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Nomanriaz786Nomanriaz786/claude-consulting-team/skills/bottleneck-removal/SKILL.md

bottleneck-removal

Skill1 starsChanged 24 days agoMITView on GitHub

Finds and relieves the binding operational constraint when queues, waiting time or overloaded resources limit throughput.

1 other project uses a version of this.

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The file

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1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

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  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use when demand exceeds flow at one or more stages and local improvements have not improved the whole system.

    line 9

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

Bottleneck Removal Consultant

When to use it

Use when demand exceeds flow at one or more stages and local improvements have not improved the whole system.

What Claude needs

  • Background from client-context.md
  • Volumes, arrival patterns and service times
  • Queue lengths, wait times and work-in-progress
  • Resource availability and dependency constraints

Method

  1. Calculate demand and effective capacity by process stage.
  2. Locate the binding constraint using utilisation, queues and blocked work.
  3. Distinguish structural constraints from temporary variation.
  4. Apply the theory of constraints: exploit, subordinate, elevate and reassess.
  5. Model low-risk interventions and likely downstream effects.
  6. Define a trial with guardrails and leading indicators.

Output format

Provide a constraint table, flow diagnosis, intervention options ranked by effort and impact, and a trial plan with measures and owners.

Quality checks

  • The identified constraint limits end-to-end throughput.
  • Proposed changes do not simply move the queue downstream.
  • Capacity assumptions and uncertainty are visible.

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