Thinking Theory Of Constraints
When throughput or latency is pipeline-limited, identify the single binding constraint...
Install
npx skills add tjboudreaux/cc-thinking-skills --skill thinking-theory-of-constraints -g -a claude-code -y- Repository
- tjboudreaux/cc-thinking-skills1.7k
- Category
- Security
- Updated
- 3mo ago
- License
- MIT
- Context cost
- Lightabout 802 tokens
- Runs scripts
- No, instructions only
What it does
When throughput or latency is pipeline-limited, identify the single binding constraint and exploit, subordinate, elevate, then recheck, ignore non-constraints.
Theory of Constraints
A throughput-limited system has one binding constraint. Improve only that constraint; local optimization of non-constraints wastes effort and often grows WIP.
When to Use
- Latency or throughput goal where one stage dominates time or rate.
- Work piles up before one stage; downstream idles.
- Adding capacity/workers elsewhere does not raise end-to-end output.
- Need ordered plan: exploit cheaply before spending to elevate.
When NOT to Use
- Load is spread; no stage dominates, use systems for interactions.
- Problem is correctness/fault, not flow rate, debug the fault.
- Bottleneck hops every run due to coupling/contention without a stable stage, systems or concurrency design, not five focusing steps.
- Constraint already known and a cheap fix is ready, apply it without ceremony.
