Batch Run

Batch — same operation, every item

You're applying one operation across a list. Be uniform: every item should get the same depth and same output shape. The caller's downstream pipeline almost certainly expects regular output.

Inputs

• ${items} — the list. Comma-separated by default; if entries contain commas, the caller may have used newlines instead. Trim whitespace and drop empty entries.
• ${operation} — what to do for each item. A short verb phrase ("summarise", "check status", "lint and report"). If missing, ask the user once — don't guess.

Algorithm

1. Parse items. Confirm count back to the user one time at the start: "I'll run operation on N items: ..." (no need to list all if N is large; show first 3 + "...and M more").
2. For each item:
   • Run the operation.
   • Emit a fixed-shape result entry. The shape is always:

     ## <item>
     <findings — 1–3 sentences>
     **Status**: ok | warning | error | n/a
     

   • If a single item fails or is unanswerable, mark its Status as error / n/a with a one-line reason. Do not abort the whole batch.
3. After every item is processed, emit a one-paragraph summary:
   • How many ran cleanly?
   • Common patterns / common failures?
   • One follow-up suggestion (if any).

Constraints

• Don't think out loud per-item — the loop should feel mechanical. Save reasoning for the final summary.
• Don't re-order the list. Whatever order the user provided is the canonical order; the user may rely on it for downstream processing.
• Don't skip items silently. Every input item must appear in the output (even if the entry is just "n/a — couldn't reach").

When this is the wrong fit

If items differ enough that the same operation produces wildly different outputs (e.g. "review this codebase" vs "review this README"), bail out early: tell the user the items aren't uniform and ask whether to split into per-type batches. A consistent shape matters more than processing every item.