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ai_sdlc_platform
ai_sdlc_platform에는 mehuldil에서 수집한 skills 38개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
Generate Sprint Stories from Master Story + sprint scope — ADO-ready PRD lift, UI/Figma, non-redundant sections
Generate Master Stories (feature-level) from PRD — for Sprint Stories use sprint-story-generator; for tech tasks use tech-task-generator
Understands natural English language queries and converts them to SDLC commands. Supports hybrid pattern matching + AI understanding. Asks for ADO work item if missing, shows non-closed items for quick selection. Works with any stage, any role.
One-command setup for AI-SDLC IDE Plugin. Installs dependencies, creates env, bootstraps .sdlc/, wires Claude Code commands, Cursor MCP, and validates everything.
Security validation for Java/TEJ/Spring backend code
Backend developer skill for Java 17, TEJ, RestExpress, Kafka, Gradle, PostgreSQL
Executive reporting - delegates to orchestrator/reporting/ for dashboards
Validate bundle size budgets, analyze package dependencies, detect redundancy, flag security vulnerabilities
Enforce module boundaries, detect circular dependencies, validate layer separation and import rules
Comprehensive profiling across CPU, memory, render, network, battery, and startup performance dimensions
Generate optimization recommendations and validate performance improvements against budgets and targets
Generate security remediation steps, fix strategies, and implementation guidance for vulnerabilities and issues
Full security pass (deps, AppSec, stability) — for secrets-only use shared/secrets-detector first
Frontend atomic skills - delegates to orchestrator/frontend/ for coordination
Performance testing skill - JMeter, Argo, load profiles, NFR validation
Product management — PRD, Master/Sprint stories (ADO-ready), analytics, gap analysis
QA atomic skills - delegates to orchestrator/qa/ for test coordination
Release management skill - release notes, compliance, SDLC reports
Enforce coding standards, guidelines compliance, and language style consistency
Detect state conflicts between local memory and Azure DevOps by comparing attributes and identifying divergences
Resolve state conflicts using 4 deterministic strategies (accept ADO, push local, manual merge, retry)
Generate OpenAPI, DB schema, and message schema contracts from design specifications
Auto-tag cross-team dependencies and track blocker relationships
Convert non-Markdown documents (docx, xlsx, pptx, html, pdf) to Markdown before AI processing
Atomic unit-test generation or validation against repo harness and coverage rule
Detect resource conflicts, skill gaps, and schedule blockers
Validate PR structure, naming, metadata, and file location conventions
PRD validation — completeness, clarity, testability, feasibility, and ADO-ready copy tables
Pre-grooming brief — team context, risks, aligned to story templates and AUTHORING_STANDARDS
Atomic skill — detect secrets, credentials, and sensitive strings in code and config (invoke before broader security-scan)
Merge state from local memory and ADO across branches, managing tags, comments, and metadata
Validate Master and Sprint Stories — template sections, ADO-ready PRD lift, UI/Figma, non-redundancy, AC quality
Atomic Azure Boards sync — compose with ask-first CRUD; use observer for inbound events
Generate Tech Stories grounded in system design, Master Story, and Sprint Story — implementation SSoT, impact, non-regression
Expand Sprint Story (+ Tech Story when present) into task files — traceability, regression, no invented scope
Atomic doc update — align README, wiki paths, ADRs, and User_Manual when behavior or contracts change
TPM skill - cross-pod coordination, dependency management, pre-grooming
UI/UX Designer skill - Figma fidelity, design system, component specifications