Skills are reusable bundles of instructions that every Basedash AI surface can read on demand. Define your metrics once and any AI agent in your workspace will pick up the skill when it's relevant. No more pasting the same caveats into every prompt. Each skill is a short, plain-language playbook for one concept. Admins manage them; everyone else's AI gets the benefit. Add them as you go — the more you teach Basedash, the more it acts like an analyst who already knows your business.
We've been quietly using Skills inside Basedash for the past few weeks. They turn out to be the most natural way to move definitions out of one-off prompts and into shared, durable context, closer to a lightweight semantic layer than a system prompt.
The thing that won us over: every AI surface picks them up automatically. Build a chart, run an automation, get a daily insight, or just ask the chat agent a question. When a skill is relevant, the agent fetches it before answering. You see the tool call (e.g. "Reading Activation rate skill") in the thinking trace, so it's never a black box.
If you've ever rewritten the same definition of MRR / activation / churn / cohort into five different prompts, this is for you.
Try it out and let us know what you think!
Natural language to chart is a familiar idea, but curious how Basedash handles ambiguous questions - like when 'active user' could mean three different things depending on the team?
The origin of this was pretty unglamorous. We kept watching people paste the same definition of activation or churn into chat, then into a chart prompt, then into an automation, and every time they'd phrase it slightly differently and get slightly different numbers. The model was doing exactly what we asked but we were just asking five versions of the same question lol.
Skills came out of fixing that for ourselves. You write the definition down once, in plain language, and from then on any agent in the workspace reaches for it when the topic comes up. A new person can ask "how's activation trending" on day one and get the same answer the rest of the team would get, because the agent is reading the same playbook everyone else's agent reads.
If you've got a metric that means something specific at your company and you're tired of explaining it to the AI every single time, give it a try and tell us where it falls short!
Moving definitions out of one-off prompts and into shared durable context is exactly the lightweight semantic layer most teams skip until they're already drowning in inconsistent metric defs. How do you handle drift when someone updates a Skill that's been silently feeding 12 different surfaces — version pin, broadcast, or both?
this is a very handy tool for founders, but I have a question on how are you handling large dataset like clickstream locally and does the data site locally even after ETL?
About Basedash Skills on Product Hunt
“Reusable AI instructions for every Basedash surface.”
Basedash Skills launched on Product Hunt on May 21st, 2026 and earned 97 upvotes and 10 comments, placing #18 on the daily leaderboard. Skills are reusable bundles of instructions that every Basedash AI surface can read on demand. Define your metrics once and any AI agent in your workspace will pick up the skill when it's relevant. No more pasting the same caveats into every prompt. Each skill is a short, plain-language playbook for one concept. Admins manage them; everyone else's AI gets the benefit. Add them as you go — the more you teach Basedash, the more it acts like an analyst who already knows your business.
Basedash Skills was featured in Artificial Intelligence (469.1k followers), Data & Analytics (5.6k followers) and Business Intelligence (3.5k followers) on Product Hunt. Together, these topics include over 99.3k products, making this a competitive space to launch in.
Who hunted Basedash Skills?
Basedash Skills was hunted by Max Musing. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Basedash Skills stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Max Musing