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Dingtalk Workspace Cli

FSecurity

Use DingTalk Workspace CLI (dws) to manage DingTalk contacts, calendar, todos, attendance, approvals, and more from the command line or AI agent workflows.

81 stars
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Added 9/19/2026
devopsrustgoshellbashtestinggitapici/cdsecurity

Works with

claude codecursorcliapimcp

Security Analysis

F39/100
criticalPipes output to a shell interpreter
mediumUses curl or wget to download content
highPerforms destructive filesystem operations
criticalModifies startup scripts or system services for persistence
criticalModifies startup scripts or system services for persistence
criticalDownloads and executes remote scripts — classic supply chain attack

Scanned 9/19/2026

Install to Claude Code

$npx -y skills add reason-machines/trending-skills --skill dingtalk-workspace-cli --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: dingtalk-workspace-cli
description: Use DingTalk Workspace CLI (dws) to manage DingTalk contacts, calendar, todos, attendance, approvals, and more from the command line or AI agent workflows.
triggers:
  - use dingtalk from the command line
  - automate dingtalk with dws
  - search dingtalk contacts
  - create dingtalk todo or calendar event
  - integrate dingtalk with AI agent
  - send dingtalk message via CLI
  - manage dingtalk workspace programmatically
  - dws command help
---

# DingTalk Workspace CLI (dws)

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.

`dws` is an officially open-sourced cross-platform CLI tool from DingTalk that unifies DingTalk's full product suite into a single binary. It is designed for both human users and AI agent workflows. Every response is structured JSON, and built-in Agent Skills let LLMs use DingTalk out of the box.

---

## Installation

### One-liner (recommended)

**macOS / Linux:**
```bash
curl -fsSL https://raw.githubusercontent.com/DingTalk-Real-AI/dingtalk-workspace-cli/main/scripts/install.sh | sh
```

**Windows (PowerShell):**
```powershell
irm https://raw.githubusercontent.com/DingTalk-Real-AI/dingtalk-workspace-cli/main/scripts/install.ps1 | iex
```

The installer:
- Auto-detects OS and architecture
- Downloads a pre-compiled binary to `~/.local/bin`
- Installs Agent Skills to `~/.agents/skills/dws`

Add to PATH if needed:
```bash
export PATH="$HOME/.local/bin:$PATH"
# Add to ~/.bashrc or ~/.zshrc to persist
```

### Build from source

```bash
git clone https://github.com/DingTalk-Real-AI/dingtalk-workspace-cli.git
cd dingtalk-workspace-cli
make build
./dws version
```

---

## Prerequisites & Setup

### 1. Create a DingTalk app

Go to [DingTalk Open Platform](https://open-dev.dingtalk.com/fe/app?hash=%23%2Fcorp%2Fapp#/corp/app), create an enterprise internal app, and note the **Client ID (AppKey)** and **Client Secret (AppSecret)**.

### 2. Configure redirect URL

In the app's **Security Settings**, add `http://127.0.0.1` as a redirect URL.

### 3. Publish the app

Go to **App Release → Version Management** and publish the app so it is active.

### 4. Whitelist (beta)

During the co-creation phase, join the DingTalk DWS group and provide your Client ID and enterprise admin confirmation to be whitelisted.

### 5. Authenticate

```bash
# Via CLI flags
dws auth login --client-id $DWS_CLIENT_ID --client-secret $DWS_CLIENT_SECRET

# Or set env vars first, then login
export DWS_CLIENT_ID=your-app-key
export DWS_CLIENT_SECRET=your-app-secret
dws auth login
```

Tokens are stored encrypted with **PBKDF2 (600,000 iterations) + AES-256-GCM**, keyed to your device MAC address.

---

## Environment Variables

| Variable | Purpose |
|---|---|
| `DWS_CLIENT_ID` | OAuth Client ID (DingTalk AppKey) |
| `DWS_CLIENT_SECRET` | OAuth Client Secret (DingTalk AppSecret) |
| `DWS_CONFIG_DIR` | Override default config directory |
| `DWS_SERVERS_URL` | Custom server registry endpoint |
| `DWS_TRUSTED_DOMAINS` | Comma-separated domains for bearer token (default: `*.dingtalk.com`) |
| `DWS_ALLOW_HTTP_ENDPOINTS` | Set to `1` to allow HTTP on loopback (dev only) |

---

## Key Commands

### Authentication

```bash
dws auth login                        # Authenticate via OAuth device flow
dws auth logout                       # Remove stored credentials
dws auth status                       # Show current auth status
```

### Contacts

```bash
# Search users
dws contact user search --keyword "Alice"

# List departments
dws contact department list

# Get user details
dws contact user get --user-id <userId>
```

### Calendar

```bash
# List events
dws calendar event list

# Create an event
dws calendar event create \
  --title "Q2 Planning" \
  --start "2026-04-01T10:00:00+08:00" \
  --end "2026-04-01T11:00:00+08:00" \
  --attendees "<userId1>,<userId2>"

# Check room availability
dws calendar room list
```

### Todo

```bash
# List tasks
dws todo task list

# Create a task
dws todo task create \
  --title "Prepare quarterly report" \
  --executors "<userId>"

# Complete a task
dws todo task complete --task-id <taskId>
```

### Chat

```bash
# List groups
dws chat group list

# Send a message via webhook
dws chat webhook send \
  --url $DINGTALK_WEBHOOK_URL \
  --content "Deployment succeeded ✅"

# Send robot message
dws chat robot send \
  --group-id <groupId> \
  --content "Hello from dws"
```

### Attendance

```bash
# Get attendance records
dws attendance record list --user-id <userId> --date "2026-03-01"

# List shift schedules
dws attendance shift list
```

### Approval

```bash
# List approval templates
dws approval template list

# Submit an approval instance
dws approval instance create \
  --process-code <processCode> \
  --form-values '{"key":"value"}'

# Query approval instances
dws approval instance list --status RUNNING
```

### DING Messages

```bash
# Send a DING message
dws ding send --receiver-ids "<userId>" --content "Urgent: please review PR"

# Recall a DING message
dws ding recall --ding-id <dingId>
```

### AI Table (aitable)

```bash
# List tables
dws aitable table list --space-id <spaceId>

# Query records
dws aitable record list --table-id <tableId>
```

### Developer Docs

```bash
# Search DingTalk open platform docs
dws devdoc search --keyword "webhook"
```

### Workbench

```bash
# List workbench apps
dws workbench app list
```

---

## Output Formats

All commands support `-f` / `--format`:

```bash
# Human-readable table (default)
dws contact user search --keyword "Alice" -f table

# Structured JSON (for agents and piping)
dws contact user search --keyword "Alice" -f json

# Raw API response
dws contact user search --keyword "Alice" -f raw
```

Save output to a file:
```bash
dws contact user search --keyword "Alice" -f json -o results.json
```

---

## Dry Run

Preview the MCP tool call without executing it:

```bash
dws todo task list --dry-run
dws calendar event create --title "Test" --dry-run
```

---

## Shell Completion

```bash
# Bash
dws completion bash > /etc/bash_completion.d/dws

# Zsh
dws completion zsh > "${fpath[1]}/_dws"

# Fish
dws completion fish > ~/.config/fish/completions/dws.fish
```

---

## Exit Codes

| Code | Category | Meaning |
|---|---|---|
| 0 | Success | Command completed successfully |
| 1 | API | MCP tool call or upstream API failure |
| 2 | Auth | Authentication or authorization failure |
| 3 | Validation | Bad input flags or schema mismatch |
| 4 | Discovery | Service discovery or cache failure |
| 5 | Internal | Unexpected internal error |

When using `-f json`, errors include structured fields: `category`, `reason`, `hint`, `actions`.

---

## Common Patterns

### Scripting: find a user then create a todo assigned to them

```bash
#!/bin/bash
set -euo pipefail

# Search for user and extract userId
USER_ID=$(dws contact user search --keyword "Alice" -f json | \
  jq -r '.data[0].userId')

echo "Found user: $USER_ID"

# Create a todo assigned to that user
dws todo task create \
  --title "Review design doc" \
  --executors "$USER_ID" \
  -f json
```

### Scripting: send a daily standup reminder

```bash
#!/bin/bash
dws ding send \
  --receiver-ids "$TEAM_USER_IDS" \
  --content "🕘 Daily standup in 5 minutes — please join!" \
  -f json
```

### CI/CD: post build status to a DingTalk group

```bash
#!/bin/bash
STATUS=${1:-"unknown"}
EMOJI=$([[ "$STATUS" == "success" ]] && echo "✅" || echo "❌")

dws chat webhook send \
  --url "$DINGTALK_WEBHOOK_URL" \
  --content "$EMOJI Build #$BUILD_NUMBER $STATUS — $BUILD_URL"
```

### Using dws in a Go project

```go
package main

import (
    "os/exec"
    "encoding/json"
    "fmt"
)

type SearchResult struct {
    Data []struct {
        UserID string `json:"userId"`
        Name   string `json:"name"`
    } `json:"data"`
}

func searchDingTalkUser(keyword string) (*SearchResult, error) {
    cmd := exec.Command("dws", "contact", "user", "search",
        "--keyword", keyword,
        "-f", "json",
    )
    out, err := cmd.Output()
    if err != nil {
        return nil, fmt.Errorf("dws error: %w", err)
    }
    var result SearchResult
    if err := json.Unmarshal(out, &result); err != nil {
        return nil, err
    }
    return &result, nil
}

func main() {
    result, err := searchDingTalkUser("Alice")
    if err != nil {
        panic(err)
    }
    for _, u := range result.Data {
        fmt.Printf("User: %s (%s)\n", u.Name, u.UserID)
    }
}
```

---

## AI Agent Integration

`dws` installs Agent Skills automatically. Most AI coding agents (Claude Code, Cursor, Windsurf, etc.) auto-discover skills in `.agents/skills/`.

### Install skills for a specific project

```bash
# Install to current working directory (project-scoped)
curl -fsSL https://raw.githubusercontent.com/DingTalk-Real-AI/dingtalk-workspace-cli/main/scripts/install-skills.sh | sh
```

Skills are placed at `./.agents/skills/dws/` — commit these to your repo so all collaborators and agents get DingTalk capabilities automatically.

### Typical agent prompts that trigger dws

- "Find the user ID for Alice in DingTalk"
- "Create a todo assigned to Bob for reviewing the PR"
- "List my calendar events for tomorrow"
- "Send a DING message to the team leads"
- "Check attendance records for user X this month"

---

## Architecture Overview

`dws` uses a **discovery-driven pipeline** — no product commands are hardcoded:

```
Market Registry → Discovery → IR (normalized catalog) → CLI (Cobra) → Transport (MCP JSON-RPC)
       ↓               ↓
  mcp.dingtalk.com   Disk cache (TTL + stale-fallback for offline use)
```

1. **Market** — fetches MCP service registry from `mcp.dingtalk.com`
2. **Discovery** — resolves service capabilities, cached to disk with TTL and stale fallback
3. **IR** — normalizes services into a unified product/tool catalog
4. **CLI** — mounts catalog onto a Cobra command tree, maps flags to MCP input params
5. **Transport** — executes MCP JSON-RPC calls with retry, auth injection, and response size limits

---

## Development

```bash
make build                       # Build binary
make test                        # Run unit tests
make lint                        # Format + lint
make package                     # Build all release artifacts locally (goreleaser snapshot)
make release                     # Build and release via goreleaser
```

---

## Troubleshooting

**`dws: command not found`**
```bash
export PATH="$HOME/.local/bin:$PATH"
```

**Auth errors (exit code 2)**
- Verify `DWS_CLIENT_ID` and `DWS_CLIENT_SECRET` are correct
- Confirm the app is published and the redirect URL `http://127.0.0.1` is configured
- Confirm your enterprise is whitelisted (required during beta)

**Discovery failures (exit code 4)**
- `dws` caches service discovery; if the cache is stale, delete it:
  ```bash
  rm -rf "${DWS_CONFIG_DIR:-$HOME/.config/dws}/cache"
  ```
- Set `DWS_SERVERS_URL` if using a custom registry

**API errors (exit code 1)**
```bash
# Get structured error details
dws todo task list -f json
# Response includes: category, reason, hint, actions
```

**Inspect raw requests**
```bash
dws contact user search --keyword "Alice" -f raw
```

**Allow HTTP for local dev/testing**
```bash
export DWS_ALLOW_HTTP_ENDPOINTS=1
```

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