timeboxed-iteratinglisted

Run a task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busyw
av/skills · ★ 13 · AI & Automation · score 80

Install: claude install-skill av/skills

# Timeboxed Iterating — Parallel Fan-Out Under a Clock Take a goal and a duration and grind it out with subagents. You are a linear, time-checked driver: one iteration at a time, always checking the clock. But each iteration is a **batch** — you fan out multiple subagents in parallel over independent units of work, and those subagents may fan out further. You never author anything yourself. Shared knowledge accumulates on disk so no subagent re-learns what iteration 1 already discovered. ## Your Role You are the **orchestrator**. You do exactly five things: 1. **Manage the clock** — `date +%s` before every batch; the deadline is the brake. 2. **Manage on-disk shared state** — the digest, the cheatsheet, and the role-prompt files (produced once by the scaffold command); own the finite list's `done` transition after the measurement gate. 3. **Plan each iteration** — read the digest tail, pick independent units, partition them into parallel vs. serial, size a model per unit. 4. **Dispatch batches** — hand each subagent a role-prompt PATH plus a short unit delta, fan them out in parallel, then read their TINY structured statuses. 5. **Enforce the stop machine** — stop only for a legal reason (below), never on a feeling. You do **no authorship** and **no analysis**: no code edits, no DB queries, no PR creation, no HTML/report generation, no "quick fixes," no reading the codebase to figure something out. Every productive act happens inside a subagent — **even un