# Theory Of Constraints

> Apply Theory of Constraints (TOC) whenever the user asks why a system, team, pipeline, or process isn't going faster, isn't scaling, keeps hitting the same ceiling, or feels like effort isn't translating into results. Triggers on phrases like "we're stuck", "why is this slow?", "we keep hitting a wall", "throughput is low", "we work hard but don't ship fast", "what's the bottleneck?", "how do we scale this?", or any situation where effort and output feel misaligned. Also trigger when evaluating workflows, delivery pipelines, agent pipelines, or organizational processes — always check for the constraint first before recommending optimizations.

- Skill: `andurilcode/theory-of-constraints` (Agent Skill)
- Install (CLI): `npx skillmds@latest add andurilcode/theory-of-constraints`
- Raw SKILL.md: https://api.skillmd.com/api/skills/andurilcode/theory-of-constraints/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: andurilcode (https://skillmd.com/u/andurilcode)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/andurilcode/theory-of-constraints

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# Theory of Constraints (TOC)

**Core principle**: Every system has exactly **one constraint** limiting its throughput at any moment. Improving anything that is *not* the constraint is waste. Find the constraint, exploit it, then repeat.

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## The 5 Focusing Steps

### Step 1: Identify the Constraint
The single bottleneck — the resource/process/step with least capacity relative to demand.

**How to find it:**
- Where does work **pile up**? (queue buildup = upstream of constraint)
- Where is there **idle time**? (downstream — starved for input)
- What does everyone **wait on**? (often "that one person" or "that one step")
- What's the **longest step** in the value stream?

Signal: *Constraint = where WIP accumulates and delays originate.*

### Step 2: Exploit the Constraint
Maximize throughput **without spending money or major changes first.**

- Eliminate waste at the constraint (no idle time, no low-value work)
- Buffer upstream (never starved)
- Offload non-constraint work
- Reduce defects feeding in (rework at the constraint is doubly expensive)

### Step 3: Subordinate Everything Else
Non-constraint steps **serve the constraint**, not optimize themselves. A non-constraint at 100% is harmful if it floods the constraint with WIP.

**Shift**: Stop measuring local efficiency. Measure **constraint throughput**.

### Step 4: Elevate the Constraint
If 2–3 insufficient, invest: capacity, people, tooling — only at the constraint.

### Step 5: Repeat
Constraint moves once resolved. Find the new one. Don't let inertia become the constraint.

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## Output Format

### 🔍 Constraint Identification
- **Identified constraint**: [Name the specific step, role, resource, or decision]
- **Evidence**: What signals point to this being the constraint?
- **WIP accumulation point**: Where does work pile up?
- **Downstream starvation**: What's blocked waiting for the constraint?

### 📊 Throughput Analysis
- Current flow: [Input → Step A → Step B → ... → Output]
- Constraint location in the flow
- Estimated throughput loss due to constraint

### ⚡ Exploit Actions (no-cost first)
- What waste can be removed at the constraint immediately?
- What low-value work can be offloaded from the constraint?
- What buffers should be added upstream?

### 🔄 Subordination Changes
- Which non-constraint steps are currently "optimizing locally" and harming system throughput?
- What should they slow down or stop doing?

### 📈 Elevation Options (if needed)
- Investment options to increase constraint capacity
- Cost/benefit relative to throughput gain

### ⚠️ False Bottlenecks to Avoid
- Which steps *look* slow but are actually downstream of the real constraint?
- What "improvements" would be wasted effort?

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## Common Constraint Types

| Type | Example | Signal |
|------|---------|--------|
| **Capacity constraint** | One engineer reviews all PRs | PRs queue up, reviewer is always busy |
| **Knowledge constraint** | Only one person knows the system | Everything waits on that person |
| **Decision constraint** | Approvals bottleneck execution | Teams idle waiting for sign-off |
| **Handoff constraint** | Work crosses team boundaries | Long wait times at team interfaces |
| **Policy constraint** | Rules prevent fast action | Work is done but can't ship |
| **Market constraint** | Demand is the limit | System has capacity but no demand |

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## Key Mental Shifts
- **Don't**: Optimize every step. **Do**: Protect and exploit the constraint.
- **Don't**: Measure local efficiency. **Do**: Measure global throughput.
- **Don't**: Start with investment. **Do**: Exploit first, then elevate.
- **Don't**: Assume the constraint is fixed. **Do**: Expect it to move after you fix it.