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Found 176 Skills
Systematic documentation authoring workflow for AI coding agents. Analyzes repositories to determine what documentation is needed, classifies each document by Diataxis type (tutorial, how-to, reference, explanation), and generates accurate, maintainable documentation that stays synchronized with the codebase. Handles greenfield projects (no docs exist), brownfield updates (refresh, enhance, rewrite existing docs), and doc audits with workflow-specific guidance for each. Use when the user requests documentation for a project: README creation, API reference, architecture docs, developer guides, changelogs, or any technical writing tied to a codebase. Also use when existing docs need auditing, updating, rewriting, or restructuring. Triggers on phrases like "write a README", "document this project", "API reference", "architecture doc", "developer guide", "getting started guide", "tutorial", "how-to", "audit our docs", "what docs are missing", "refresh the docs", "Diataxis", "doc the public API", "write a CHANGELOG", "explain this codebase", "onboarding doc", or "ADR". Triggers when creating or editing `README.md`, `CONTRIBUTING.md`, `CHANGELOG.md`, `docs/`, `mkdocs.yml`, `docusaurus.config.*`, `sphinx`/`conf.py`, ADRs, or any markdown file paired with code. Triggers when public APIs, CLI flags, configuration options, or environment variables change and the user wants the docs kept in sync. Do NOT use for standalone prose, marketing copy, blog posts, design documents, RFCs unrelated to a codebase, or documents where the source of truth is not source code.
Weighted decision scoring framework for architectural and technology choices. Frames decisions with 2-4 options, scores against weighted criteria, detects close calls, and records decisions in the active ADR or task plan. Use when: "should I use X or Y", "which approach", "compare options", "trade-offs between", "help me decide", "evaluate alternatives"
Use when the user needs system design, architecture decision records, scalability analysis, trade-off evaluation, or non-functional requirements planning. Triggers: new system design, technology selection, scaling strategy, ADR creation, infrastructure topology, service boundary definition.
One-shot viral game pipeline — turn a tweet, news story, or short prompt into a scaffolded, designed, deployed, and monetized browser game in roughly 10 minutes. Use when the user says "make a viral game", "build a game from this tweet", "turn this story into a game", "/viral-game", or provides a tweet URL / short concept they want shipped end-to-end fast. Do NOT use when the user wants to design and build a real game project with milestones, ADRs, or multi-session iteration — use `/make-game` for that. Also do NOT use for modifying existing games (use `/add-feature` or `/improve-game`).
Design data architecture at enterprise and solution levels. Cover data mesh, lakehouse, governance, domain-driven design, conceptual/logical/physical data modeling, platform selection, and compliance frameworks. Produce ADRs, data model diagrams, platform comparison matrices, and governance policy templates. Triggers on "design data platform", "choose data warehouse", "data mesh", "lakehouse architecture", "data governance", "data modeling", "platform selection", "data architecture decision", "compliance framework", or "data strategy". For applied AI solution architecture (RAG data plane, embeddings, vector stores in commercial or enterprise products), use applied-ai-architect-commercial-enterprise. For dbt analytics layers and mart delivery, use analytics-data-engineer—not data-architect.
Build and maintain project-specific review policy for `agentic-review` by combining repository docs (`AGENTS.md`, `ENGINEERING.md`, `CONTEXT.md`/`CONTEXT-MAP.md`, ADRs), repository-mined conventions, and structured user input, then writing machine-usable policy files under `<docs-dir>/review/policies/`, including audit-governance metadata consumed by `agentic-review`. Use when the user wants architecture integrity checks (onion/clean/hexagonal), module-specific review rules, dependency-direction policy, naming/inheritance convention enforcement, stricter project/domain review standards, or explicit auditability requirements for specialist review coverage.
Break a single epic into implementable story files. Reads the epic, its GDD, governing ADRs, and control manifest. Each story embeds its GDD requirement TR-ID, ADR guidance, acceptance criteria, story type, and test evidence path. Run after /create-epics for each epic.
Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.
Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
Design software architectures with appropriate patterns for scale, maintainability, and team structure. Covers layered, hexagonal, event-driven, CQRS, and modular monolith architectures. Produces architecture decision records, component diagrams, and dependency maps. Prevents over-engineering, premature distribution, and architectural drift.
Expert in designing high-level enterprise solutions. Specializes in TOGAF adaptation, trade-off analysis, and aligning technology with business strategy.
Invoke for complex multi-step tasks requiring intelligent planning and multi-agent coordination. Use when tasks need decomposition, dependency mapping, parallel/sequential/swarm/iterative execution strategies, or coordination of multiple specialized agents.