AI DevKit · Structured SDLC workflow with 8 phases — requirements, design review, planning, implementation, testing, and code review. Use when the user wants to build a feature end-to-end, or run any individual phase (new requirement, review requirements, review design, execute plan, update planning, check implementation, write tests, code review).
AI DevKit · Document a code entry point with structured analysis, dependency mapping, and saved knowledge docs. Use when users ask to document, understand, or map code for a module, file, folder, function, or API.
AI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).
AI DevKit · Proactively orchestrate running AI agents — scan statuses, assess progress, send next instructions, and coordinate multi-agent workflows. Use when users ask to manage agents, orchestrate work across agents, or check on agent progress.
AI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.
AI DevKit · Review code, skills, and prompts for security vulnerabilities — OWASP Top 10, prompt injection, business logic flaws, and insecure defaults. Use when reviewing PRs, auditing modules, reviewing AI skills/prompts, or preparing for release.
AI DevKit · Analyze and simplify existing implementations to reduce complexity, improve maintainability, and enhance scalability. Use when users ask to simplify code, reduce complexity, refactor for readability, clean up implementations, improve maintainability, reduce technical debt, or make code easier to understand.
AI DevKit · Test-driven development — write a failing test before writing production code. Use when implementing new functionality, adding behavior, or fixing bugs during active development.