --scope workspace
kiro-cli mcp list [workspace|global]
kiro-cli mcp status --name my-server
kiro-cli mcp remove --name my-server --scope workspace

OpenCode

bash pty:true workdir:~/project command:"opencode run 'Your task'"

Pi Coding Agent

# Install: npm install -g @mariozechner/pi-coding-agent

# Interactive
bash pty:true workdir:~/project command:"pi 'Your task'"

# Non-interactive (single response)
bash pty:true command:"pi -p 'Summarize src/'"

# Different provider/model
bash pty:true command:"pi --provider openai --model gpt-4o-mini -p 'Your task'"

Parallel Issue Fixing (git worktrees)

Fix multiple issues simultaneously using isolated worktrees:

# 1. Create worktrees
git worktree add -b fix/issue-78 /tmp/issue-78 main
git worktree add -b fix/issue-99 /tmp/issue-99 main

# 2. Launch agents (background + PTY)
bash pty:true workdir:/tmp/issue-78 background:true command:"pnpm install && codex --yolo 'Fix issue #78: <description>. Commit and push.'"
bash pty:true workdir:/tmp/issue-99 background:true command:"pnpm install && codex --yolo 'Fix issue #99: <description>. Commit and push.'"

# 3. Monitor
process action:list
process action:log sessionId:XXX

# 4. Create PRs
cd /tmp/issue-78 && git push -u origin fix/issue-78
gh pr create --repo user/repo --head fix/issue-78 --title "fix: ..." --body "..."

# 5. Clean up
git worktree remove /tmp/issue-78
git worktree remove /tmp/issue-99

Rules

  1. Always use pty:true — Coding agents need a pseudo-terminal.
  2. Respect tool choice — If the user asks for Kiro, use Kiro; for Codex, use Codex. Do NOT hand-code patches yourself when orchestrating agents. If an agent fails or hangs, respawn it or ask the user — don't silently take over.
  3. Be patient — Don't kill sessions just because they seem slow.
  4. Monitor with process:log — Check progress without interfering.
  5. Codex auto-approve flags — Use --full-auto (sandboxed) or --yolo (no sandbox) for building tasks.
  6. Kiro tool trust — Use --trust-all-tools for automation; --trust-tools for restricted scope.
  7. Kiro one-shots — Use --no-interactive for single-response queries.
  8. Parallel is OK — Run multiple agent processes concurrently for batch work.
  9. Never start agents in ~/clawd/ — Agents will read system docs and behave unpredictably.
  10. Never checkout branches in ~/Projects/openclaw/ — That's the live OpenClaw instance.
  11. Suggest Kiro /plan for complex tasks — When requirements are unclear or multi-step, suggest Plan Agent and let the user decide.
  12. Leverage Kiro skills — If the project has .kiro/skills/ or the user has ~/.kiro/skills/, relevant skills activate automatically. No extra flags needed.

Progress Updates

When you spawn coding agents in the background, keep the user informed:

  • On start — 1 short message: what's running, where, and which agent.
  • On change — Update only when something happens:

- A milestone completes (build finished, tests passed) - The agent asks a question or needs input - An error occurs or user action is needed - The agent finishes (include what changed and where)

  • On kill — Immediately say you killed it and why.

Auto-Notify on Completion

For long-running tasks, append a wake trigger so OpenClaw is notified immediately when the agent finishes:

... your task here.

When completely finished, run this command to notify me:
openclaw gateway wake --text "Done: [brief summary]" --mode now

Example:

bash pty:true workdir:~/project background:true command:"codex --yolo exec 'Build a REST API for todos.

When completely finished, run: openclaw gateway wake --text \"Done: Built todos REST API with CRUD endpoints\" --mode now'"

This triggers an immediate wake event instead of waiting for the next heartbeat.


Learnings

  • PTY is essential — Without pty:true, output breaks or the agent hangs.
  • Git repo required for Codex — Use mktemp -d && git init for scratch work.
  • exec for one-shots — codex exec "prompt" runs and exits cleanly.
  • submit vs write — submit sends input + Enter; write sends raw data without newline.
  • Skills activate automatically — No slash command needed; Kiro matches your request against skill descriptions.
  • Plan before complex builds — /plan saves time on multi-step features by clarifying requirements upfront.

平台分布

OpenClaw

89.39%
按下载量换算13,074

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install openclaw-kirocli-coding-agent 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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