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[](https://versuz.dev/skills/jmagly-aiwg-plugins-sdlc-skills-sdlc-quickref)Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install jmagly-aiwg-plugins-sdlc-skills-sdlc-quickrefgit clone https://github.com/jmagly/aiwg.gitcp aiwg/SKILL.MD ~/.claude/skills/jmagly-aiwg-plugins-sdlc-skills-sdlc-quickref/SKILL.md--- name: sdlc-quickref namespace: aiwg platforms: [all] kernel: true description: SDLC framework quick reference — phase model, capability domains, and curated discovery phrases that surface the right skill on `aiwg discover` --- # SDLC Framework — Quick Reference This is your always-loaded directory for the AIWG **SDLC framework** (300+ skills). It does **not** list every skill. Instead, it teaches you the framework's mental model and gives you **curated search phrases** that map to `aiwg discover` lookups. Use the phrases — each is validated to surface its target skill in the top-3 ranked results. ## Canonical access pattern: discover → show When you find a candidate via `aiwg discover`, fetch its body with `aiwg show <type> <name>`. **Never** use `find`, `ls`, `Glob`, or direct `Read` on `<provider>/skills/` paths — those reflect the kernel-pivot deploy state, not the full surface. ```bash aiwg discover "<phrase>" # find — returns ranked candidates aiwg show skill <name> # fetch — streams the SKILL.md body ``` If your platform's Skill tool errors on a non-kernel skill (expected — most aren't kernel), the fallback is `aiwg show`, never filesystem browsing. Last-resort if `aiwg` itself is broken: read directly from `$AIWG_ROOT/agentic/code/...` (the canonical corpus, always present). ## How to use this quickref 1. Identify which **capability domain** the user's need belongs to (table below) 2. Pick a **curated phrase** from that domain (or paraphrase the user's words) 3. Run `aiwg discover "<phrase>"` and surface the top match (or top-3) to the user 4. If no curated phrase fits, improvise — `aiwg discover` is forgiving with natural language **Do not enumerate skills from memory.** The framework ships hundreds of skills and the kernel set you can see is just the orientation layer. ## What this framework is for End-to-end software-development-lifecycle support. Phase-based workflows (Inception → Elaboration → Construction → Transition → Production) with multi-agent artifact generation, gate criteria, traceability, and 100+ document templates. ## Capability domains | Domain | Covers | |---|---| | **Project bootstrap** | Starting a new project, scaffolding intake, scanning a codebase to seed an SDLC corpus | | **Phase transitions** | Moving between Inception / Elaboration / Construction / Transition / Production | | **Continuous workflows** | Recurring cycles: requirements, architecture, tests, security, performance, risk | | **Quality gates** | Phase-boundary validation, traceability, gate criteria | | **Team & process** | Onboarding, knowledge transfer, retrospectives, cross-team sync | | **Production & ops** | Deployment, hypercare, incident response | | **Compliance** | Regulatory frameworks (SOC2, GDPR, HIPAA, PCI-DSS) and change control | | **Artifact generation** | Architecture docs, ADRs, test plans, deployment plans, runbooks | ## Curated discovery phrases Each phrase has been tested — running it through `aiwg discover` returns the listed skill in the top-3 ranked results. Use them verbatim or as a starting point for your own phrasing. ### Project bootstrap ```bash aiwg discover "start a new project" # → new-project (score 1.00) aiwg discover "scan codebase for intake" # → intake-from-codebase aiwg discover "intake wizard" # → intake-wizard ``` ### Phase transitions ```bash aiwg discover "inception to elaboration" # → flow-inception-to-elaboration aiwg discover "elaboration to construction" # → flow-elaboration-to-construction aiwg discover "construction to transition" # → flow-construction-to-transition aiwg discover "concept to inception" # → flow-concept-to-inception ``` ### Continuous workflows ```bash aiwg discover "risk management cycle" # → flow-risk-management-cycle (score 0.93) aiwg discover "execute test strategy" # → flow-test-strategy-execution aiwg discover "performance optimization cycle" # → flow-performance-optimization aiwg discover "security review cycle" # → flow-security-review-cycle aiwg discover "requirements evolution" # → flow-requirements-evolution aiwg discover "architecture evolution" # → flow-architecture-evolution aiwg discover "iteration dual track" # → flow-iteration-dual-track aiwg discover "delivery track" # → flow-delivery-track aiwg discover "discovery track" # → flow-discovery-track ``` ### Quality gates ```bash aiwg discover "phase gate check" # → flow-gate-check aiwg discover "gate evaluation" # → gate-evaluation aiwg discover "traceability check" # → check-traceability aiwg discover "handoff checklist" # → flow-handoff-checklist ``` ### Team & process ```bash aiwg discover "team onboarding" # → flow-team-onboarding (score 1.00) aiwg discover "knowledge transfer" # → flow-knowledge-transfer aiwg discover "retrospective" # → flow-retrospective-cycle (score 1.00) aiwg discover "cross-team synchronization" # → flow-cross-team-sync (score 1.00) ``` ### Production & ops ```bash aiwg discover "deploy production" # → flow-deploy-to-production (score 0.51) aiwg discover "production hypercare" # → flow-hypercare-monitoring aiwg discover "production incident triage" # → flow-incident-response (score 0.55) ``` ### Compliance ```bash aiwg discover "compliance validation" # → flow-compliance-validation (score 1.00) aiwg discover "change control" # → flow-change-control ``` ### Artifact generation ```bash aiwg discover "create SAD" # → artifact-orchestration (score 1.00) aiwg discover "generate use case realization" # → generate-realization aiwg discover "build proof of concept" # → build-poc aiwg discover "decision support matrix" # → decision-support ``` ## Mental model — the phase machine ``` Inception (4-6w) → Elaboration (4-8w) → Construction (8-16w) → Transition (2-4w) → Production │ │ │ │ LO milestone LA milestone IOC milestone PR milestone ``` - **Inception** — validate problem, vision, risks, business case - **Elaboration** — detailed requirements, architecture baseline, risk retirement, test strategy - **Construction** — feature implementation, automated testing, security validation, performance - **Transition** — production deployment, UAT, support handover, hypercare (2-4w) - **Production** — ongoing operations, incident response, feature iteration Cross-cutting: risk-management, architecture-evolution, requirements-evolution, security-review, performance-optimization, test-strategy run continuously across all phases. ## Artifact directory layout All SDLC artifacts go under `.aiwg/`: ``` .aiwg/ ├── intake/ # Project intake forms, solution profiles ├── requirements/ # Use cases, user stories, NFRs ├── architecture/ # SAD, ADRs, diagrams ├── planning/ # Phase and iteration plans ├── risks/ # Risk register ├── testing/ # Test strategy, plans ├── security/ # Threat models, security gates ├── deployment/ # Deployment plans, runbooks ├── working/ # Temporary scratch (safe to delete) └── reports/ # Generated reports ``` ## When the curated phrases don't fit Improvise. The discovery scorer uses trigger phrases (4× weight), capability descriptions (2× weight), titles, tags, summaries, and paths. Multi-token queries require ≥50% token overlap, so noise queries return zero results. ```bash aiwg discover "<your need, paraphrased>" --limit 5 ``` If the top-3 results all score below ~0.20, the framework genuinely may not have a curated skill for that need. Then you can improvise — but always check first. ## Anti-pattern: don't enumerate If a user asks "what SDLC skills are available?" or "what can the SDLC framework do?", **do not list from this skill or from memory**. Run: ```bash aiwg discover --type skill --limit 20 "<their interest area>" ``` This skill is the orientation layer; the index is the lookup. Enumerating from memory means you're treating the kernel set as exhaustive — which it deliberately isn't.