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umlforge_api_sequence

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Diagram how services call each other for a user action, including failure paths, retries, and error handling.

Instructions

Diagram how services call each other for a specific user action or API flow.

USE THIS WHEN:

  • You want to trace a request across multiple services (e.g. "user logs in")

  • You are designing API contracts between microservices

  • You need to show failure paths, retries, and error handling between services

  • You are writing QA test cases or doing incident post-mortems

NOT FOR:

  • Full codebase analysis → use umlforge_reverse_engineer

  • Async/event-driven messaging → use umlforge_event_driven

  • Frontend component interactions → use umlforge_frontend_components

  • Database schema design → use umlforge_erd_schema

Produces:

  • Sequence diagram: happy path + at least 2 failure paths, activation boxes, sync vs async arrows, performance boundary annotations

  • Inter-service dependency table: caller, callee, protocol, failure mode, mitigation

  • (report_mode=True) Design Score: Resilience, Performance, Contract Clarity (A–F)

Args: services: All participants, e.g. "API Gateway, Auth Service, Order Service, Payment Provider, User DB". user_journey: The action to diagram in plain English, e.g. "User places an order through checkout". report_mode: True → also produce a Design Score report. Pro/Team/Enterprise only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
servicesYes
report_modeNo
user_journeyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Description adds depth beyond annotations: explains produced artifacts (sequence diagram with failure paths, dependency table, optional report), and notes report_mode license restriction. No contradiction with annotations.

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

Conciseness4/5

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

Well-structured with headings and bullet-like sections, front-loaded purpose. Slightly verbose but all content earns its place.

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?

Given the tool's complexity (3 parameters, no nested objects, output schema exists), description covers inputs, outputs, constraints (license), and use cases thoroughly.

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

Parameters5/5

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

Despite 0% schema coverage, description fully explains each parameter: services as comma-separated list, user_journey as plain English action, report_mode with license caveat.

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?

Description clearly states it diagrams how services call each other for a specific user action or API flow. It also distinguishes from siblings with 'NOT FOR' examples.

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?

Explicitly lists when to use (trace request, design API contracts, failure paths) and when not to use, with named alternatives.

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

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