Primary Purpose:
DingTalk Workspace CLI (dws) is a command-line tool designed to manage DingTalk workspace operations efficiently. It serves as an interface for developers and AI agents, enabling seamless interaction with DingTalk's ecosystem.
Key Features:
For Humans: The tool offers intuitive commands such as --help for usage guidance, --dry-run to preview actions without execution, and flexible output formats (-f table/json/raw) for data presentation.
For AI Agents: It provides structured JSON responses and built-in Agent Skills, facilitating integration with AI tools like Claude Code and Cursor.
For Enterprise Admins: The tool features a zero-trust architecture with OAuth device-flow authentication, domain allowlisting, and least-privilege scoping, ensuring robust security.
Audience & Benefit:
Ideal for developers seeking efficient workspace management, AI agents requiring direct interaction, and enterprise admins prioritizing secure access. Benefits include enhanced productivity through command-line efficiency, secure access mechanisms, and seamless integration with AI tools, all underpinned by a zero-trust security model.
This tool can be installed via winget, offering a straightforward setup process for users.
README
DingTalk Workspace CLI (dws)
dws — DingTalk Workspace on the command line, built for humans and AI agents.
> [!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.
>
>
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
The installer ships skills in one of two layouts. CLI commands (dws aitable ..., dws calendar ...) are identical in both modes — only the agent-side skill layout differs.
> 🧪 multi is currently EXPERIMENTAL / preview. All product-scoped skills pass the dispatch verifier, but interface, naming and cross-skill references may change in future releases. For production / shared environments, prefer mono. File issues if you hit problems.
TTY install (download then run): curl -O .../install.sh && bash install.sh — prompts 1) mono 2) multi (default 1).
Override via env: DWS_SKILL_MODE=multi curl -fsSL ... | sh.
Switch later: dws skill setup --mode multi (or --mode mono) — re-run any time.
Other install methods
npm (requires Node.js (npm/npx)):
npm install -g dingtalk-workspace-cli
Install the latest beta:
npm install -g dingtalk-workspace-cli@beta
Homebrew (macOS / Linux):
brew tap DingTalk-Real-AI/dingtalk-workspace-cli https://github.com/DingTalk-Real-AI/dingtalk-workspace-cli.git
brew install dingtalk-workspace-cli
> The Formula lives in this repository, so the first tap command must include the explicit repository URL. Afterwards, use brew upgrade dingtalk-workspace-cli normally.
Install the keg-only Homebrew beta without replacing the stable Formula:
brew install dingtalk-workspace-cli-beta
$(brew --prefix dingtalk-workspace-cli-beta)/bin/dws version
To make the beta dws the default for the current shell, prepend $(brew --prefix dingtalk-workspace-cli-beta)/bin to PATH.
> macOS users: If you see "cannot be opened because Apple cannot check it for malicious software", run:
> bash > 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
Static endpoint data is generated from the Wukong baseline and committed in this
repository under internal/syncdata, so source builds do not require a sibling
data checkout.
> Requires Go 1.25+. Use make package to cross-compile for all platforms (macOS / Linux / Windows x amd64 / arm64).
China mirror
For users in mainland China, the following channels avoid GitHub network issues. By default (without setting these environment variables) the installer pulls from GitHub.
DWS_GITEE_REPO=DingTalk-Real-AI/dingtalk-workspace-cli curl -fsSL https://gitee.com/DingTalk-Real-AI/dingtalk-workspace-cli/raw/main/scripts/install.sh | sh
> With DWS_GITEE_REPO set, the installer resolves the latest version and every release asset (binary, checksums, skills) from the Gitee API instead of GitHub. If it is unset, installation defaults to GitHub.
> npmmirror automatically syncs public packages from the public npm registry, so this works directly in China.
3. Skills only (Gitee mirror):
DWS_GITEE_REPO=DingTalk-Real-AI/dingtalk-workspace-cli curl -fsSL https://gitee.com/DingTalk-Real-AI/dingtalk-workspace-cli/raw/main/scripts/install-skills.sh | sh
> With DWS_GITEE_REPO set, install-skills.sh resolves the version and skills package from Gitee; it also auto-falls back to the Gitee mirror when GitHub is unreachable.
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 stable release versions
dws upgrade --beta # upgrade to the latest beta pre-release
dws upgrade --check --beta # check the beta track without installing
dws upgrade --list --beta # list beta pre-release versions
dws upgrade --version v1.0.7 # upgrade to a specific version
dws upgrade --version v1.0.8-beta.1 # upgrade to a specific beta version
dws upgrade --rollback # rollback to the previous version
dws upgrade -y # skip confirmation prompt
By default, dws upgrade follows the stable release track. Use --beta only when you explicitly want the newest GitHub pre-release build.
Six-channel post-release verification
Maintainers and release validators can run the release-quality smoke checks for curl, PowerShell, npm stable, npm beta, Homebrew, and dws upgrade:
git clone https://github.com/DingTalk-Real-AI/dingtalk-workspace-cli.git /tmp/dws-verify
cd /tmp/dws-verify/verify
bash verify-all-channels.sh
The verifier uses isolated directories and does not replace the dws on the current PATH. It reports PASS, FAIL, and SKIP; a platform skip is not a pass and must be covered on the matching host. See verify/README.md for the platform matrix.
How it works
The upgrade process follows a two-phase atomic flow to ensure consistency:
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.
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 available stable release versions with changelogs
--beta
Use the beta pre-release track for upgrade, --check, or --list
--version
Upgrade to a specific version (e.g. v1.0.7 or v1.0.8-beta.1)
--rollback
Rollback to the previous backed-up version
--force
Force reinstall even if already on the latest version
Credentials are securely persisted after first login (Keychain). Subsequent runs auto-refresh tokens.
Multiple organizations (profiles)
dws can stay logged in to several DingTalk accounts at once, including multiple accounts in the same organization. A profile is uniquely identified by corpId:userId; the current profile decides which identity a command runs as.
dws auth login # add or refresh one account
dws profile list # list every logged-in account
dws profile switch # persistently switch; use - to toggle back
dws profile switch ":" # friendly input; names must be unique
dws --profile contact user search --query "..." # use that org's explicitly recorded current account
dws --profile contact user search --query "..." # use one exact account without changing the default
Selectors support corpId:userId, corpId:userName, corpName:userId, and corpName:userName. Friendly names are input aliases only; use the stable profile value returned by profile list for automation. Duplicate organization or account names fail with explicit corpId:userId candidates. If an organization has multiple accounts but no recorded current account, --profile fails instead of choosing the first or most recently used account.
currentProfile, previousProfile, and per-organization defaults are stored as exact identities. primaryProfile remains in JSON only for compatibility and is not used for selection. profile list reads status and expiry from each real identity Token without refreshing it. auth logout --profile removes all local accounts in that organization; an exact selector or local profile name removes one account.
Cross-org reads are orchestrated by the agent rather than a built-in --all-orgs: list profiles, group by corpId, and use the unique isOrgCurrent=true account for each organization. If a multi-account organization has no default, ask the user to choose an account first. Writes default to the current account — confirm both organization and account before cross-org writes.
On macOS, an unreadable registered token slot blocks a new OAuth login rather than risking a mixed Keychain/file-DEK state. If normal terminal commands can still read the login while a sandbox using DWS_DISABLE_KEYCHAIN=1 cannot, migrate the legacy and profile auth entries without exposing tokens:
The migration validates every selected auth ciphertext before writing, ignores unrelated application secrets, and can be rerun after an interrupted commit. If validation identifies genuinely damaged ciphertext, remove only the affected account with dws auth logout --profile , or all accounts in one organization with --profile , then log in again. Use dws auth reset only when you intend to discard every local profile.
Migrate auth between Linux sandboxes
Copying only ~/.dws/app.json does not carry the refresh token; access tokens expire after ~2 hours. Use the official export/import flow:
# Sandbox A (already logged in)
dws auth export -o /tmp/dws-auth.tar.gz
# Or for copy/paste: dws auth export --base64 -o /tmp/dws-auth.b64
# Sandbox B
dws auth import -i /tmp/dws-auth.tar.gz
# Or: dws auth import -i /tmp/dws-auth.b64 --base64
dws auth status # confirm "Refresh Token: valid"
The bundle includes the encrypted keychain under ~/.local/share/dws-cli (with auth-token.enc and dek) plus required ~/.dws config files.
Windows export and import are intentionally rejected before credentials or
bundles are read: Windows stores credentials as DPAPI-protected HKCU Registry
values, and the current file-DEK bundle has no safe DPAPI-to-portable conversion.
Quick Start
dws contact user search --query "engineering" # search contacts
dws calendar event list # list today's calendar events
dws doc search --query "quarterly" # search DingTalk Docs
dws minutes list mine # list AI meeting notes I created
dws drive list # list DingTalk drive files
dws todo task create --title "Quarterly report" --executors "" # create a todo (replace )
dws todo task list --dry-run # preview without executing
> Full command list: docs/command-index.md — all commands with descriptions and when-to-use guidance.
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 "" --yes
# Use --dry-run to preview operations (safe execution)
dws contact user search --query "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}'
Command Help and Schema
Use Cobra help and Schema for different parts of the command contract:
dws --help is the source of truth for whether a command exists and which flags the binary accepts.
dws schema "" is the Agent contract for command selection, parameter mappings and constraints, risk, and confirmation semantics.
If Help and Schema disagree, treat it as contract drift: pass only flags accepted by Cobra and use the more conservative safety semantics.
Schema describes commands; it does not read or search DingTalk business data. Execute the real product command after discovery.
# Confirm that the command exists and inspect accepted flags
dws aitable record query --help
# Discover within a product, then inspect the selected leaf contract
dws schema aitable
dws schema "aitable record query"
# Execute the real business query
dws aitable record query --base-id BASE_ID --table-id TABLE_ID --limit 10
dws schema --all exports the complete contract for tooling, CI, audits, and compatibility baselines. Agents should prefer product/group discovery followed by a leaf query to avoid loading the full Catalog into context.
Agent Skills
The repo ships a complete Agent Skill system under skills/, organized into two layouts:
skills/multi/ — per-product skills (dingtalk-aitable/, dingtalk-calendar/, dingtalk-chat/, ...), each with its own SKILL.md. 🧪 EXPERIMENTAL / preview — see banner in each multi SKILL.md for caveats.
Shared reviewed inputs for Schema generation live separately under internal/cli/schema_hints/. They are not Agent Skills and are excluded from binaries and release skill bundles.
After installing, AI tools like Claude Code / Cursor can operate DingTalk directly through natural language:
# Install skills into current project (defaults to mono)
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).
>
> China users: prefix DWS_GITEE_REPO to use the Gitee mirror — see China mirror.
Switching or re-installing with dws skill setup:
# Interactive: prompts for mode + target agents
dws skill setup
# Install mono skill to every detected agent home (claude / cursor / codex / opencode / qoder)
dws skill setup --mode mono --target all --yes
# Install multi skills to a single agent home
dws skill setup --mode multi --target cursor --yes
# Point at a local source tree (e.g. a fork or work-in-progress)
DWS_SKILL_SOURCE=/path/to/skills dws skill setup --mode multi
Flag
Values
Description
--mode
mono | multi
Skill layout; defaults to interactive prompt
--target
all | claude | cursor | codex | opencode | qoder
Where to install; all covers every detected agent home
--source
path
Local source directory (overrides bundled skills)
--yes
—
Skip confirmation prompts
Env vars: DWS_SKILL_MODE=mono|multi (also honored by install.sh / install.ps1), DWS_SKILL_SOURCE=.
Per-product command reference (aitable, chat, calendar, etc.)
Intent guide
skills/mono/references/intent-guide.md
Disambiguation for confusing scenarios (e.g. report vs todo)
Global reference
skills/mono/references/global-reference.md
Auth, output formats, global flags
Error codes
skills/mono/references/error-codes.md
Error codes + debugging workflows
Recovery guide
skills/mono/references/recovery-guide.md
RECOVERY_EVENT_ID handling
Ready-made scripts
skills/mono/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
Personal Event Subscription — real-time DingTalk messages for event-driven agents
dws event consume subscribes as the currently logged-in user over a managed Stream WebSocket and emits each event as one NDJSON line on stdout. The public catalog covers scoped and all one-to-one/group messages, specified senders, read/recall/reaction events, and group title/disband lifecycle events.
The default ndjson, json, and pretty output preserves the transport envelope (type, event_type, string data, and headers) for existing scripts; compact retains its existing processor. Add --flatten to emit the stable top-level business fields used by Agent workflows. --format controls JSON serialization; --flatten controls the data structure and cannot be combined with -f raw or --debug-raw-events.
> Prerequisite: run dws auth login. Personal identity is resolved from the OAuth token and cannot be supplied through command-line identity flags.
For an event-focused installation, use the official convenience installer:
curl -fsSL https://raw.githubusercontent.com/DingTalk-Real-AI/dingtalk-workspace-cli/main/scripts/install-event.sh | sh
# Inspect the public personal event catalog and schema
dws event list
dws event schema user_im_message_receive_o2o --flatten
# Listen for messages that mention the current user
dws event consume user_im_message_receive_at --flatten -f ndjson
# Listen for one-to-one messages with a specified user
dws event consume user_im_message_receive_o2o --user --flatten -f ndjson
# Listen by openDingtalkId (external contact, bot, or cross-organization identity)
dws event consume user_im_message_receive_o2o --open-dingtalk-id --flatten -f ndjson
# Listen for messages in a specified group
dws event consume user_im_message_receive_group --group --flatten -f ndjson
# Listen for all one-to-one or all group messages
dws event consume user_im_message_receive_o2o_all --flatten -f ndjson
dws event consume user_im_message_receive_group_all --flatten -f ndjson
# Listen for a specified group's title changes, member changes, or disband event
dws event consume user_im_group_updated --group --flatten -f ndjson
dws event consume user_im_group_member_added --group --flatten -f ndjson
dws event consume user_im_group_member_exited --group --flatten -f ndjson
dws event consume user_im_group_disbanded --group --flatten -f ndjson
# Listen for multiple events for the same user in one process
dws event consume \
user_im_message_receive_o2o \
user_im_message_read_o2o \
user_im_message_recall_o2o \
--user \
--flatten \
-f ndjson
# Inspect local consumers and cancel a subscription
dws event status
dws event stop
For one-to-one and specified-sender events, use exactly one target identity: --user for an internal userId, or --open-dingtalk-id for an openDingtalkId. The CLI does not infer or convert between these identity types.
Feature
Details
Managed lifecycle
consume creates or reuses the personal subscription; stop cancels it and cleans local state
Shared connection
Consumers for the same user share one local bus and cloud connection
Multi-event process
One consume process can listen for compatible events for the same target while retaining one subscription per event
Subscription isolation
Normal consumers match both event type and subscribe_id
Agent-friendly output
Stream events are written to stdout as NDJSON; status and diagnostics use stderr
Observability
status shows remote subscriptions, the personal bus, and local consumers
Cross-platform
Unix Socket on macOS/Linux, Windows Named Pipe on Windows
See skills/multi/dingtalk-event/SKILL.md for the Agent workflow and supported event parameters.
Raw API Access — call any DingTalk OpenAPI directly
dws api lets you call any DingTalk OpenAPI without an SDK. Tokens are automatically acquired and refreshed.
> Prerequisite: Must login with your own app credentials (see Custom App mode). Encrypted tokens from MCP default-credential login are not supported for raw API calls.
# Login (first time only)
dws auth login --client-id --client-secret
# === api.dingtalk.com ===
# List all enterprise apps
dws api GET /v1.0/microApp/allApps
# Search users (POST + JSON body)
dws api POST /v1.0/contact/users/search \
--data '{"queryWord":"engineering","offset":0,"size":10}'
# === oapi.dingtalk.com ===
# Get user details (use --base-url to specify domain)
dws api POST /topapi/v2/user/get \
--base-url https://oapi.dingtalk.com \
--data '{"userid":""}'
# Or use the full URL directly
dws api POST https://oapi.dingtalk.com/topapi/v2/user/get \
--data '{"userid":""}'
# === General ===
dws api GET /v1.0/microApp/allApps --page-all # auto-paginate
dws api GET /v1.0/microApp/allApps --dry-run # preview request
dws api GET /v1.0/microApp/allApps --jq '.agentId' # jq filtering
Feature
Details
Dual-form auto-detection
Automatically selects api.dingtalk.com (header auth) or oapi.dingtalk.com (query-param auth) based on URL
Automatic token management
App-level accessToken is fetched on first call, cached while valid, auto-refreshed on expiry
Domain allowlist
Only api.dingtalk.com and oapi.dingtalk.com permitted — prevents token leakage
Auto-pagination
--page-all iterates all pages. --page-limit caps the maximum (default 10, set to 0 for unlimited, hard cap at 500 to prevent infinite loops)
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 --query "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 "dev app create" --jq '.tool.required'
# Return only specific fields
dws aitable record query --base-id BASE_ID --table-id TABLE_ID --fields invocation,response
Schema Introspection — Agent command discovery and execution contracts
dws schema aitable # discover product commands
dws schema "aitable record query" # view the selected leaf contract
dws schema "aitable record query" --jq '.tool.required' # view required fields
dws schema --all # full export for CI/audit/baselines
Pipe & File Input — read flag values from files or stdin
> Note: @ is treated as the @ file-injection prefix only when the next character is an ASCII path-shaped character (A-Z / a-z / 0-9 / . / / / ~ / _ / -), or @- for stdin. Chat-bot payloads like --text "@所有人 周报" or --text "@张三 看一下" pass through unchanged, so literal mentions reach the API as-is.
DingTalk bot — connect a robot to your local AI
dws dev connect bridges a DingTalk robot to a local AI CLI (Claude Code / Codex / opencode / Qoder / Gemini, or any tool via --agent-cmd): @-mention the bot in a chat and it answers using your local agent, keeping per-conversation multi-turn memory.
dws dev connect --channel auto --unified-app-id
> --unified-app-id resolves clientSecret at runtime via dev app credentials get,
> so the secret never appears in argv (ps / journald / shell history). The
> legacy --robot-client-id --robot-client-secret still works but
> the CLI will warn you.
In-chat session commands (send the bare command as the whole message — no agent turn, no tokens):
Command
Effect
/new (aliases /start, /reset)
Start a fresh session; the previous one is left intact (resumable where the agent supports it)
/clear
Wipe the current session — disposed through the agent's real session op (opencode issues DELETE /session/:id); channels whose agent exposes no delete primitive fall back to a reset
See docs/robot-quickstart.md for the full 4-step walkthrough (install → create robot → connect → add to a group).
Key Services
Service
Command
Capabilities
Contact
contact
Look up users, departments, labels, roster profiles and dismissals; create enterprises and enterprise accounts; invite employees
Chat / IM
chat (im)
Send / reply / search messages, group & member management, bot & webhook messaging, reactions, recall
Calendar
calendar
Events CRUD, attendees, meeting rooms, free/busy & time suggestions
Todo
todo
Create / list / update / complete tasks and comments
Approval
oa
Approve / reject / revoke / transfer; query pending / initiated / CC instances and forms
Attendance
attendance
Clock-in records, shifts, summaries, group rules (read-only)
Search the Open Platform docs and diagnose API errors
AI Search
aisearch
Enterprise people search by name / dept / role / duty / supervisor / phone / job-number
Live
live
List my live streams
Raw API
api
Call any DingTalk OpenAPI directly, with managed app-level token
> Full command listing with usage scenarios: docs/command-index.md. Run dws --help for the top-level tree, or dws --help for any service's subcommands.
> Note on chat bot: bot capabilities (send-by-bot / recall-by-bot / add-bot / send-by-webhook / bot search) are merged into the relevant chat subtrees (e.g. dws chat message send-by-bot, dws chat group members add-bot) so the agent-facing command surface stays flat and discoverable. There is no longer a separate top-level bot product.
Coming soon
conference (video meetings)
Multi-skill mode (experimental) — per-product skills under skills/multi/; opt in via dws skill setup --mode multi
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
