diff --git a/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md b/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md
index e5f5e2a7..f8135642 100644
--- a/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md
+++ b/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md
@@ -72,50 +72,6 @@ work while the sub-agent grinds.
   turn it loose on the full batch. A prompt bug replicated across 100
   items is 100 cleanups.
 
-## Split a big independent batch across parallel subagents
-
-One subagent is a sequential worker — a 50-item batch takes roughly 50
-items' worth of wall-clock even though nothing about the recipe forces
-serialization. If the items are independent (each one touches its own
-file/issue/row, nothing depends on another item's result) and the batch
-is big enough that wall-clock matters, chunk it across N subagents
-running at once instead of handing the whole thing to one.
-
-- **Split by natural boundaries**, not an arbitrary item count — one
-  subagent per file, per directory, per module, per label, whatever
-  grouping keeps each worker's slice self-contained. A worker that has
-  to coordinate with another worker mid-task isn't actually independent
-  work; re-scope the split until it is.
-- **Isolate each worker's writes.** For a git-based batch, give each
-  worker its own `git worktree` (own working directory, own branch, same
-  underlying repo — cheap, no full reclone) so N workers editing
-  different files never race on the same working tree or index. For a
-  non-git batch (issue relabeling, API calls), independent items don't
-  need filesystem isolation at all — just launch N in parallel.
-- **Launch all N in the background and don't babysit any single one** —
-  same as the one-subagent case, just N background bash tasks instead of
-  one. Check on them as a batch, not by polling each individually in a
-  loop.
-- **Mind the container's memory cap before picking N.** Your whole
-  container shares one `MemoryMax` (a few GB by default) with every
-  subagent you spawn *and* your own process. A `claude` process plus its
-  MCP servers can hold several hundred MB to ~1GB depending on the task;
-  spawning a dozen at once on a small container doesn't just slow
-  things down, it can OOM the whole container — taking your own
-  in-flight turn down with it, not just the subagents. Rule of thumb:
-  **2-4 concurrent workers** on a default-sized container; check
-  `free -h` (or ask whoever owns the container's config for its
-  `MemoryMax`) before going higher, and chunk a bigger batch into
-  successive waves of that size rather than firing everything at once.
-- **You own the merge.** Once all N report done, review + verify each
-  worker's slice (same "don't trust the self-report blind" rule as
-  below), then combine — for a git-based split, that's you merging N
-  branches (or cherry-picking) into one, not each worker pushing/PRing
-  its own slice.
-
-Skip this for a batch small enough to finish in a couple minutes single-
-threaded — the coordination overhead isn't worth it below that size.
-
 ## Resume for follow-ups
 
 `claude --resume <name> -p "Now run the same procedure over the second batch."`
@@ -143,6 +99,3 @@ anything the sub-agent left ambiguous or exempted for a human call.
   suggests something "isn't possible" or "doesn't exist," confirm it
   before writing that conclusion into the prompt; a wrong assumption
   gets replicated across the whole batch.
-- Handing a big independent batch to one subagent instead of splitting
-  it across several in parallel - a 50-item sequential run burns wall-
-  clock the split-by-worktree approach above would've avoided for free.