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Architecture · Version 1.1.0 · Reviewed 2026-08-02

Multi-Tenant Rate Limiting Designer

Make a defensible decision about fair share design and burst handling with evidence, explicit trade-offs, and a verification plan.

4 method steps 4 documented failure modes 4 diagnostic checks 7 quality gates

Designs fair-share rate limiting so one tenant cannot consume capacity belonging to others.

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What this skill helps you do

  • Fair share design
  • Burst handling
  • Limit enforcement

How Multi-Tenant Rate Limiting Designer works

You provide

Requirements, constraints, and the current topology

It inspects

Critical path and failure boundaries for fair share design

It decides

A burst handling decision with consequences recorded

You verify

Rollout stages with the signal that gates each one

What it checks first

Multi-Tenant Rate Limiting Designer designs fair-share rate limiting so one tenant cannot consume capacity belonging to others. Use it when the work involves Fair share design, Burst handling, Limit enforcement.

  1. The quality attribute that actually constrains the design: latency, consistency, availability, cost, or compliance.
  2. The critical path and the number of network hops on it.
  3. Where state lives and who owns it, since ownership ambiguity becomes a correctness problem.
  4. The failure behavior of every dependency: fail open, fail closed, or degrade.

Failure modes it recognizes

  • Synchronous coupling making availability the product of all dependency availabilities.
  • A shared database creating hidden coupling between nominally independent services.
  • A component with no clear owner, so its failure has no defined response.
  • Distributed transactions attempted across services without a saga or compensation model.

Answers it will reject

  • Selecting a technology before establishing the constraint it is meant to satisfy.
  • Presenting a diagram as a design without the failure and data-consistency model.
  • Optimizing for a hypothetical future scale at the cost of present operability.

Decision rules it applies

  • Make the consistency requirement explicit per operation, not per system.
  • Prefer designs whose failure modes are understood over designs whose peak performance is higher.
  • Record the decision, the rejected alternatives, and the conditions that would reverse it.

Evidence it asks for

  • Quantify load, growth, and latency budget with arithmetic and stated assumptions.
  • Define the rollout stages and the signal that gates each one.
  • Name the reversal path for the decision.

The method inside

  1. Turn fair share design into explicit functional requirements and quality-attribute constraints.
  2. Model the critical path, state, trust, and failure boundaries that govern burst handling.
  3. Compare viable designs for limit enforcement against weighted constraints and operational ownership.
  4. Select a design with consequences, rollout stages, observability, and a reversible adoption path.

Deliverables

  • Fair share design assessment
  • Burst handling decision and action plan
  • Limit enforcement verification checklist

Evidence requirements

  • Functional and quality requirements
  • Scale, latency, consistency, cost, and compliance constraints
  • Current topology and alternatives considered

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

One customer scripted our API and degraded service for everyone else despite our global rate limit.

Expected output

A global limit protects the system but not the tenants, which is exactly what you observed. Limit per tenant with a shared burst pool, and add a concurrency cap because request rate alone does not bound expensive long-running calls...

Boundaries and compatibility

Ideal for

  • Fair share design: produce a decision or artifact grounded in supplied evidence.
  • Burst handling: produce a decision or artifact grounded in supplied evidence.
  • Limit enforcement: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Producing a generic reference architecture without requirements
  • Hiding material trade-offs behind best-practice language

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.