docs: clarify lobster DSL rationale

docs/tools/lobster.md

@@ -23,6 +23,16 @@ Today, complex workflows require many back-and-forth tool calls. Each call costs
 - **Approvals built in**: Side effects (send email, post comment) halt the workflow until explicitly approved.
 - **Resumable**: Halted workflows return a token; approve and resume without re-running everything.
 
+## Why a DSL instead of plain programs?
+
+Lobster is intentionally small. The goal is not "a new language," it's a predictable, AI-friendly pipeline spec with first-class approvals and resume tokens.
+
+- **Approve/resume is built in**: A normal program can prompt a human, but it can’t *pause and resume* with a durable token without you inventing that runtime yourself.
+- **Determinism + auditability**: Pipelines are data, so they’re easy to log, diff, replay, and review.
+- **Constrained surface for AI**: A tiny grammar + JSON piping reduces “creative” code paths and makes validation realistic.
+- **Safety policy baked in**: Timeouts, output caps, sandbox checks, and allowlists are enforced by the runtime, not each script.
+- **Still programmable**: Each step can call any CLI or script. If you want JS/TS, generate `.lobster` files from code.
+
 ## How it works
 
 Clawdbot launches the local `lobster` CLI in **tool mode** and parses a JSON envelope from stdout.