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While working with a selection of time seies in canvas, I would like the ability to select a number of these to send to canvas in one action for further analysis. The way it works now I can send one time series to canvas and then have to search for the other time series i want to add to charts manually.

Currently, the search function starts only after entering a keyword and pressing Enter.Would it be possible to support incremental search, where results are updated dynamically as the user types?I believe that the “Data explorer” in Data Fusion (prior to the current Search feature) used incremental search.With incremental search, users can see results immediately, which makes it easier to try different keywords—especially for users who do not remember exact equipment names or file names. It also reduces the need to retype words.In addition, with the current behavior, there are cases where pressing Enter does not seamlessly trigger the search. In such situations, users need to click the search box again before pressing Enter, which can be slightly frustrating.On the other hand, I understand that incremental search may increase system load and could have performance implications. If introducing incremental search negatively impacts overall search performance, then the current implementat

When searching for assets or timeseries, there’s a feature in the detail tab that shows a list of Canvases where they’re used.↓Would it be possible to extend this to also show a list of Charts that use a given timeseries?Some example use cases:・Charts tend to be created in large numbers, so it’s sometimes hard to remember which Chart was used to create which visualization. Being able to trace Charts from a timeseries would make it much easier to reuse existing work.・Especially for scheduled calculation tags, it can be difficult to find the Chart where the original calculation logic is defined. It would be really helpful if we could trace back from the timeseries to the corresponding Chart to review the calculation.

I would like to submit a product idea regarding Charts calculations.Currently, calculations in Charts are performed only within the time range that is visible on the screen. We would like to request an enhancement that allows users to define a specific calculation period (i.e., start and end points) directly within the calculation formula.For example, when using the “sample average” operator, the result is calculated only based on the data currently displayed. As a result, the calculated value changes when the user scrolls or shifts the visible time range.We would like to be able to calculate metrics such as average values over a fixed, explicitly defined time range, including data outside of the current view. This would ensure that the result remains consistent and is not affected by scrolling or changes in the displayed window.We believe this functionality would significantly improve usability and enable more stable and meaningful analysis.Thank you for your consideration.

Currently when plotting Work orders and Permit to work on Charts is difficult to see the difference. The colors are too close. It would be great to have different colors there to choose from or at least make more contrast on the default ones.

Hi!The Q2 Product Release describes the new Atlas Skills feature as “reusable, lifecycle-managed assets”. In my experience the current designmakes skills very hard to reuse makes it impossible to manage their lifecycleReusing skillsTo reuse skills means to me that I can add skills to my agents that have been authored by someone else for another use case. The agent builder in CDF lets me add new skills in two different ways:Search among the skills already added to the agent Upload a skill markdown fileSo the only way to reuse a skill is to download a skill from another agent and re-upload it to my agent? There is no lifecycle management here. Skill versions will become stale very quickly. You have no idea whether your skill is up to date or not.There is no repository of skills where I can search for something relevant to me. I have no idea what skills have already been created. There is no way to inspect a skill once it has been added to my agent (I need to download it locally). Is ther

SummaryThe Cognite Toolkit forces an agent to be defined as a single monolithic YAML file — config (name, id, description, LLM), instructions, the skills list (external IDs to pre-existing skills), and tools (including inline Python source) all in one file. We need a modular, file-structure-based agent definition that the toolkit parses at deploy time, so skills and Python tools can live as standalone, testable, version-controlled source files that are created and attached to the agent automatically on deploy. Pain pointsThe monolithic YAML blocks normal DevOps practice (isolation, unit tests, review, reuse). Concretely:Skills cannot be deployed from source. A skill should be an isolated directory containing a SKILL.md (possibly other supporting files as well, as per the emerging standard). But the toolkit references a skill only by external ID — the skill must already exist in CDF. There is no way to point the toolkit at a SKILL.md and have it create and attach the skill on the fly du

Today it is possible to specify the unit of a property of a View, enabling unit conversion on consumption (via the API). However, the CDF UI is currently not showing this unit. It means that we either have to create a dedicated “property_UOM”, or we have to add the unit into the @name in the View description. It would be preferable if the UI could show the unit, and also support the unit conversion. 

Today an Atlas AI agent (and Flow app) uses my personal access rights when accessing CDF. However, we see the need for being able to further restrict this. One example is: I have write access, but I do not want my Agent to have the same write access. This issue is currently not solvable by using a separate service principal for the Agent, since different users will have different read access, so I cannot have one Agent with a fixed set of access rights. What would work is to be able to grant the agent certain (maximum) access rights, and then the final access rights are the minimum of the agents and mine access rights.This becomes increasingly important when the capabilities of the (reasoning) agents are growing. We need to be able to provide additional (and strict) guardrails

With the data modelling framework, most models will end up with a significant number of Views. Today we are not able to control the order the Views are presented in a good way. By reverse engineering it seems like the order of the Views is based on The order of the (first mentioned) CDM extension in the model definition. Alle non-CDM Views are listed at the end, irrespectively whether it is listed before CDM or not  What is considered a CDM extension by the UI is not based on the implements, but whether it reference at least one property from one of the CDM containers Inside each Category (eg, a specific CDM extension, or the non-CDM Views), the order in the model definition dictates the orderIf I choose alphabetic sorting it seems to only affect the non-CDM-Views, and not the order inside each CDM category. It do however put all the CDM categories first or last It is very inconvenient to use the order of appearance in the model definition as the way of sorting (we have to sort both th