DingTalk Workspace CLI (dws)

dws — DingTalk Workspace on the command line, built for humans and AI agents.

中文版 · English · Reference · Changelog

Important

Co-creation Phase: This project accesses DingTalk enterprise data and requires enterprise admin authorization. Join the DingTalk DWS co-creation group for support and updates. See Getting Started below.

Table of Contents

• Why dws?
• Installation
• Upgrade
• Getting Started
• Quick Start
• Using with Agents
• Features
• Key Services
• Security by Design
• Reference & Docs
• Contributing

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Why dws?

• For humans — --help for usage, --dry-run to preview requests, -f table/json/raw for output formats.
• For AI agents — structured JSON responses + built-in Agent Skills, ready out of the box.
• For enterprise admins — zero-trust architecture: OAuth device-flow auth + domain allowlisting + least-privilege scoping. Not a single byte can bypass authentication and audit.

Installation

macOS / Linux:

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

Windows (PowerShell):

irm https://raw.githubusercontent.com/DingTalk-Real-AI/dingtalk-workspace-cli/main/scripts/install.ps1 | iex

Other install methods

npm (requires Node.js (npm/npx)):

npm install -g dingtalk-workspace-cli

Pre-built binary: download from GitHub Releases.

macOS users: If you see "cannot be opened because Apple cannot check it for malicious software", run:

xattr -d com.apple.quarantine /path/to/dws

Build from source:

git clone https://github.com/DingTalk-Real-AI/dingtalk-workspace-cli.git
cd dingtalk-workspace-cli
go build -o dws ./cmd       # build to current directory
cp dws ~/.local/bin/         # install to PATH

Requires Go 1.25+. Use make package to cross-compile for all platforms (macOS / Linux / Windows x amd64 / arm64).

Upgrade

Requires v1.0.7 or later. For earlier versions, please re-run the install script to upgrade.

dws has built-in self-upgrade capability. Updates are pulled directly from GitHub Releases with SHA256 integrity verification and automatic backup.

dws upgrade                    # interactive upgrade to latest version
dws upgrade --check            # check for new versions without installing
dws upgrade --list             # list all available versions
dws upgrade --version v1.0.7   # upgrade to a specific version
dws upgrade --rollback         # rollback to the previous version
dws upgrade -y                 # skip confirmation prompt

How it works

The upgrade process follows a two-phase atomic flow to ensure consistency:

1. Prepare — downloads the platform-specific binary and skill packages to a temporary directory, verifies SHA256 checksums, and extracts/validates all files. If any step fails, the upgrade aborts without modifying the existing installation.
2. Apply — only after all preparations succeed, the binary is replaced and skill packages are installed to all detected agent directories (~/.agents/skills/dws, ~/.claude/skills/dws, ~/.cursor/skills/dws, etc.).

A backup of the current version is automatically created before each upgrade. Use dws upgrade --rollback to restore the previous version if needed.

Flag	Description
--check	Check for updates without installing
--list	List all available versions with changelogs
--version	Upgrade to a specific version (e.g. v1.0.7)
--rollback	Rollback to the previous backed-up version
--force	Force reinstall even if already on the latest version
--skip-skills	Skip skill package update
-y	Skip confirmation prompt

Getting Started

dws auth login            # browser opens automatically
dws auth login --device   # for headless environments (Docker, SSH, CI)

Select your organization and authorize. That's it.

If your organization hasn't enabled CLI access, you'll be prompted to send an access request to your admin. Once approved, re-run dws auth login.

Organization hasn't enabled CLI access?

1. After selecting your organization, click "Apply Now" to notify the admin
2. The admin receives a request card and can approve with one click
3. Once approved, re-run dws auth login

Admin: Enable CLI access for your organization

Go to Developer Platform → "CLI Access Management" → Enable.

Custom App mode (CI/CD, ISV integration)

For enterprise-managed scenarios, create your own DingTalk app:

1. Open Platform Console → Create App
2. Security Settings → Add redirect URLs: http://127.0.0.1,https://login.dingtalk.com
3. Publish the app
4. Login:

dws auth login --client-id <your-app-key> --client-secret <your-app-secret>

Credentials are securely persisted after first login (Keychain). Subsequent runs auto-refresh tokens.

Quick Start

dws contact user search --keyword "engineering"     # search contacts
dws calendar event list                            # list calendar events
dws todo task create --title "Quarterly report" --executors "<your-userId>"   # create a todo (replace <your-userId>)
dws todo task list --dry-run                       # preview without executing

Using with Agents

dws is designed as an AI-native CLI. Complete Installation and Getting Started first, then configure your agent:

Agent Invocation Patterns

# Use --yes to skip confirmation prompts (required for agents)
dws todo task create --title "Review PR" --executors "<your-userId>" --yes

# Use --dry-run to preview operations (safe execution)
dws contact user search --keyword "engineering" --dry-run

# Use --jq to extract precisely (save tokens)
dws contact user get-self --jq '.result[0].orgEmployeeModel | {name: .orgUserName, dept: .depts[0].deptName, userId}'

Schema Discovery

Agents don't need pre-built knowledge of every command. Use dws schema to dynamically discover capabilities:

# Step 1: Discover all available products
dws schema --jq '.products[] | {id, tool_count: (.tools | length)}'

# Step 2: Inspect target tool's parameter schema
dws schema aitable.query_records --jq '.tool.parameters'

# Step 3: Construct the correct call
dws aitable record query --base-id BASE_ID --table-id TABLE_ID --limit 10

Agent Skills

The repo ships a complete Agent Skill system (skills/). After installing, AI tools like Claude Code / Cursor can operate DingTalk directly through natural language:

# Install skills into current project
curl -fsSL https://raw.githubusercontent.com/DingTalk-Real-AI/dingtalk-workspace-cli/main/scripts/install-skills.sh | sh

install.sh installs to $HOME/.agents/skills/dws (global); install-skills.sh installs to ./.agents/skills/dws (current project).

What's included:

Component	Path	Description
Master Skill	SKILL.md	Intent routing, decision tree, safety rules, error handling
Product references	references/products/*.md	Per-product command reference (aitable, chat, calendar, etc.)
Intent guide	references/intent-guide.md	Disambiguation for confusing scenarios (e.g. report vs todo)
Global reference	references/global-reference.md	Auth, output formats, global flags
Error codes	references/error-codes.md	Error codes + debugging workflows
Recovery guide	references/recovery-guide.md	RECOVERY_EVENT_ID handling
Ready-made scripts	scripts/*.py	13 batch operation scripts (see below)

Ready-made scripts — 13 Python scripts for common multi-step workflows

Script	Description
calendar_schedule_meeting.py	Create event + add participants + find & book available meeting room
calendar_free_slot_finder.py	Find common free slots across multiple people, recommend best meeting time
calendar_today_agenda.py	View today/tomorrow/this week's schedule
import_records.py	Batch import records from CSV/JSON into AITable
bulk_add_fields.py	Batch add fields to an AITable data table
upload_attachment.py	Upload attachment to AITable attachment field
todo_batch_create.py	Batch create todos from JSON (with priority, due date, executors)
todo_daily_summary.py	Summarize today/this week's incomplete todos
todo_overdue_check.py	Scan overdue todos and output overdue list
contact_dept_members.py	Search department by name and list all members
attendance_my_record.py	View my attendance records for today/this week/specific date
attendance_team_shift.py	Query team shift schedules and attendance statistics
report_inbox_today.py	View today's received reports with details

ISV Integration: Author your own Agent Skills and orchestrate them with dws skills for cross-product workflows: ISV Skill → dws Skill → DingTalk Open Platform API (enforced auth + full audit).

Features

Smart Input Correction — auto-corrects common AI model parameter mistakes

Built-in pipeline engine that normalizes flag names, splits sticky arguments, and fuzzy-matches typos:

# Naming convention auto-conversion (camelCase / snake_case / UPPER -> kebab-case)
dws aitable record query --baseId BASE_ID --tableId TABLE_ID         # auto-corrected to --base-id --table-id

# Sticky argument splitting
dws contact user search --keyword "engineering" --timeout30           # auto-split to --timeout 30

# Fuzzy flag name matching
dws aitable record query --base-id BASE_ID --tabel-id TABLE_ID       # --tabel-id -> --table-id

# Value normalization (boolean / number / date / enum)
# "yes" -> true, "1,000" -> 1000, "2024/03/29" -> "2024-03-29", "ACTIVE" -> "active"

Agent Output	dws Auto-Corrects To
--userId	--user-id
--limit100	--limit 100
--tabel-id	--table-id
--USER-ID	--user-id
--user_name	--user-name

jq Filtering & Field Selection — fine-grained output control to reduce token consumption

# Built-in jq expressions
dws aitable record query --base-id BASE_ID --table-id TABLE_ID --jq '.invocation.params'
dws schema --jq '.products[] | {id, tools: (.tools | length)}'

# Return only specific fields
dws aitable record query --base-id BASE_ID --table-id TABLE_ID --fields invocation,response

Schema Introspection — query parameter schemas before making calls

dws schema                                              # list all products and tools
dws schema aitable.query_records                        # view parameter schema
dws schema aitable.query_records --jq '.tool.required'   # view required fields
dws schema --jq '.products[].id'                        # extract all product IDs

Pipe & File Input — read flag values from files or stdin

# Read message body from a file
dws chat message send-by-bot --robot-code BOT_CODE --group GROUP_ID \
  --title "Weekly Report" --text @report.md

# Pipe content via stdin
cat report.md | dws chat message send-by-bot --robot-code BOT_CODE --group GROUP_ID \
  --title "Weekly Report"

# Read from stdin explicitly
dws chat message send-by-bot --robot-code BOT_CODE --group GROUP_ID \
  --title "Weekly Report" --text @-

Key Services

Service	Command	Commands	Subcommands	Description
Contact	contact	6	user dept	Search users by name/mobile, batch query, departments, current user profile
Chat	chat	10	message group search	Group CRUD, member management, bot messaging, webhook
Bot	chat bot	6	bot group message search	Robot creation/search, group/single messaging, webhook, message recall
Calendar	calendar	13	event room participant busy	Events CRUD, meeting room booking, free-busy query, participant management
Todo	todo	6	task	Create, list, update, done, get detail, delete
Approval	oa	9	approval	Approve/reject/revoke, pending tasks, initiated instances, process list
Attendance	attendance	4	record shift summary rules	Clock-in records, shift schedules, attendance summary, group rules
Ding	ding	2	message	Send/recall DING messages
Report	report	7	create list detail template stats sent	Create reports, sent/received list, templates, statistics
AITable	aitable	20	base table record field attachment template	Full CRUD for bases/tables/records/fields, templates
Workbench	workbench	2	app	Batch query app details
DevDoc	devdoc	1	article	Search platform docs and error codes

86 commands across 12 products. Run dws --help for the full list, or dws <service> --help for subcommands.

Coming soon

doc (documents) · mail (email) · minutes (AI transcription) · drive (cloud drive) · conference (video) · tb (Teambition) · aiapp (AI apps) · live (streaming) · skill (marketplace)

Security by Design

dws treats security as a first-class architectural concern, not an afterthought. Credentials never touch disk, tokens never leave trusted domains, permissions never exceed grants, operations never escape audit — every API call must pass through DingTalk Open Platform's authentication and audit chain, no exceptions.

For Developers

Mechanism	Details
Encrypted token storage	PBKDF2 + AES-256-GCM encryption, keyed by device physical MAC address; cross-platform Keychain/DPAPI integration provides additional protection — tokens cannot be decrypted on another machine
Input security	Path traversal protection (symlink resolution + working directory containment), CRLF injection blocking, Unicode visual spoofing filtering — prevents AI Agents from being tricked by malicious instructions
Domain allowlist	DWS_TRUSTED_DOMAINS defaults to *.dingtalk.com; bearer tokens are never sent to non-allowlisted domains
HTTPS enforced	All requests require TLS; HTTP only permitted for loopback during development
Dry-run preview	--dry-run shows call parameters without executing, preventing accidental mutations
Zero credential persistence	Client ID / Secret used in memory only — never written to config files or logs

For Enterprise Admins

Mechanism	Details
OAuth device-flow auth	Users must authenticate through an admin-authorized DingTalk application
Least-privilege scoping	CLI can only invoke APIs granted to the application — no privilege escalation
Allowlist gating	Admin confirmation required during co-creation phase; self-service approval planned
Full-chain audit	Every data read/write passes through the DingTalk Open Platform API — enterprise admins can trace complete call logs in real time; no anomalous operation can hide

For ISVs

Mechanism	Details
Tenant data isolation	Operates under authorized app identity; cross-tenant access is impossible
Skill sandbox	Agent Skills are Markdown documents (SKILL.md) — prompt descriptions only, no arbitrary code execution
Zero blind spots	Every API call during ISV–dws skill orchestration is forced through DingTalk Open Platform authentication — full call chain is traceable with no bypass path

Found a vulnerability? Report via GitHub Security Advisories. See SECURITY.md.

Reference & Docs

• Reference — environment variables, exit codes, output formats, shell completion
• Architecture — discovery-driven pipeline, IR, transport layer
• Changelog — release history and migration notes

Contributing

See CONTRIBUTING.md for build instructions, testing, and development workflow.

License

Apache-2.0