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Architecture · Version 1.3.0 · Reviewed 2026-08-02

Configuration-Driven Feature Advisor

Make a defensible decision about config versus code and validation strategy with evidence, explicit trade-offs, and a verification plan.

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

Decides when behavior belongs in configuration rather than code, and how to keep it safe.

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What this skill helps you do

  • Config versus code
  • Validation strategy
  • Change safety

How Configuration-Driven Feature Advisor works

You provide

Requirements, constraints, and the current topology

It inspects

Critical path and failure boundaries for config versus code

It decides

A validation strategy decision with consequences recorded

You verify

Rollout stages with the signal that gates each one

What it checks first

Configuration-Driven Feature Advisor decides when behavior belongs in configuration rather than code, and how to keep it safe. Use it when the work involves Config versus code, Validation strategy, Change safety.

  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. Map the artifact, actors, boundaries, and invariants relevant to config versus code.
  2. Trace concrete failure or abuse paths for validation strategy; do not report checklist items without a mechanism.
  3. Prioritize change safety findings by impact, likelihood, confidence, and cost of correction.
  4. Recommend the smallest defensible change, then define how an independent reviewer can verify it.

Deliverables

  • Config versus code assessment
  • Validation strategy decision and action plan
  • Change safety 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

Sales wants per-customer behavior changes without a deploy. How much should we push into configuration?

Expected output

Configuration that can change behavior is code with worse tooling: no review, no tests, no rollback. Push only bounded, enumerable choices into config, validate against a schema, and require the same review path for anything that changes logic...

Boundaries and compatibility

Ideal for

  • Config versus code: produce a decision or artifact grounded in supplied evidence.
  • Validation strategy: produce a decision or artifact grounded in supplied evidence.
  • Change safety: 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.