IM Channel Security Enhanced, DingTalk User Matching, Memory & Skill Self-Evolution

Improvements

• IM Channel Security Enhanced: IM sessions now enforce permission boundaries, ensuring conversations and commands stay within allowed workspaces for safer Agent operations.
• DingTalk Channel User Matching: The DingTalk channel now supports nickname-based identity resolution and message filtering for more accurate user matching.
• Memory & Skill Self-Evolution: Multiple improvements to the memory and Skill self-evolution pipeline for greater stability and efficiency.

IM channel expansion, scheduled automation, and stronger session reliability

What's New

• More IM Channels: Wakers can now connect through Feishu, WeChat, and WeCom Bot, in addition to the existing DingTalk channels.

• Skill Marketplace Search: The CLI and console now support searching and filtering Skill Marketplace entries more easily.

Improvements

• IM Channel Experience: IM replies now handle streaming, media, pairing/open-access policies, and rapid consecutive messages more reliably.
• Session Recovery: Console sessions recover better from SSE reconnects, daemon restarts, gateway fallback, and idle/restart windows.
• Memory System: Project memory now supports custom sections, improved locale initialization, and more accurate usage-state attribution.

Issue Fixes

• Fixed IM channel replies being lost when the same sender sends multiple messages quickly.
• Fixed worker/model errors being silently dropped in IM channels; users now receive clearer failure messages.
• Fixed SSE reconnect scenarios that could leave the console stuck in a thinking or pending state.
• Fixed duplicate output rendering after reconnect or event replay.
• Fixed stop-button behavior when a session requires restart.
• Fixed quota-exceeded errors so they render as friendly user-facing cards.
• Fixed oversized image reads that could trigger BAD_REQUEST failures when many images are attached.
• Fixed Skill reference completion to use the correct Skill display name.
• Fixed other known issues.

Multiple Wakers can now collaborate within the same project; Memory & Skills upgrades

What's New

• Public Projects: You can now create "public projects," letting all Wakers under a single account share the context and artifacts within a project.
• GitHub Triggers: Triggers now fire correctly even for repositories where the current account is not a collaborator.

Improvements

• Skill Management: Streamlined the workflow, with the accompanying Skill templates polished to match.
• Memory Self-Evolution: Memory now evolves automatically based on usage, and templates adapt to the system language.

Bug Fixes

• After logging out and signing back in with the same account, digital employees no longer show up empty in the console or in qoderwake waker list.
• On macOS, a failed "launch at startup" registration no longer blocks the rest of the installation.
• Fixed a scenario where GitHub event triggers were previously failing.
• Fixed other known issues.

0.0.10

QoderWake is now open for public beta.

QoderWake is an AI digital worker runtime platform that lets you build a team of "digital workers" (Wakers) on your local machine. Each worker has a role, a name, a persona, and specialized skills — ready to chat or get work done whenever you need them.
This public beta supports macOS (13+) and mainstream Linux distributions. Windows support is not yet available.

AI Employee

• Create multiple workers, each with independent identity, memory, skills, and workspace
• Built-in role templates (Software Engineer, QA, Product Manager, Data Analyst, Content Operations, etc.), with full support for custom roles
• Assign tasks through natural language conversation, with real-time visibility into thinking process, code output, and tool invocations
• Workers proactively ask for approval before performing sensitive operations, with three-tier permission policies (Allow / Ask / Deny)

Automated Triggers

• Multiple trigger types including scheduled, GitHub Webhook, and more
• Run history, calendar view, monthly statistics, and execution limits
• "Test pull" before saving — read-only validation of data source connectivity

Skills & Tool Integration

• Built-in skills ready out of the box, one-click install from the skill marketplace, custom skill uploads, and automatic skill distillation
• MCP protocol support for connecting external tools, with full OAuth 2.0 authorization flow
• Fine-grained on/off control at the individual tool level

Long-term Memory

• Persistent memory across sessions, organized by sections (user preferences, project knowledge, key decisions, etc.)
• Personal memory (per worker) and project-level shared memory
• Built-in semantic search, daily auto-consolidation, version snapshots and rollback

Multi-channel Access

• Web Console: Local visual management interface covering all operations, with dark theme and language switching
• IM Channels: Connect workers to IM platforms (e.g. DingTalk) for direct interaction in group chats or private messages
• CLI: Full-featured command-line tool including process management, diagnostics, and backup/restore