Turn scattered notesinto a product spec
A new spec always starts as a mess: a discovery call, a Slack thread, a screenshot, and a blank page you keep avoiding. Khint turns that pile into a structured first draft (problem, goals, scope, open questions) with a reusable AI action, keeps the context with Memory, and publishes the result to Confluence, all from one keyboard shortcut.
The blank page
is the hard part
You have all the inputs (the call, the constraints, the goal someone stated in passing), but they're scattered across five tabs, and turning them into a spec someone else can build from is the work you keep pushing to tomorrow. It's not a writing problem so much as a structuring one: what's the actual problem, what's in scope, what still needs a decision. Khint closes that gap with its three pillars (Agents, Capture, and Memory) behind one palette, so the draft gets written while the context is still in your head.
From scattered inputs to a first draft
Drafting a new “Guest checkout” spec, blank page first.
Open a session for the spec you're writing
Before you gather anything, start a Memory session: call it “Guest checkout spec”. Every agent you run is logged to it, and Khint keeps a compact running summary that rides along on each prompt. So as you move from problem to goals to scope, the model already knows the feature you're shaping and the decisions you've already made. How Memory works →
Gather the scattered inputs
Drop the raw material into one rough notes block: the discovery-call takeaways, the constraint someone raised in Slack, the goal your lead stated. When a detail only lives on a screen (a competitor's flow, a slide, a diagram), use the palette's Extract text row to capture it straight into your notes instead of retyping. The goal is one messy block of truth, not a polished doc yet.
Draft the spec skeleton
Select the block and run a saved agent like “Draft spec”. It returns a structured first draft: a problem statement, goals, in-scope and out-of-scope, and the open questions that still block a decision. No prompt yet? Type a one-line description of the structure you want and press Generate; tighten it later with Improve. The blank page is now a scaffold you can react to.
Fill the gaps and tighten the prose
Work the draft section by section. Run a second agent to expand the user stories, or a Doc Polish agent to tighten a clumsy paragraph in place. Clone the Doc Polish starter pack from the Agents page for a working one. Chaining your draft and polish agents into one Workflow turns “notes → readable section” into a single shortcut. Already have a draft to polish? →
Publish it where the team will read it
With Atlassian connected, the Confluence Create page row publishes the finished spec as a page your team can read and comment on. One page per run, so every publish is deliberate. Prefer a different home? The Notion Create page row drafts it there instead. Either way the spec leaves your keyboard and lands where the conversation actually happens. How integrations work →
One block of notes, one spec skeleton
An example of what a spec-drafting agent might return. The decisions stay yours.
The content above is invented for the example: Khint never decides your scope or invents a goal you didn't state. It imposes the structure your agent asks for and surfaces the gaps you still have to close. Pair it with a acceptance-criteria agent so each in-scope item lands build-ready, and publish the whole thing to Confluence without leaving the keyboard.
Why not just paste the notes into a chatbot?
You can, and for every new spec you'll re-explain your preferred structure, re-paste the product context, and copy each section back into your doc by hand. Khint removes the round-trips: the drafting agent is saved once and reused on every spec, Memory carries the feature context into each prompt automatically, and the Atlassian and Notion integrations publish the result where the team will actually read it. Because an agent only sees the text you select, plus the session summary you opted into, your unreleased spec isn't sitting in a chat history. When the draft is done, see how Khint handles PRD polish.
Common questions
How does Khint help me write a product spec from scratch?
A new spec starts as a pile of raw inputs: a discovery call, a few Slack threads, a competitor screenshot, your own half-formed goals. Khint sits behind one shortcut (Cmd+Shift+K) so you can turn that pile into a structured first draft without leaving your doc: select a block of notes, run a saved AI agent, and get back a spec skeleton (problem statement, goals, in-scope, out-of-scope, and the open questions you still need to answer). You do the thinking and the decisions; Khint does the structuring and the writing.
Is this different from polishing an existing PRD?
Yes, and the two are complementary. Writing is the blank-page problem: going from scattered inputs to a first structured draft. Polishing is the editing problem: tightening a draft you already have into something readable. A writing agent is tuned to impose structure and surface gaps; a polish agent is tuned to clarify prose you've already written. If you already have a rough draft, see how Khint handles PRD polish instead.
Do I have to write the drafting prompt myself?
No. In the agent editor, type a one-line description of the spec structure you want and press Generate. Khint drafts the prompt for you; press Improve later to refine it in place. You can also clone the Doc Polish starter pack from the Agents page as a starting point for the tightening pass, then save your own spec-drafting agent alongside it.
Can Khint pull text out of screenshots into the spec?
Yes. The palette's Extract text row captures a region of your screen (a competitor's UI, a whiteboard photo, a slide from the kickoff deck), runs OCR on it, and drops the text onto your clipboard so you can paste it straight into your notes instead of retyping. It's one of Khint's three pillars, Capture, and it works on any window without a separate app.
Can Khint publish the finished spec to Confluence?
Once you connect Atlassian with your email, an API token, and your cloud domain, the palette adds a Confluence Create page row that publishes your drafted spec as a page your team can read and comment on. You can also draft into a Notion page with the Notion Create page row. Each write is one explicit action, so nothing is filed without you triggering it.
Where does my spec text go?
An agent only ever sees the text you selected, plus the compacted summary of your active Memory session if you opted in. Memory sessions live in a local SQLite database on your Mac and are never synced to Khint's servers, and your Atlassian credentials sit in your OS keychain. Nothing about an unreleased feature leaves your device silently.
Try it on your next spec
Free with 300 credits a month, about 10 AI actions a day. No credit card. Save the drafting agent once, reuse it on every spec after.