Activate when: returns are piling up before a deadline; reviewer/preparer is the bottleneck; 'we can't get through them all,' 'clients waiting on missing doc...
--- name: tax-season-throughput-constraints description: "Activate when: returns are piling up before a deadline; reviewer/preparer is the bottleneck; 'we can't get through them all,' 'clients waiting on missing docs,' planning staffing for Jan–Apr. Do NOT activate when: off-season, low volume; the issue is a single stuck return (use debugging, not capacity theory)." --- # Tax Prep — Season Throughput (Theory of Constraints) > **Industry front door for theory-of-constraints.** Adds domain triggers, example, packs only. Parent Process unchanged. **Activate when:** returns are piling up before a deadline; reviewer/preparer is the bottleneck; "we can't get through them all," "clients waiting on missing docs," planning staffing for Jan–Apr. **Do NOT activate when:** off-season, low volume; the issue is a single stuck return (use debugging, not capacity theory). ## Why this variant The parent theory-of-constraints finds the one step that caps total output and subordinates everything to it. In a tax practice the constraint is almost never "preparation" — it's usually **the reviewer** or **client missing-documents**. Optimizing anything else is wasted motion during season. ## Domain inputs → parent's Process Pipeline stages: intake → doc-complete → prep → review → e-file. 1. Measure WIP at each stage; the stage with the growing queue = constraint. 2. Exploit: protect reviewer time (no admin), pre-triage returns so review is fast. 3. Subordinate: preparers pace to reviewer capacity, not their own. 4. Elevate: add reviewer capacity / async review / raise complexity threshold for partner review. ## Worked example 80 returns in "prep-done," 6 cl2ear/day through review → 13-day backlog vs 5 days to deadline. → Constraint = review. Exploit: batch simple returns for a fast lane; move partner off prep entirely. Missing-docs is the upstream feeder — a chaser (see onboarding/data-room agents) protects the constraint from starving. ## Packs - **Solo:** one fast-lane vs deep-lane split; cap daily complex intake. - **Firm:** reviewer-protected calendar; WIP board; extension-triage rule when backlog > days-remaining. ## Red flags - Preparers "busy" but review queue growing = optimizing the non-constraint. - Missing-docs starving the constraint (idle reviewer waiting on clients). ## Verification - [ ] Constraint stage identified by queue growth, not opinion - [ ] Non-constraint work subordinated to it - [ ] Extension policy triggered when backlog > remaining days - [ ] Upstream doc-chaser keeps constraint fed --- Part of **deciqAI Knowledge Skills**. Core method: theory-of-constraints. --- *Part of **deciqAI Knowledge Skills** — 189 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/c/tax-season-throughput-constraints** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*
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