Development Skill
Angular Migration
Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and…
$15
CQRS Implementation
Implement Command Query Responsibility Segregation for scalable architectures.
A comprehensive implementation guide for Command Query Responsibility Segregation, separating your write model from your read model so each can be optimized and scaled independently. It pairs the architecture with production-ready Python templates: command and query buses, handlers, read-model projections, and a synchronizer that keeps reads in sync with events. You get the patterns to write through validated commands, read from denormalized views, and handle eventual consistency without surprises.
$15 one-time
Add to a kit → Prices include 20% VAT. · Forged on real agency work · one-time, no lock-in
- Type Skill
- Category Development
- Delivery Email · instant
- License One-time
Inside the run · no black box
See the actual work before you buy it.
The skill builds and operates two separate paths for the same data, a write side and a read side, wired together by events. The loop it executes:
- Routes every state change as a Command through a command bus. The handler runs three validation layers before anything is persisted: syntactic (type and format checks), semantic (business rules like stock availability), and concurrency (expected version for optimistic locking).
- A valid command produces domain events appended to the event store as immutable facts. The write model never gets UPDATEd in place, only new events are added.
- A projector process tails the event log from its last checkpoint, applies each relevant event to denormalized read tables (flat, join-free views like OrderSummary), and saves the new checkpoint position.
- Queries go through a separate query bus straight to those read tables: paginated, filtered, optimized per query pattern. New query need? A new projection is added instead of bending the existing schema.
- For read-your-writes consistency, the query handler can poll the projection version until it catches up to the command's expected version, with a timeout that returns stale data plus an explicit warning.
- Every projection ships with a rebuild mechanism: clear the read model, reset the checkpoint to zero, replay all events. A corrupted read model is disposable, the event log is the single source of truth.
One power source. 6 lines out.
cqrs-implementation · core
core active · 6 lines
- ✓ scaling reads independen…
Scaling reads independently from writes under heavy query load
- ✓ building an event-sourced
Building an event-sourced system with an append-only event log
- ✓ optimizing complex repor…
Optimizing complex reporting queries with denormalized read models
- ✓ rebuilding a corrupted or
Rebuilding a corrupted or newly-needed projection from the event stream
- ✓ handling read-your-write…
Handling read-your-writes consistency right after a command
- ✓ wiring command and query
Wiring command and query buses into a FastAPI application
Yours to keep.
Drag time forward. Watch what stays.
Forever
That's what owning means.
The rented stack
ai writing tool: subscription
expired · access lostanalytics suite: subscription
expired · access lostdesign platform: subscription
expired · access lost(nothing left)
Your forge
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Read and write sides scale and evolve independently instead of fighting one model
license: perpetual -
Query performance improves through denormalized, join-free read views
license: perpetual -
Any read model can be rebuilt from scratch, making projections disposable and recoverable
license: perpetual -
Eventual consistency is managed with defined SLAs rather than left to chance
license: perpetual
subscriptions expire · deeds don't
Everything in the box.
Pick a piece up. Watch it work.
Command infrastructure templates: base command, handlers, and a command bus
6 parts · one working system · ships instantly by email
This wasn't forged for everyone.
- Not for you if you'd rather rent a tool than own one.
- Not for you if you want someone else to run your stack.
- Not for you if you're happy guessing.
Backend engineers and architects building scalable, event-driven systems that need independent read and write models and high-performance queries.
then this was forged for you.Works with
Universal by design: these run in any AI. Delivered in the open Agent Skills + MCP format (native in Claude); ChatGPT, Gemini, Cursor and Copilot adapt the same files their own way.
- Claude Native format
- ChatGPT Adapts via open standards
- Gemini Adapts via open standards
- Cursor Adapts via open standards
- Copilot Adapts via open standards
Catch what's on your mind.
the air is clear. nothing between you and the forge.
catch a spark: the forge will answer
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The templates are Python. Is the guidance useful if my stack is not Python?
The command and query buses, handlers and projection templates are Python, but the separation pattern itself is language-agnostic. You can port the structure, and the ready-made code just saves time if you are already on Python.
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Does splitting the read and write model force eventual consistency on me?
Often yes, especially once you add the append-only event log and read-model projections. That is the trade you accept for scaling reads independently, so the guide treats consistency as a deliberate design choice rather than hiding it.
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How do I know CQRS is right for my app and not overkill?
It pays off under heavy query load, complex reporting or event sourcing, where one model cannot serve both sides well. For a straightforward CRUD app the added moving parts usually cost more than they return, and the guide is honest about that line.
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How is it delivered?
By email right after purchase: ready to run, downloaded instantly, no setup wait.
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One-time or subscription?
A one-time purchase; no subscription or hidden fees. VAT (20%) is included.
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Can I get a refund?
As a digital product, it can’t be refunded once downloaded. That’s why we show exactly what’s inside and who it’s for, right here.