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umlforge_event_driven

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Design event-driven messaging architectures, modeling producer-broker-consumer flows with failure handling. Supports Kafka, SQS, RabbitMQ, event sourcing, and pub/sub patterns.

Instructions

Design an event-driven or async messaging architecture (Kafka, SQS, RabbitMQ, etc.).

USE THIS WHEN:

  • Services communicate via events or messages (not direct API calls)

  • You are designing event sourcing, CQRS, or pub/sub patterns

  • You want to model producer ? broker ? consumer flows with failure handling

NOT FOR:

  • Synchronous REST/gRPC calls between services ? use umlforge_api_sequence

  • Entity lifecycle (Order goes pending ? active) ? use umlforge_state_machine

  • Full system architecture overview ? use umlforge_stakeholder_arch

Produces:

  • Event flow sequence: producers ? broker ? consumers with ack, retry loops (max N), dead-letter queue handling

  • Event catalogue table: name, producer, consumers, payload, idempotency, retention

  • Choreography vs orchestration assessment with coupling risk flags

  • Failure mode analysis: scenario, impact, detection, recovery

  • (report_mode=True) Event System Analysis Notes: reliability risks, idempotency gaps, resilience quick wins

Args: system_context: What this event-driven system does and why it uses messaging. producers: Services that emit events (e.g. "Order Service emits order.placed"). consumers: Services that consume events (e.g. "Notification, Inventory, Analytics"). broker: Message broker (e.g. "Kafka", "RabbitMQ", "AWS SQS/SNS") (optional). events: Named domain events (e.g. "order.placed, payment.failed") (optional). report_mode: True ? also produce Event System Analysis Notes. Pro/Team/Enterprise only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brokerNo
eventsNo
consumersYes
producersYes
report_modeNo
system_contextYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A4.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=false, and destructiveHint=false, so the safety profile is covered. The description adds useful output-shape context (retry loops, DLQ handling, failure mode analysis, report_mode gating) but does not disclose runtime behavior beyond that, such as generation time, determinism, or external calls. Given the annotation coverage, a 3 is appropriate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tightly structured with single-line bullets under USE THIS WHEN, NOT FOR, Produces, and Args. Every line is front-loaded and adds distinct information; no filler or repetition of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a design-generation tool with six parameters, required/optional split, an output schema, and rich annotations, the description covers purpose, exclusions, expected artifacts, and parameter intent. Nothing an agent needs to invoke or route this tool is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the burden. It documents all six parameters with examples for producers, consumers, broker, and events, and explains report_mode with its entitlement constraint. system_context is described as intent rather than format, which is the only minor gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Design an event-driven or async messaging architecture (Kafka, SQS, RabbitMQ, etc.)'. It also explicitly names which sibling tools to use for adjacent concerns (umlforge_api_sequence, umlforge_state_machine, umlforge_stakeholder_arch), so an agent can disambiguate without inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit USE THIS WHEN and NOT FOR sections that name the exact alternative tool for each excluded scenario (synchronous REST/gRPC, entity lifecycle, full system architecture). This goes beyond when-to-use into when-not and how-to-route, leaving nothing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.