aiup-core

aiup-core is the stack-independent foundation of the AI Unified Process. It turns a product vision into requirements, an entity model, use cases, and test journeys that stack-specific plugins can implement.

Use this plugin for every AI Unified Process project. It works with any programming language because its output boundary is a set of reviewable files under docs/.

Skills and workflow

Inception          Elaboration                             Construction
─────────────     ───────────────────────────────────     ──────────────────────────────────────────────────
/requirements  →  /entity-model  →  /use-case-diagram  →  /use-case-spec  →  /test-case
                                                    └→  /business-process  ↗

Each skill reads the artifacts created by earlier steps. The linked SKILL.md files are the authoritative reference for detailed inputs, outputs, and behavior.

Installation

Tessl

Initialize the project once:

tessl init --agent agents

agents is the vendor-neutral layout; use claude-code, cursor, gemini, codex, copilot, or copilot-vscode for a specific host. Then install the plugin:

tessl install ai-unified-process/aiup-core

Depending on the configured agent, skills may be exposed as slash commands or invoked by intent, for example "create the requirements catalog".

Claude Code

/plugin marketplace add ai-unified-process/marketplace
/plugin install aiup-core

See the marketplace installation guides for other agents and manual adoption.

Prerequisites

For the forward workflow, create docs/vision.md in the target project. It should describe the product mission, target users, goals, scope, and constraints. The marketplace provides a vision template.

Existing projects can begin with /reverse-engineer instead of a vision document.

Inputs and generated artifacts

your-project/
└── docs/
    ├── vision.md                    # maintained by the team
    ├── requirements.md              # /requirements
    ├── glossary.md                  # /requirements (domain terms and synonyms to avoid)
    ├── entity_model.md              # /entity-model
    ├── use_cases.puml               # /use-case-diagram
    ├── processes/
    │   └── BP-001-*.bpmn            # /business-process (optional), read by /test-case
    ├── use_cases/
    │   └── UC-001-*.md              # /use-case-spec
    └── test_cases/
        └── TC-001-*.md              # /test-case

/spec-review checks these files against each other. Its bundled script spec_lint.py needs only Python and can run as a blocking CI gate; accepted findings of an existing project go into docs/.spec-lint-baseline.json. /spec-review report writes docs/spec-report.html: requirement coverage, the traceability matrix, and the findings on one page.

Review and commit these files with the source code. Stack plugins consume the entity model, use case specifications, and test journeys without depending on which coding agent produced them.

Project structure

aiup-core does not impose a source-code layout. It writes only to the documentation paths above and inspects an existing source tree when /reverse-engineer runs. The selected stack plugin detects or documents the implementation layouts it supports.

MCP servers

Related documentation

• Getting started
• Workflow and artifacts
• Project setup
• Choose a stack plugin

License

Apache-2.0 · © 2025-2026 Simon Martinelli and the AI Unified Process contributors

See LICENSE and NOTICE. "AI Unified Process" identifies the original methodology; derived works must retain the NOTICE file and must not present themselves as the official AI Unified Process.