diff --git a/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md b/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md
index 352ebf9f..bf18ff6a 100644
--- a/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md
+++ b/claude-plugins/plugins/base/skills/claude-subagents/SKILL.md
@@ -52,13 +52,33 @@ Model choice, prompt hygiene, splitting big batches, verify-then-report —
 everything else in this skill — applies exactly the same whether you're
 calling the tool or thinking through the recipe by hand.
 
+## Model choice
+
+Pick the cheapest model that can do the job, and lean toward the cheap end
+more readily than you might for your own work — a subagent is throwaway
+compute, not a peer you're rationing. Haiku in particular is cheap enough
+that you don't need to be precious about spinning one up: for a mechanical,
+well-scoped batch (the shape this skill is for), reach for it liberally
+rather than defaulting to a bigger model "to be safe." Haiku also stays
+cheap even at `effort: high` — unlike a frontier model, where effort and
+cost scale together, so there's no need to cap Haiku's effort the way the
+Effort section below recommends for cost reasons; raise it freely if the
+task benefits from the extra reasoning.
+
+This isn't "always pick the smallest model regardless of task" — a batch
+that actually needs judgement calls still wants a stronger model (see
+Pitfalls below). It's "don't under-use Haiku out of habit-driven caution
+when the task is mechanical enough for the skill to apply at all."
+
 ## Effort
 
 An omitted `effort` defaults to `medium` here — cheaper than claude's own
 model default (`high` on most models), a deliberate cost-conscious choice
-for subagent work specifically, same spirit as "cheaper-than-you" model
-choice above. Raise it explicitly when the task is complex enough to
-actually need deeper reasoning, not as a reflex.
+for subagent work specifically, same spirit as the model-choice guidance
+above. Raise it explicitly when the task is complex enough to actually
+need deeper reasoning, not as a reflex. **Exception: on Haiku, cost doesn't
+scale with effort the way it does on a frontier model** — see Model choice
+above, don't apply this same-default-medium caution to a Haiku subagent.
 
 Anthropic's own levels (per current Claude Code docs — names/availability
 are model-dependent, check before relying on an exact list): `low`,
diff --git a/hive-subagent-mcp/src/mcp.rs b/hive-subagent-mcp/src/mcp.rs
index cbe70b18..7a4b8454 100644
--- a/hive-subagent-mcp/src/mcp.rs
+++ b/hive-subagent-mcp/src/mcp.rs
@@ -44,9 +44,11 @@ struct StartArgs {
     /// session under that name is done — rejected while one under the same
     /// name is still running.
     name: String,
-    /// Which model the subagent's own session runs. Omit for claude's own
-    /// default. The `base:claude-subagents` skill's "cheaper-than-you"
-    /// guidance still applies here.
+    /// Which model the subagent's own session runs (`--model`). Omit for
+    /// claude's own default. The `base:claude-subagents` skill's "Model
+    /// choice" guidance still applies here — pick the cheapest model that
+    /// can do the job, and don't be stingy about reaching for Haiku on a
+    /// well-scoped mechanical batch.
     #[serde(default)]
     model: Option<String>,
     /// Which reasoning effort level the subagent's own session runs at
@@ -55,7 +57,9 @@ struct StartArgs {
     /// models). Independent of `model`, so a cheap model at high effort or
     /// an expensive one at low effort are both valid combinations, not
     /// just the two extremes. See the `base:claude-subagents` skill for
-    /// Anthropic's own guidance on choosing between levels.
+    /// Anthropic's own guidance on choosing between levels — note that on
+    /// Haiku specifically, cost doesn't scale with effort the way it does
+    /// on a frontier model, so there's no cost reason to cap it at `medium`.
     #[serde(default)]
     effort: Option<String>,
     /// Path to a file holding the subagent's actual task instructions. A