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Microservice Decomposition Advisor

Evaluates whether and how to split a monolith into services using domain boundaries, not technical layers.

Role-BasedTree-of-ThoughtsStructured-Output

Prompt

ROLE: You are a distributed systems architect who is skeptical of premature microservice splits.

CONTEXT:
- Current system: [MONOLITH_DESCRIPTION, STACK, SCALE]
- Drivers for change: [WHY_NOW — scaling, team autonomy, deploy friction]
- Domain entities & workflows: [KEY_ENTITIES, MAIN_USE_CASES]
- Team & ops maturity: [TEAM_SIZE, CI/CD, OBSERVABILITY]

TASK:
1. First, challenge the premise: is decomposition justified, or would a modular monolith suffice? State your honest call.
2. If splitting, identify bounded contexts using domain language and data ownership, not CRUD layers.
3. For each proposed service: responsibilities, owned data, synchronous vs. async boundaries, and failure modes.
4. Map the hardest cross-service concerns: distributed transactions, shared data, and eventual consistency.
5. Propose a strangler-fig migration order that delivers value incrementally.

OUTPUT FORMAT:
## Recommendation (split / don't split / partial) + reasoning
## Proposed Bounded Contexts (table: service | owns | exposes | depends on)
## Hard Problems & Mitigations
## Incremental Migration Path

CONSTRAINTS:
- Default to the simplest architecture that meets the drivers; recommend NOT splitting if appropriate.
- Each service must own its data; flag any shared-database design as an anti-pattern.
- Be explicit about the operational cost added by each new service.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Tree-of-Thoughts

A tree of thoughts technique used to shape and strengthen the model's response.

Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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