Feature Requests

Possibility to add/use skills such as Claude Cowork, Codex, OpenClaw, etc. So that you can also improve certain working conditions of agents and also combine them with other workflows and tools that you may already be using, such as Claude Cowork or Codex.

I’d love to see a feature in ClickUp AI similar to ChatGPT’s “Custom Instructions.” Instead of re-selecting a saved prompt every time, I want to define my AI style, tone, goals, and contextual preferences once—and have them automatically applied across all interactions with ClickUp Brain and AI Agents (in tasks, chat, etc.). Why this matters: • It’s key for creative brainstorming and maintaining consistent tone across work. • Saves time from having to reapply prompts. • Makes AI truly feel like an extension of my workflow and voice. Bonus feature idea: Allow workspaces to upload contextual documents (PDFs, strategy docs, style guides) that AI can reference persistently.

It would be great to be able to use AI to quickly generate clean, and cool looking whiteboards. Currently the AI Brain in whiteboard only generates images, and they are all cut off. Instead, i'd like to ask it to "pull all tasks from this board as headers with unique colors, and put descriptions as sub sticky notes". That way I could create a quick org chart, or view of specific tasks quickly, efficiently, and in a cool looking way. On some other tools this involves importing .json and .csv data which most LLM/AI tech can work with. If I could simply copy and paste in such formats and choose my template look or describe it then it would save tons of time in the long run. No current workaround to generate formatted whiteboard material. I can almost get there by importing .csv or .json as tasks using import or AI Brain. Then I have to drag in each tasks. However, once I try to do any whiteboarding the AI just generates faulty images instead of editable structures in a useful format. Final goal, open whiteboard, ask AI to pull in tasks I've already got of a tag type from X project, tell it to build a color coded structure using bubbles at the top and stickies below it (or from template example), and presto it builds a structure. Example attached. I've use a different tool and AI to do this with prompts so it's very possible. Giving users a few preset prompts and styles would solidify this as useful for all sorts of purposes in the whiteboard tool.

The AI notetake lists the date in US format (MM/DD/YYY). It would be good to choose DD/MM/YYYY as most of the world uses that format over the US one.

It would be very useful to have access to teams via the MCP.

Problem: The current AI Usage dashboard provides a high-level overview but lacks the necessary granularity for effective resource management. Currently, while Super Agents have a clear breakdown, other high-consumption features like Autopilot Agents, AI Cards, AI Fields, and AI Tasks only show aggregate costs. Furthermore, the dashboard prioritizes monetary value (USD) over the actual credit count, and lacks historical month-over-month reporting for trial/bonus pools. Proposed Solution: I suggest a comprehensive update to the AI Usage interface to include: Dual Metric Visibility: Display "Credits Consumed" alongside "Monetary Cost (USD)" as standard columns. Relying on tooltips (hovering) makes it difficult to compare usage across different workflows quickly. Granular Breakdown for All AI Features: Extend the "Super Agent" level of detail to Autopilot Agents, AI Fields, and AI Cards. We need to see: Which specific Agent/Automation triggered the usage. The location (List/Folder/Space) of the trigger. The User/Member responsible for the action. Historical Data & Period Filtering: Ability to filter usage by previous months or custom date ranges. Currently, the breakdown resets on the 1st of each month, making it impossible to audit past consumption patterns once the month ends. Audit Log Integration: A dedicated "AI Audit Log" or better filtering in the existing Automation Audit Log to specifically isolate AI-related consumption events. Why this is important: As a decision-maker, I cannot confidently purchase additional AI Credit packs or add-ons without understanding exactly how our current credits are being spent. Clear visibility is the bridge between a "trial" and a "paid" commitment. Better governance tools will help teams optimize their workflows and scale their AI usage responsibly.

Clickup KI Voice to Text etc. generally charge above a fixed credit limit without feeling like 100 separate packages. So it feels like that despite the fact that you have the Clickup Business version and the “All in AI” package, you still have to add additional packages and that is super confusing and then it feels like functions are being removed from the packages over time. Wouldn't it be much easier simply to set up and bill everything on a fixed credit sum per plan and then every user can decide for themselves which functions they use and where how much. Some go more towards AI superagents, others more voice-to-text, etc. But in the end, you have a fixed credit sum with every license that is fair for all sides. I mean AI usage also costs ClickUp a bit about the models and we just passed it through and with z.B. 25% surcharge simply continues to charge us end users. But that would make it more flexible and easier what you spend where now and what is included where and then you can simply flexibly upgrade the credit limit flexibly if you need and/or scale more. Simply with every new user/employee that you integrate with a paid version, the company-wide credit limit increases by sum X and it is still consumed as necessary across all channels. With the AI Notetaker, Clickup z.B is very good. Because it is simply at the hour limit and regardless of whether 1 employee then consumes 80% of it alone because the others are less in meetings, it doesn't matter at all for ClickUp. So I would say it would also be as transparent as possible for all sides, fair and would cause less frustration as to what is already behind an older payment barrier, etc.

AI agents currently only have access to public lists - this prevents us from building "AI Agenta" of any kind in our workspace as our lists are all private and client facing.

Seems straightforward, I want to be able to create a list using AI