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Code Quality · Version 1.1.0 · Reviewed 2026-08-02

Domain Language Reviewer

Make a defensible decision about ubiquitous language and concept boundaries with evidence, explicit trade-offs, and a verification plan.

4 method steps 5 documented failure modes 4 diagnostic checks 7 quality gates

Aligns code vocabulary with the business domain so the model stays legible as the product grows.

₹99 one-time

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What this skill helps you do

  • Ubiquitous language
  • Concept boundaries
  • Naming consistency

How Domain Language Reviewer works

You provide

The code, its invariants, and how failures currently surface

It inspects

Error paths and lifetime handling for ubiquitous language

It decides

A concept boundaries change that makes invalid states unrepresentable

You verify

A deliberately invalid input fails clearly at the boundary

What it checks first

Domain Language Reviewer aligns code vocabulary with the business domain so the model stays legible as the product grows. Use it when the work involves Ubiquitous language, Concept boundaries, Naming consistency.

  1. Whether errors are handled where they can be resolved or merely passed upward with less context.
  2. Whether types make invalid states unrepresentable or merely document intent.
  3. Ownership and lifetime of resources, and whether every path releases what it acquired.
  4. Whether abstractions hide complexity or relocate it somewhere harder to inspect.

Failure modes it recognizes

  • A caught exception logged and swallowed, allowing execution to continue with invalid state.
  • Error types collapsed into a single generic type, losing the ability to handle cases differently.
  • Nullable fields encoding several distinct meanings, forcing every caller to guess.
  • A helper abstraction with one caller, which adds indirection without removing duplication.
  • Silent coercion masking a type mismatch until it surfaces as corrupt data.

Answers it will reject

  • Rewriting for elegance without a behavioral test suite, which converts known code into unknown risk.
  • Adding a lint rule to enforce a pattern nobody has justified.
  • Treating warnings as noise, which trains the team to ignore the one that matters.

Decision rules it applies

  • Fail fast on invalid state rather than continuing with a defaulted value.
  • Encode invariants in types and constraints where the language allows it.
  • Prefer local clarity over global cleverness; the reader is the constraint.

Evidence it asks for

  • Confirm each error path is exercised by a test rather than assumed correct.
  • Check that a deliberately invalid input produces a clear failure at the boundary.
  • Compare behavior before and after refactoring with characterization tests.

The method inside

  1. Map the artifact, actors, boundaries, and invariants relevant to ubiquitous language.
  2. Trace concrete failure or abuse paths for concept boundaries; do not report checklist items without a mechanism.
  3. Prioritize naming consistency 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

  • Ubiquitous language assessment
  • Concept boundaries decision and action plan
  • Naming consistency 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

The same concept is called order, purchase, and transaction in different parts of our codebase and it causes real bugs.

Expected output

Three names usually means three subtly different concepts that were never separated, not one concept named badly. Define each precisely with the business, then decide whether they merge or stay distinct before renaming anything...

Boundaries and compatibility

Ideal for

  • Ubiquitous language: produce a decision or artifact grounded in supplied evidence.
  • Concept boundaries: produce a decision or artifact grounded in supplied evidence.
  • Naming consistency: 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.