ai-sdlc

Run the full AI-SDLC pipeline — plan, create Jira tickets, design architecture, implement, test, review, and fix bugs. Agents coordinate through Jira as the message bus.

Use this agent when the AI-SDLC orchestrator needs technical specifications designed for Jira stories. Spawned during Phase 3 (Architecture). <example> Context: Stories created in Jira, need tech specs user: "/sdlc PROJ-100" (resuming, stories in To Do) assistant: "I'll spawn the sdlc-architect agent to design tech specs for the stories." <commentary> Stories need technical design before development can begin. </commentary> </example> <example> Context: New stories need architecture design user: "Design the technical approach for these stories" assistant: "I'll spawn the sdlc-architect agent to create tech specs and update Jira." <commentary> Architect agent handles all technical design work in the SDLC pipeline. </commentary> </example>

Use this agent when the AI-SDLC orchestrator needs to fix bugs found by the tester or QA reviewer. Spawned during Phase 7 (Bug Fix) for Bug sub-tasks. <example> Context: Tests failed, bug sub-task created user: "/sdlc PROJ-100" (bug PROJ-110 needs fixing) assistant: "I'll spawn the sdlc-bug-fixer agent to fix PROJ-110." <commentary> Bug fixer handles test failures and QA-reported issues. </commentary> </example> <example> Context: QA found issues, bug tickets created user: "Fix the bugs found in QA review" assistant: "I'll spawn sdlc-bug-fixer agents for each bug ticket." <commentary> Bug fixer resolves issues and sends the story back through the pipeline. </commentary> </example>

Use this agent when the AI-SDLC orchestrator needs code implemented for a Jira story. Spawned during Phase 4 (Implementation) for each story in "Ready for Dev" status. <example> Context: Story has a tech spec, ready for implementation user: "/sdlc PROJ-100" (story PROJ-105 is Ready for Dev) assistant: "I'll spawn the sdlc-developer agent to implement PROJ-105." <commentary> Developer agent picks up stories with tech specs and writes the code. </commentary> </example> <example> Context: Multiple stories ready for parallel development user: "Implement the next batch of stories" assistant: "I'll spawn sdlc-developer agents for each independent story." <commentary> Multiple developer agents can run in parallel for independent stories. </commentary> </example>

Use this agent when the AI-SDLC orchestrator needs to create Jira tickets from an approved plan. Spawned by the /sdlc command during Phase 2 (Jira Creation). <example> Context: SDLC plan approved, need to create tickets user: "The plan is approved, create the Jira tickets" assistant: "I'll spawn the sdlc-jira-creator agent to create the epic and stories in Jira." <commentary> Plan approved by user, orchestrator triggers Jira creation. </commentary> </example> <example> Context: Creating tickets from a structured project breakdown user: "/sdlc plan.md" (after plan approval) assistant: "I'll spawn the sdlc-jira-creator to populate Jira with the planned stories." <commentary> Automated ticket creation as part of the SDLC pipeline. </commentary> </example>

Use this agent when the AI-SDLC orchestrator needs to break down a project into epics and stories with acceptance criteria. This agent is spawned by the /sdlc command during Phase 1 (Planning). <example> Context: SDLC orchestrator starting a new project user: "/sdlc build a Jira ticket analytics tool" assistant: "I'll spawn the sdlc-planner agent to break down this project into epics and stories." <commentary> The orchestrator triggers the planner for any new project entering the SDLC pipeline. </commentary> </example> <example> Context: SDLC orchestrator with an existing plan file user: "/sdlc /path/to/plan.md" assistant: "I'll spawn the sdlc-planner agent to refine this plan into implementable stories." <commentary> Even with an existing plan, the planner structures it into the epic/story format with acceptance criteria. </commentary> </example>

AI-SDLC Jira conventions and context protocol. This skill provides the standard templates, workflow states, and context-passing protocol used by all AI-SDLC agents. It is loaded as reference material by the /sdlc command and individual agents — not invoked directly. Use this skill when working with the AI-SDLC pipeline, when you need to understand how agents coordinate through Jira, or when creating/modifying SDLC agent definitions.