feat: scaled transact budgets + labeled timeout diagnostics + envelope docs

- The transact apply budget scales with the batch — max(30s, opCount x 2s) —
  or is exactly the caller's new TransactOptions.timeoutMs. A flat 30s cap
  silently limited honest bulk work to ~15 operations on network-attached
  storage (~2s/op measured in a production import) while looking generous for
  small batches. Internal batch paths (removeMany chunks) get the same
  scaling via the shared transactTimeoutBudget helper.
- TransactionTimeoutError now reports the operation it stopped at as i/N with
  the operation's name, elapsed vs budgeted time, and states the batch rolled
  back atomically and is retryable; context carries the fields
  programmatically.
- The transact operational envelope is documented (optimistic-concurrency
  guide): budget math, chunking with ifAbsent idempotency, when to reach for
  addMany vs transact, and the precompute pattern (embedBatch + per-op
  vector) that keeps inference out of the commit path.
- Embedding claims made honest per an end-to-end probe of the built dist:
  batch and single embedding paths produce bit-identical vectors and a
  vector-supplied add is fully searchable, but batch throughput on the
  default WASM engine measures comparable to sequential (~160ms/text) — the
  5-10x speedup claim in the addMany JSDoc is replaced with the measured
  reality and the actual win (inference outside the budgeted write path).

docs/guides/optimistic-concurrency.md

@@ -180,3 +180,35 @@ Brainy 8.0 has exactly two write-coordination counters, at two granularities:
 They compose: a `transact()` batch can carry per-entity `ifRev` checks *and* a whole-store `ifAtGeneration`; any failed check rejects the entire batch before anything is staged. Generations also power snapshots and time travel (`brain.now()`, `brain.asOf()`, `db.persist()`) — see the [consistency model](../concepts/consistency-model.md) and [Snapshots & Time Travel](./snapshots-and-time-travel.md).
 
 A snapshot or historical view captures each entity *including* its `_rev` at that moment, so reading the past and writing back with `ifRev` against the live state works exactly as you'd hope: the write fails if the entity moved since the state you copied from.
+
+## The transact envelope: batch size, budget, and bulk imports
+
+`transact()` applies its batch atomically under one commit — which means the whole batch
+shares one **apply budget**. Since 8.7.0 the budget scales with the batch:
+`max(30 s, opCount × 2 s)`, or exactly what you pass as `timeoutMs`. A tripped budget rolls
+the entire batch back (nothing partial survives) and throws a retryable
+`TransactionTimeoutError` that names the operation it stopped at, the batch size, and the
+elapsed vs budgeted time — a diagnosis, not just a failure:
+
+```
+Transaction timed out at operation 41/120 ('add') — 246012ms elapsed, budget 240000ms.
+The batch rolled back atomically; retry with a higher timeoutMs or a smaller batch.
+```
+
+Practical envelope guidance for bulk work:
+
+1. **Precompute embeddings outside the commit path.** Embedding inside `transact()` spends
+   the budget on model inference. Use `brain.embedBatch(texts)` and pass each vector via
+   the op's `vector` field — the commit then pays only storage costs, and a retried batch
+   never re-pays inference. (The win is *where* the inference happens, not raw embedding
+   throughput: on the default WASM engine, batch and sequential embedding measure
+   comparably, ~160 ms/text; native embedding providers may batch faster.)
+2. **Chunk very large imports** into batches of a few hundred ops with one `transact()`
+   each. You lose whole-import atomicity but keep per-chunk atomicity, bounded memory, and
+   resumability — pair with `ifAbsent` upserts so a retried chunk is idempotent.
+3. **Slow disks change the math, not the contract.** On network-attached storage a single
+   op can cost ~2 s (canonical write + fsync + index maintenance). The scaled default
+   absorbs that; pass an explicit `timeoutMs` only when you know better than the scale.
+4. **`addMany`/`relateMany` are the convenience tier** — they chunk and batch-embed for
+   you, with per-item error reporting instead of batch atomicity. Choose by what you need:
+   atomic-all-or-nothing → `transact()`; resilient bulk load → `addMany`.