A competitor watchlist, your own viewers' requests, and a swipe file — sitting inside the project where you'll build the reel.
Add the channels you measure yourself against and a background sweep records each one roughly daily, keeping a month of history. You see what a channel published this week and how it did — not a lifetime average that hides the trend.
Point it at a topic and it searches YouTube inside a shared daily budget, working out the comparison at read time rather than storing a copy that goes stale. When the day's budget is spent it says so and degrades, instead of failing or filling the gap with a number nobody measured.
Your channel's comments are mined for the things people actually asked you to cover, and each one arrives as a candidate topic with the comment behind it. This reads the YouTube channel you connected; the Instagram equivalent needs a comment permission the app has not been granted, and connecting an Instagram account at all is waiting on Meta App Review.
Keywords are scored against each other so you can rank candidates. Absolute monthly search volume needs a paid data provider that is not wired up here, so that field stays empty rather than showing a figure we would have had to guess.
Keep reels worth stealing from in folders, and turn a saved reel into style rules your project applies to its own generations — the same style-training path the editor uses, reached from the reel you saved.
Views, subscriber counts, publish dates and result counts are always shown. YouTube-derived scores — outlier multiples, velocity, a 0-100 opportunity number — are switched off, because YouTube's developer terms rule out derived metrics until an exception is granted. Where the score would sit, you get a lock and an explanation.
Most research tools hand you a number and no way to argue with it. A 0-100 opportunity score is a judgement wearing a measurement's clothes: you cannot see what went into it, so you cannot tell when it is wrong. ReelMint shows the raw facts instead — how many results a query returned, how many views the top ones got, how big those channels are, when they published — and lets you do the comparing.
The missing numbers are missing on purpose. YouTube-derived scores stay off because YouTube's developer terms treat derived metrics as off-limits until an exception is granted, and absolute keyword volume stays blank because the paid provider that would supply it is not configured. A blank field is honest; a guessed one is the thing this whole site argues against. Research reads the YouTube channel you connected, so connect one first — the Instagram side uses Instagram's own Business Discovery through a connected Instagram account, which is waiting on Meta App Review.
Research, the watchlist and the swipe file are in the free tier. They read your own connected channel — no extra subscription, no keyword tool.
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