application

A NestJS application-layer guide for implementing use cases, command and query handlers, interfaces, application services, and read models. A use case is a piece of application behavior, while CQRS separates commands that change data from queries that read it.

In plain words
What is it for?
Use it to build bounded-context use cases, CQRS handlers, cross-module interfaces, reusable application services, Redis-backed read models, and orchestration across multiple services.
Why use it?
It helps choose an implementation pattern that matches the project and keeps coordination logic separate from business rules, storage, and HTTP details.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/softtor/nestjs-hexagonal/application
Any agent
npx skills add Softtor/nestjs-hexagonal --skill application
Clone the repo
git clone --depth 1 https://github.com/Softtor/nestjs-hexagonal

Made for: Claude Code, Codex.

Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,220 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00066 $0.04220
Opus 5 $0.00033 $0.02110
Sonnet 5 $0.00013 $0.00844
Haiku 4.5 $0.00007 $0.00422

Measured 2d ago against content hash fa867684abb6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

application scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/application/SKILL.md · 607 lines

How it starts

The opening of the file, as written. The whole thing — 607 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Note: Examples use companyId as the multi-tenant identifier. Replace with your project's term (e.g., organizationId, tenantId).

Application Layer

This skill covers everything inside a bounded context's application/ directory: use cases, CQRS handlers, DTOs, ports, application services, and Redis read models.


1. Pattern Selection

Work through this flowchart before writing a single line of code.

Does the module already use CQRS (CommandBus / QueryBus)?
├── No  → Pattern A (plain UseCase + TOKEN)
└── Yes →
        Is this a simple read (findById) with no RBAC or transformation?
        ├── Yes → Skip use case — inject repository directly in controller
        └── No  →
                Does orchestration span multiple services (QueryBus calls,
                multiple ports, complex enrichment)?
                ├── Yes → Pattern C (Handler as Orchestrator)
                └── No  → Pattern B (CQRS Command/Query)

Need read model / projections?
└── CQRS R/W separation: write side → Pattern B/C, read side → Redis query handler
    (see references/read-model-patterns.md)

Reusable logic between 2+ handlers?
└── Extract into Application Service (@Injectable, in application/services/)

Shared domain logic (no I/O, no framework)?
└── Extract into Domain Service (plain class, in domain/services/)

2. Pattern A — Plain UseCase with TOKEN

Use when the context uses plain use cases without CQRS (e.g., customers, contacts).

Directory layout

application/
├── dtos/
│   └── create-<context>.dto.ts
└── usecases/
    ├── create-<context>.usecase.ts
    └── __tests__/
        └── create-<context>.usecase.spec.ts

DTO

// application/dtos/create-<context>.dto.ts
export namespace Create<Context>Dto {
  export interface Input {
    companyId: string;
    name: string;
    // add domain-specific fields
  }

  export interface Output {
    id: string;
    companyId: string;
    name: string;
    createdAt: Date;
  }
}

Read the full file on GitHub · 607 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 607 lines · 0 tokens per session scan A fa867684abb6

Subscribe to this mod's changes

application is a skill published in the GitHub repository Softtor/nestjs-hexagonal (5 stars, last pushed 22d ago), licensed MIT. It adds 66 tokens to every session and 4,220 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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