mcpbeat

Biz Toc

asgard-ai-platform/biz-toc

Apply Theory of Constraints (TOC) to identify and manage system bottlenecks. Use this skill when the user needs to find what limits throughput, optimize a constrained process, apply the Five Focusing Steps, or implement Drum-Buffer-Rope scheduling — even if they say 'our output is stuck', 'what's the bottleneck', or 'why can't we produce more'.

5k tokens
context cost
the whole folder, loaded on every use
3
files
instructions only
0
copies elsewhere
how many repositories repackaged it
223
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/asgard-ai-platform/skills --skill biz-toc

What comes with it

15 840 bytes besides the instruction
examples/sample_scenario.md
references/dbr-scheduling.md

The instruction itself

12 sections, as written by the author

Theory of Constraints (TOC)

Overview

TOC asserts that every system has at least one constraint (bottleneck) that limits total throughput. Improving non-bottleneck processes does NOT improve system output �� only improving the bottleneck does. The Five Focusing Steps provide a systematic method to find and manage constraints.

Framework

IRON LAW: The System Is Only as Strong as Its Weakest Link

Improving a non-bottleneck process is a WASTE of resources — it produces
more work-in-progress that piles up at the bottleneck. Before optimizing
any process, verify it IS the bottleneck. If it's not, stop.

The Five Focusing Steps

  • IDENTIFY the constraint — Find the bottleneck (highest utilization, longest queue, most WIP accumulation)
  • EXPLOIT the constraint — Maximize throughput at the bottleneck without adding resources (reduce downtime, eliminate waste at this step, ensure it never starves for input)
  • SUBORDINATE everything else — Pace all other processes to the bottleneck's rhythm. Non-bottlenecks should NOT run at full capacity.
  • ELEVATE the constraint — If exploitation isn't enough, invest to increase bottleneck capacity (add equipment, hire, outsource)
  • REPEAT — After elevating, the constraint may shift to another process. Go back to Step 1.

Drum-Buffer-Rope (DBR) Scheduling

| Element | What It Is | Purpose |

|---------|-----------|---------|

| Drum | The bottleneck's pace | Sets the rhythm for the entire system |

| Buffer | Time buffer before the bottleneck | Ensures the bottleneck never starves for work |

| Rope | Signal to release work at the start | Controls WIP by tying input rate to bottleneck pace |

Throughput Accounting (TOC Financial Metrics)

| Metric | Definition |

|--------|-----------|

| Throughput (T) | Revenue - Truly Variable Costs (materials only) |

| Investment (I) | Money tied up in the system (inventory, equipment) |

| Operating Expense (OE) | All other costs to run the system |

| Net Profit | T - OE |

| ROI | (T - OE) / I |

Output Format

# TOC Analysis: {System/Process}

## System Map
{Process A} → {Process B} → {**Process C (bottleneck)**} → {Process D} → Output

## Constraint Identification
- Bottleneck: {process step}
- Evidence: {utilization %, queue length, WIP accumulation}
- Current throughput: {units/period}

## Five Focusing Steps
| Step | Action | Expected Impact |
|------|--------|----------------|
| 1. Identify | {bottleneck location} | — |
| 2. Exploit | {optimize without investment} | +X% throughput |
| 3. Subordinate | {pace other processes} | Reduce WIP by X% |
| 4. Elevate | {investment if needed} | +X% throughput |
| 5. Repeat | {new constraint location} | — |

## DBR Implementation
- Drum: {bottleneck pace = X units/hour}
- Buffer: {X hours of WIP before bottleneck}
- Rope: {release new work every X minutes}

Examples

Correct Application

Scenario: TOC for a PCB assembly line (5 stations)

  • Station throughput: Solder Paste (100/hr) → Pick & Place (80/hr) → Reflow Oven (50/hr) → Inspection (90/hr) → Packaging (120/hr)
  • Bottleneck: Reflow Oven (50/hr) — lowest throughput, highest utilization
  • Exploit: Reduce oven changeover time from 30 min to 10 min → effective capacity +15%
  • Subordinate: Slow Pick & Place to 55/hr (don't overproduce WIP before oven)
  • Elevate: If needed, add second reflow oven → double capacity

Incorrect Application

  • Bought a faster Pick & Place machine (80→120/hr) → System throughput unchanged because Reflow Oven (50/hr) is still the bottleneck. Wasted investment. Violates Iron Law.

Gotchas

  • Constraints can be non-physical: Market demand, policy, or management attention can be the real constraint. If the factory can produce 1000 but only sells 500, the market is the constraint.
  • Moving bottleneck: After elevating one constraint, the bottleneck shifts. Teams often celebrate and forget Step 5 (Repeat).
  • Subordination is counterintuitive: Running non-bottleneck machines at less than full capacity feels wasteful. It's not — overproduction at non-bottlenecks creates WIP that clogs the system.
  • TOC vs Lean: Lean eliminates waste everywhere. TOC focuses only on the constraint. They complement each other: use TOC to find WHERE to focus, Lean to optimize HOW.

References

  • For Drum-Buffer-Rope implementation details, see references/dbr-scheduling.md

How to use it

Copy the folder

Take asgard-ai-platform/biz-toc from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.