diff --git a/quartz/src/jvmTest/kotlin/com/vitorpamplona/quartz/nip01Core/relay/prodbench/TagAuthorIndexBenchmark.kt b/quartz/src/jvmTest/kotlin/com/vitorpamplona/quartz/nip01Core/relay/prodbench/TagAuthorIndexBenchmark.kt
new file mode 100644
index 0000000000..7ef0fc7ac8
--- /dev/null
+++ b/quartz/src/jvmTest/kotlin/com/vitorpamplona/quartz/nip01Core/relay/prodbench/TagAuthorIndexBenchmark.kt
@@ -0,0 +1,184 @@
+/*
+ * Copyright (c) 2025 Vitor Pamplona
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy of
+ * this software and associated documentation files (the "Software"), to deal in
+ * the Software without restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the
+ * Software, and to permit persons to whom the Software is furnished to do so,
+ * subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+ * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+ * COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN
+ * AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+ * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ */
+package com.vitorpamplona.quartz.nip01Core.relay.prodbench
+
+import com.vitorpamplona.quartz.nip01Core.core.Event
+import com.vitorpamplona.quartz.nip01Core.relay.filters.Filter
+import com.vitorpamplona.quartz.nip01Core.store.sqlite.DefaultIndexingStrategy
+import com.vitorpamplona.quartz.nip01Core.store.sqlite.EventStore
+import com.vitorpamplona.quartz.utils.EventFactory
+import kotlinx.coroutines.runBlocking
+import kotlin.test.Test
+
+/**
+ * Measures the two tag-path query shapes the client filter-assembler survey
+ * (2026-07) found hot but that no existing benchmark covers:
+ *
+ * 1. **tag ∩ author (DM-room shape)** — `kinds=[4] AND authors=[peer] AND
+ *    #p=[me] LIMIT n`. 65 assembler call sites build this shape (every
+ *    NIP-04 chat room, reports-by-follows, follows-scoped community feeds).
+ *    [com.vitorpamplona.quartz.nip01Core.store.sqlite.IndexingStrategy.indexTagsWithKindAndPubkey]
+ *    gates a covering `(tag_hash, kind, pubkey_hash, created_at)` index for
+ *    it, but the flag is off everywhere (including geode). Without it the
+ *    plan seeks `(tag_hash, kind)` and reads EVERY DM the user has ever
+ *    received before filtering to the one peer. This compares query latency
+ *    with the flag off vs on, and the batch-insert cost the extra index adds.
+ *
+ * 2. **large-IN tag watcher (reactions shape)** — `kinds=[7] AND
+ *    #e=[hundreds of note ids] LIMIT n`. The per-value streams come sorted
+ *    off `(tag_hash, kind, created_at)`, but their union does not, so SQLite
+ *    collects every matching row and TEMP-B-TREE sorts to the limit — the
+ *    tag-index analogue of the follow-feed regression
+ *    [MergeQueryExecutor] fixed for author streams. Reported with and
+ *    without a `since` bound to show what EOSE-warm steady state hides.
+ *
+ * Size the seed with `-DtagBenchScale=N` (default 1 ≈ ~200k events).
+ */
+class TagAuthorIndexBenchmark {
+    companion object {
+        val SCALE = System.getProperty("tagBenchScale")?.toInt() ?: 1
+    }
+
+    private val hex = "0123456789abcdef"
+
+    private fun mix(seed: Long): Long {
+        var z = seed + -0x61c8864680b583ebL
+        z = (z xor (z ushr 30)) * -0x40a7b892e31b1a47L
+        z = (z xor (z ushr 27)) * -0x6b2fb644ecceee15L
+        return z xor (z ushr 31)
+    }
+
+    private fun hex64(
+        salt: Long,
+        index: Int,
+    ): String {
+        val out = CharArray(64)
+        for (w in 0 until 4) {
+            val v = mix(salt * 1_000_003 + index.toLong() * 4 + w)
+            for (b in 0 until 8) {
+                val byte = ((v ushr (b * 8)) and 0xFF).toInt()
+                out[(w * 8 + b) * 2] = hex[byte ushr 4]
+                out[(w * 8 + b) * 2 + 1] = hex[byte and 0xF]
+            }
+        }
+        return String(out)
+    }
+
+    private val sig = "0".repeat(128)
+    private var idSeq = 0
+
+    private fun ev(
+        pubkey: String,
+        createdAt: Long,
+        kind: Int,
+        tags: Array<Array<String>>,
+    ): Event = EventFactory.create(hex64(7, idSeq++), pubkey, createdAt, kind, tags, "", sig)
+
+    private fun seedEvents(): List<Event> {
+        idSeq = 0
+        val base = 1_700_000_000L
+        val span = 3_000_000L // ~35 days
+        val me = hex64(9, 0)
+        val events = ArrayList<Event>(220_000 * SCALE)
+
+        // DM inbox: 200 peers, 300 DMs each → 60k kind-4 rows sharing the
+        // same (p:me) tag hash. The room query wants one peer's 300.
+        val peers = (0 until 200).map { hex64(2, it) }
+        for ((i, peer) in peers.withIndex()) {
+            repeat(300 * SCALE) {
+                val ts = base + (mix(i * 131L + it) and 0x7fffffff) % span
+                events.add(ev(peer, ts, 4, arrayOf(arrayOf("p", me))))
+            }
+        }
+
+        // Notification noise: 2000 authors mention me in kind-1 notes, so
+        // (p:me) spans multiple kinds like a real inbox does.
+        repeat(40_000 * SCALE) {
+            val author = hex64(3, it % 2_000)
+            val ts = base + (mix(it * 17L) and 0x7fffffff) % span
+            events.add(ev(author, ts, 1, arrayOf(arrayOf("p", me))))
+        }
+
+        // Reactions: 100k kind-7 events spread over 5000 target notes, for
+        // the large-IN watcher shape.
+        val noteIds = (0 until 5_000).map { hex64(5, it) }
+        repeat(100_000 * SCALE) {
+            val author = hex64(4, it % 3_000)
+            val ts = base + (mix(it * 29L) and 0x7fffffff) % span
+            events.add(ev(author, ts, 7, arrayOf(arrayOf("e", noteIds[it % noteIds.size]))))
+        }
+        return events
+    }
+
+    @Test
+    fun compareTagAuthorIndex() =
+        runBlocking {
+            val events = seedEvents()
+            val me = hex64(9, 0)
+            val peers = (0 until 200).map { hex64(2, it) }
+            val noteIds = (0 until 5_000).map { hex64(5, it) }
+
+            println("─ TagAuthorIndexBenchmark: ${events.size} events (scale=$SCALE) ─")
+
+            val strategies =
+                listOf(
+                    "flag-off" to DefaultIndexingStrategy(indexFullTextSearch = false),
+                    "flag-on " to DefaultIndexingStrategy(indexFullTextSearch = false, indexTagsWithKindAndPubkey = true),
+                )
+
+            for ((label, strategy) in strategies) {
+                val store = EventStore(dbName = null, indexStrategy = strategy)
+
+                val t0 = System.nanoTime()
+                events.chunked(10_000).forEach { store.batchInsert(it) }
+                val insertMs = (System.nanoTime() - t0) / 1e6
+                println("  ═ $label ═  insert: %.0f ms (%.1f µs/event)".format(insertMs, insertMs * 1000 / events.size))
+
+                // 1. DM room: one peer's DMs out of the whole (p:me) inbox.
+                val room = Filter(kinds = listOf(4), authors = listOf(peers[42]), tags = mapOf("p" to listOf(me)), limit = 100)
+                time(store, "dm-room (#p ∩ author ∩ kind, limit 100)", room)
+
+                // 2. Reactions watcher: 300 note ids, cold (no since).
+                val watcher = Filter(kinds = listOf(7), tags = mapOf("e" to noteIds.take(300)), limit = 500)
+                time(store, "reactions (#e IN 300, limit 500, cold)", watcher)
+
+                // 3. Same watcher, EOSE-warm (since bounds the window).
+                val warm = watcher.copy(since = 1_700_000_000L + 2_900_000L)
+                time(store, "reactions (#e IN 300, limit 500, since)", warm)
+
+                store.close()
+            }
+        }
+
+    private suspend fun time(
+        store: EventStore,
+        label: String,
+        filter: Filter,
+    ) {
+        repeat(3) { store.query<Event>(filter) }
+        val runs = 10
+        var rows = 0
+        val start = System.nanoTime()
+        repeat(runs) { rows = store.query<Event>(filter).size }
+        val ms = (System.nanoTime() - start) / 1e6 / runs
+        println("    %-42s %8.2f ms  (%d rows)".format(label, ms, rows))
+    }
+}
diff --git a/quartz/src/jvmTest/kotlin/com/vitorpamplona/quartz/nip01Core/store/fs/FsDriverSelectionBenchmark.kt b/quartz/src/jvmTest/kotlin/com/vitorpamplona/quartz/nip01Core/store/fs/FsDriverSelectionBenchmark.kt
new file mode 100644
index 0000000000..54058191ba
--- /dev/null
+++ b/quartz/src/jvmTest/kotlin/com/vitorpamplona/quartz/nip01Core/store/fs/FsDriverSelectionBenchmark.kt
@@ -0,0 +1,158 @@
+/*
+ * Copyright (c) 2025 Vitor Pamplona
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy of
+ * this software and associated documentation files (the "Software"), to deal in
+ * the Software without restriction, including without limitation the rights to use,
+ * copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the
+ * Software, and to permit persons to whom the Software is furnished to do so,
+ * subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+ * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+ * COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN
+ * AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
+ * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ */
+package com.vitorpamplona.quartz.nip01Core.store.fs
+
+import com.vitorpamplona.quartz.nip01Core.core.Event
+import com.vitorpamplona.quartz.nip01Core.relay.filters.Filter
+import com.vitorpamplona.quartz.utils.EventFactory
+import kotlinx.coroutines.runBlocking
+import java.nio.file.Files
+import java.nio.file.Path
+import kotlin.io.path.exists
+import kotlin.test.Test
+
+/**
+ * Quantifies [FsQueryPlanner]'s "first available driver wins" ordering
+ * (tags → kinds → authors) on the `authors + kinds + limit` shape — the
+ * most common CLI query (27 assembler call sites; every `amy feed`-style
+ * author timeline over non-replaceable kinds).
+ *
+ * `Filter(authors=[pk], kinds=[1], limit=n)` drives from `idx/kind/1/`
+ * (the biggest tree in any real store) and post-filters the author, even
+ * though `idx/author/<pk>/` holds exactly that author's events. The
+ * benchmark times:
+ *
+ *  - **kind-driver (current)**: the filter as the planner runs it today.
+ *  - **author-driver (proposed)**: same result set, but driven from the
+ *    author tree with the kind check as a post-filter — what a cost-based
+ *    picker (compare candidate directory sizes) would choose.
+ *
+ * Also reports the author-only shape (`authors + limit`) as the floor: the
+ * planner already picks the author tree there, so its time is the target.
+ *
+ * Size the seed with `-DfsBenchScale=N` (default 1 ≈ ~30k events; each
+ * event is a file + ~3 hardlinks, so seeding dominates wall time).
+ */
+class FsDriverSelectionBenchmark {
+    companion object {
+        val SCALE = System.getProperty("fsBenchScale")?.toInt() ?: 1
+    }
+
+    private val hex = "0123456789abcdef"
+
+    private fun mix(seed: Long): Long {
+        var z = seed + -0x61c8864680b583ebL
+        z = (z xor (z ushr 30)) * -0x40a7b892e31b1a47L
+        z = (z xor (z ushr 27)) * -0x6b2fb644ecceee15L
+        return z xor (z ushr 31)
+    }
+
+    private fun hex64(
+        salt: Long,
+        index: Int,
+    ): String {
+        val out = CharArray(64)
+        for (w in 0 until 4) {
+            val v = mix(salt * 1_000_003 + index.toLong() * 4 + w)
+            for (b in 0 until 8) {
+                val byte = ((v ushr (b * 8)) and 0xFF).toInt()
+                out[(w * 8 + b) * 2] = hex[byte ushr 4]
+                out[(w * 8 + b) * 2 + 1] = hex[byte and 0xF]
+            }
+        }
+        return String(out)
+    }
+
+    private val sig = "0".repeat(128)
+    private var idSeq = 0
+
+    private fun ev(
+        pubkey: String,
+        createdAt: Long,
+        kind: Int,
+    ): Event = EventFactory.create(hex64(7, idSeq++), pubkey, createdAt, kind, emptyArray(), "", sig)
+
+    @Test
+    fun compareDrivers() =
+        runBlocking {
+            val root: Path = Files.createTempDirectory("fs-driver-bench-")
+            val store = FsEventStore(root)
+            try {
+                val base = 1_700_000_000L
+                val span = 3_000_000L
+                val target = hex64(9, 0)
+
+                // Background: 300 authors × 100 kind-1 notes.
+                val bg = ArrayList<Event>(30_000 * SCALE + 300)
+                repeat(30_000 * SCALE) {
+                    val author = hex64(1, it % 300)
+                    bg.add(ev(author, base + (mix(it * 31L) and 0x7fffffff) % span, 1))
+                }
+                // Target author: 200 kind-1 notes + 50 kind-7 reactions.
+                repeat(200) { bg.add(ev(target, base + (mix(it * 131L) and 0x7fffffff) % span, 1)) }
+                repeat(50) { bg.add(ev(target, base + (mix(it * 61L) and 0x7fffffff) % span, 7)) }
+
+                val t0 = System.nanoTime()
+                store.transaction { bg.forEach { insert(it) } }
+                val insertMs = (System.nanoTime() - t0) / 1e6
+                println("─ FsDriverSelectionBenchmark: ${bg.size} events (scale=$SCALE), seed %.0f ms ─".format(insertMs))
+
+                // Current planner: kinds present → kind tree drives, author
+                // is a post-filter over the whole kind-1 listing.
+                val kindDriven = Filter(authors = listOf(target), kinds = listOf(1), limit = 50)
+                time(store, "kind-driver (current planner)") { store.query<Event>(kindDriven).size }
+
+                // Proposed: drive from the author tree, post-filter kind —
+                // same semantics, what a cost-based picker would run.
+                time(store, "author-driver (proposed)") {
+                    store
+                        .query<Event>(Filter(authors = listOf(target), limit = 250))
+                        .asSequence()
+                        .filter { it.kind == 1 }
+                        .take(50)
+                        .count()
+                }
+
+                // Floor: author-only shape, planner already optimal here.
+                val authorOnly = Filter(authors = listOf(target), limit = 50)
+                time(store, "author-only (planner floor)") { store.query<Event>(authorOnly).size }
+            } finally {
+                store.close()
+                if (root.exists()) {
+                    Files.walk(root).use { it.sorted(Comparator.reverseOrder()).forEach { p -> Files.deleteIfExists(p) } }
+                }
+            }
+        }
+
+    private inline fun time(
+        store: FsEventStore,
+        label: String,
+        run: () -> Int,
+    ) {
+        repeat(3) { run() }
+        val runs = 10
+        var rows = 0
+        val start = System.nanoTime()
+        repeat(runs) { rows = run() }
+        val ms = (System.nanoTime() - start) / 1e6 / runs
+        println("    %-32s %8.2f ms  (%d rows)".format(label, ms, rows))
+    }
+}