megaRules & texture buckets
The Rules tab is where a coaching group's own strategy — not a fixed vendor taxonomy — gets written down in a form the rest of the app can use.
Spots and rulesets
A spot is whatever scope makes sense to your group — "BTN vs BB SRP flop cbet sizing," say. Each spot can hold multiple named rulesets (a v1 and a v2 as your thinking evolves, or different rulesets for different stakes), and each ruleset holds an ordered list of rules.
A rule is a texture condition plus a strategy
Every rule pairs a texture condition — paired or not, has trips, suitedness (monotone, rainbow, two-tone with the flush draw on the high/middle/low card), a rank range, ranks the flop must contain or must not — with a strategy entry: an action, a bet size, a frequency, a confidence level, and free-text notes.
Rules resolve like a CSS cascade
Rules in a ruleset have a priority order (drag to reorder). Given a real flop, megamaster walks the rules in priority order and takes the first one whose texture condition matches — the same shape as a browser resolving CSS, or a waterfall of specificity. A broad fallback rule ("any flop → default line") sits at the bottom; specific exceptions ("monotone, ace-high → different sizing") sit above it and win when they apply.
megamaster doesn't ship a fixed texture taxonomy. Which flops belong to a "bucket" is computed from the rule you write, at query time — so a group's own way of splitting textures is exactly representable, instead of being forced through someone else's categories.
Testing a rule against a real flop
Type in any three flop cards and the Rules tab shows which rule actually wins for that exact flop — the fastest way to check a ruleset behaves the way you intended before trusting it.
Mined rules carry a price tag
The rules above are ones you write. There's a second kind, and the difference matters: rules mined from a solved library package arrive with a measured EV cost — what following that simplification actually gives up against playing the full solver strategy, in big blinds, per runout class.
Open a solved tree in the Viewer and any mined rules covering the node you're on are listed beside it, each showing its own cost. A rule whose cost is below solve noise reads ≈ free rather than a spuriously precise small number — a simplification you can adopt with nothing to weigh up.
Mined rules are shown, never auto-applied. Simplifying your strategy is a decision with a price, and the point of measuring the price is to let you make that decision — not to make it on your behalf and present the result as the solve.
Importing rules
Rulesets can be imported from text, so a strategy worked out once — in a document, in a coaching session — can be pasted in rather than re-entered rule by rule.