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meetup-coding-with-ai
meetup-coding-with-ai에는 SebastienDegodez에서 수집한 skills 22개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
Use when running mutation testing, killing mutants, verifying test quality, checking mutation score, or analyzing survivors after the test baseline is green
Use when selecting architecture patterns for a new feature, performing Event Modeling, defining bounded contexts, choosing DDD tactical patterns, evaluating pattern fitness, or understanding how patterns compose. Covers Event Modeling methodology, DDD strategic design, DDD tactical patterns, Clean Architecture, CQRS, and Event Sourcing.
Use when reviewing DESIGN artefacts (event models, ADRs, component diagrams, context maps, interface contracts) for quality, DDD compliance, architectural correctness, and prohibition of negative or baseline-restating ADRs. Contains gate definitions and scoring rubric for the solution-architect-reviewer lenses.
Use whenever an agent must run a toolchain command (build, test, mutation) and needs the concrete invocation. Resolves build/test/mutation commands from the detected stack so no agent hardcodes `dotnet test`, `dotnet build`, or any toolchain command. Loaded by acceptance-designer and software-engineer.
Use this skill BEFORE drafting any agentic primitive module (skill, persona scoping file, scope-attached rule file, orchestrator workflow) or when refactoring an existing one. Activate whenever the task asks to design, restructure, or critique an agentic module across any agent harness (Claude Code, Copilot, Cursor, OpenCode, Codex). This skill drives an 8-step disciplined design process whose output is mermaid diagrams + an interface sketch + a persisted plan that the calling thread (or a coder persona it loads) then turns into natural-language modules. Do not skip to natural-language drafting before the design artifacts exist.
Use when documenting architecture decisions as ADRs, evaluating trade-offs between alternatives, or managing the lifecycle of existing decisions. Covers ADR template, status transitions, consequence analysis, and quality criteria.
Use when designing test coverage matrices, assigning tests to Clean Architecture layers, planning the outside-in implementation order, or applying the Walking Skeleton strategy. Ensures every behaviour is tested at the right level with no redundancy. Load after writing Gherkin scenarios.
Use when reviewing DISCOVER artefacts (triage reports, sprint proposals) for completeness, prioritization quality, and duplicate handling. Contains gate definitions G1-G6 and scoring rubric for the backlog-discoverer-reviewer lenses.
Use when reviewing DISTILL artefacts (Gherkin scenarios, test plans, implementation plans) for quality, completeness, and alignment. Contains the gate definitions and scoring rubric for the acceptance-designer-reviewer lenses.
Use when writing, reviewing, or structuring BDD scenarios in Gherkin format. Covers Given/When/Then conventions, scenario outline patterns, background usage, tag strategies, and domain language alignment. Load before any Gherkin authoring.
Use when deciding what to test at each Clean Architecture layer (Domain, Application, Infrastructure, API, Architecture), selecting test doubles per boundary, or enforcing layer boundaries through architecture tests. Language-agnostic principles with .NET, Java, Python, TypeScript examples.
Use when authoring OpenAPI/AsyncAPI contracts, generating Microcks samples, setting up Testcontainers mocks, verifying provider contracts, or bridging API contracts across DESIGN → DISTILL → DELIVER phases.
Use when completing a TDD phase or before committing — self-discipline checkpoints the software-engineer runs against their own output. Not a review contract. The reviewer verifies artifacts independently.
Use when transforming raw issues or feature requests into well-structured user stories with acceptance criteria. Covers user story format, INVEST criteria, acceptance criteria patterns, story splitting techniques, DoR 8-item gate, and 8 antipatterns to detect.
Use when writing tests from the outside-in, defining behavior before code, or any feature where tests should start from observable business behavior and let internal design emerge. Covers double-loop TDD, 4-phase cycle, boundary-to-boundary testing, iron rule of tests, walking skeleton, and post-GREEN wiring verification.
Use when capturing E2E test evidence (screenshots, videos, traces), uploading evidence to GitHub issue comments, or configuring Playwright in CI pipelines for the DELIVER phase and orchestrator feedback loop.
Install the full eleven-workflow skraft SDLC pipeline (discover → discuss → design → distill → deliver, each with an automated reviewer) into the current repo in one pass. Use when the user wants an end-to-end agent pipeline driven by a single issue label, or types /install-skraft-pipeline.
iOS 26 Liquid Glass design system — dynamic glass material with blur, reflection, and interactive morphing for SwiftUI, UIKit, and WidgetKit.
Use when writing or improving Gherkin .feature files, after business rules and examples have been discovered
Use before writing any Gherkin scenario, when business rules need to be explored and edge cases discovered through collaborative example mapping
Autonomously optimize any Github Copilot skill by running it repeatedly, scoring outputs against binary evals, mutating the prompt, and keeping improvements. Based on Karpathy's autoresearch methodology. Use when: optimize this skill, improve this skill, run autoresearch on, make this skill better, self-improve skill, benchmark skill, eval my skill, run evals on. Outputs: an improved SKILL.md, a results log, and a changelog of every mutation tried.
Use when implementing any feature or fix using TDD, before writing any implementation code