Feature Requests

Platforms like Claude have popularized "skills" — structured, multi-file AI instruction packages that go well beyond a basic system prompt. A skill bundles a core instruction file, reference documents the model loads on demand, supporting assets, and a trigger description that controls when it activates. Users are building skills for everything from technical playbooks to domain-specific mentors to operational runbooks, and this pattern is becoming the standard way power users encode reusable expertise into AI. Currently, there's no way to import these into Hatz. Users who've built skill libraries on other platforms have to manually recreate them as separate Apps or Agents, losing the multi-file structure and progressive context loading in the process. For MSPs onboarding teams onto Hatz, this creates unnecessary migration friction and duplicated effort. The core ask is a skill import pipeline that accepts a standard skill package (ZIP with a SKILL.md at root + optional reference files and assets) and converts it into Hatz-native Workshop items — mapping instructions to Agent system prompts, reference files to knowledge sources, and descriptions to Workshop metadata. Unsupported components would be flagged during import so the user knows what needs attention. The bigger unlock is skill routing in Chat. Once skills exist as first-class objects, Hatz could evaluate a user's message against available skill descriptions and automatically load the right expertise context — no manual app or agent selection required. This would transform Chat from a general-purpose LLM interface into a context-aware assistant that knows which domain knowledge to pull in based on the question. Long-term, this naturally extends into multi-tenant skill distribution and a community marketplace — the same management model Hatz already does well with Apps and Agents, applied to portable, versioned expertise packages that MSPs can build once and deploy across all their tenants.

Implement "Project" folders that function as a unified workspace, similar to Claude projects. - Folder-Level Knowledge: Allow users to upload "Project Files" (PDFs, docs, code) that are automatically indexed and accessible to every chat within that folder. Custom Instructions: Set a "Project Brief" or system prompt that applies to all chats in the folder, eliminating the need to repeat context. Cross-Chat Awareness: Enable the AI to reference context or conclusions from previous chats within the same project folder.

Not sure if I'm misunderstanding the instructions, but it seems to require creating an api user with a designated set of permissions and then sharing the credentials to everyone who needs to add the connectwise integration. So not only are the permissions the same for everyone, the creds are also shared with everyone. Seems very sketchy, unfriendly and insecure. Would expect some kind of filter to talk to Connectwise using my existing permissions not an admins level of access.

I’d like to request a feature that would allow users to attach previous chats as context sources in a new chat. Right now, conversations are isolated with no memory function, which makes it difficult to build continuity across projects. A simple solution would be to let users select one or more past chats and include them as reference material, similar to how files can be attached. This would improve workflow efficiency, reduce repetitive prompting, and allow users to build structured context hubs inside the platform. Instead of re-explaining strategy, tone, audience, or prior decisions, the AI could reference existing discussions and provide more aligned, strategic outputs. For example, I could create a “Marketing Context” chat containing brand voice, target audience, and campaign strategy. Later, when starting a new “Facebook Ads” chat, I would attach the Marketing Context chat as a source so the AI already understands the background and can generate ads ideas that stay consistent with the overall strategy. And most importantly this needs to be a dynamic link so context can be updated overtime. My request is different from the Memory function on the roadmap because it does not require persistent, system-level memory across sessions. Instead, it proposes a lightweight, user-controlled method of attaching specific past chats as context sources to a new conversation. Rather than automatically retaining evolving user data, this approach treats prior chats as knowledge blocks that can be selectively reused when relevant. This avoids full memory persistence while still enabling continuity, making it simpler to implement and more targeted toward workflow organization rather than long-term conversational memory.

Workflows were to be apps that can be strung together. If you already have several apps that perform the steps you want for a full workflow, you have to recreate them in the workflow. When creating a workflow, we can [+ prompt section], how about a [+ App ID] (select our app name or id) and then our app becomes part of the flow. Use case for his is there are 6 apps that are used with each other to analyze data for a report - we use a combination of these 6 apps monthly. A different person has created each of the apps. Sometimes you would use Apps 1, 2, 3, 4, 5, and 6. Other times you would only need apps 2, 4, and 5. While other times you would need apps 1 and 6 only. The first prompt (prompt 0) could be your selection of which ones you needed and the login in the workflow would take this input along with your document (any other input) and begin the process by calling the apps you selected. This is done today using power automate manual run with inputs and then the power automate flow calls the appropriate app IDs via API, gets the output and passes to the next app id, etc. Will be great when an entire Workflow can be automatically launched via the workflow ID just the like the apps are with their AppID.