「compose」の検索結果

Decompose a game concept into individual systems, map dependencies, prioritize design order, and create the systems index.

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Provisioning infrastructure via cloud IaC (Terraform/OpenTofu/CloudFormation/Pulumi) and local dev environments (Docker Compose, env vars). Use for IaC design or multi-cloud provisioning.

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Implementing production iOS/Android/macOS native features (SwiftUI, Compose) and iterating a screen against a reference design. Not for cross-platform RN/Flutter (Port) or web (Artisan).

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Tags harness-decomposed curriculum items (KUDs, LTs, criteria) with a school's developmental band metadata while preserving source voice and labels. Supply the band schema; the skill derives mapping rules from it.

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Manage Docker containers, images, volumes, networks, and Compose stacks — lifecycle ops, debugging, cleanup, and Dockerfile optimization.

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管理 Docker 容器、镜像、卷、网络和 Compose 栈——生命周期操作、调试、清理和 Dockerfile 优化。

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Use when you have a finalized brainstorm-beagle spec at `.beagle/concepts/<slug>/spec.md` and need a bite-sized, TDD-driven implementation plan before any code is written. Triggers on: "write a plan", "plan this spec", "turn the spec into a plan", "now plan the implementation", "write-plan". Reads the spec, designs the file structure, decomposes work into 2-5 minute TDD steps with exact paths and commands, self-reviews against the spec, gets user approval, then writes to `.beagle/concepts/<slug>/plan.md` and offers to generate an execution handoff prompt via the subagent-prompt skill. Does NOT brainstorm specs, write code, or execute the plan — produces the plan document (and an optional handoff prompt) only.

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Kotlin/Compose/Hilt/coroutine test code patterns: fakes, MainDispatcherRule, Turbine, Roborazzi, golden-contract calls. Use when writing or fixing Kotlin test code. Not for the TDD workflow (use tdd).

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Use this skill to generate well-branded interfaces and assets for RIPDPI (an Android-native, Compose-first VPN and DPI-bypass app), either for production or throwaway prototypes/mocks/etc. Contains essential design guidelines, colors, type, fonts, brand-ship icons, and an interactive UI kit of every public composable from the live ui/components tree.

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RIPDPI's edge-to-edge and window-inset rules for Compose screens, scaffolds, sheets, and the single enableEdgeToEdge() call site. Use for insets, system bars, or edge-to-edge layout here.

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Decompose and explain healthcare cost growth into contributing factors including utilization changes, unit price shifts, case mix evolution, and population changes. Use when analyzing PMPM cost trends, explaining cost variance to leadership, preparing actuarial summaries, or identifying cost reduction opportunities.

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Musical form and structural analysis covering binary, ternary, rondo, sonata, theme-and-variations, and popular song forms. Covers formal archetypes (AB, ABA, ABACA, sonata-allegro), 12-bar blues, arch form, minimalist process forms, strophic and through-composed designs, and formal analysis methodology for both score study and listening. Use when determining the structural plan of a piece, analyzing sectional relationships, or understanding how form shapes musical narrative.

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Computational thinking as a problem-solving discipline independent of programming languages. Covers the four pillars (decomposition, pattern recognition, abstraction, algorithm design), computational problem-solving methodology (understand, decompose, generalize, formalize, verify), abstraction levels (from hardware through user interface), modeling and simulation, automata and formal languages (DFA, NFA, regular expressions, context-free grammars, Turing machines), computational complexity classes (P, NP, NP-complete, undecidable), and constructionist pedagogy (learning by building, Logo, Scratch, physical computing). Use when approaching unfamiliar problems, teaching problem-solving strategies, analyzing problem complexity, or bridging between domain knowledge and computational solutions.

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Use when you have captured session evidence — session-retro / session- observatory-live traces in .planning/patterns/, tool logs, correction records — and want to induce a reusable skill from it. Segments the traces into candidate skill units (an LLM judgment, not a deterministic parse) and decomposes each candidate into a four-part structured spec: workflow structure, execution semantics, and runtime attachments (verification, safety, rollback, state). It emits a spec object, NOT a finished SKILL.md, and hands that spec to skill-forge. It sits between skill-integration (upstream frequency detector) and skill-forge (downstream author). Backed by Agent-Trace-to-Skill Induction (arxiv 2606.06893v1). Triggers on inducing a skill from captured traces, turning a repeated pattern into a skill spec, and preparing evidence for skill-forge.

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Transform a user's builder vision into a complete, executable GSD mission package. Use this skill whenever a user has described what they want to BUILD (a product, tool, feature, system, educational pack, or ecosystem component) and wants it structured for GSD execution. Triggers include: 'structure this for GSD', 'make this into a milestone', 'turn this vision into a mission', 'package this up for Claude Code', 'create the mission files', 'I want to hand this to GSD', 'make me a mission package', or any request to decompose a described system into wave-based executable tasks. Also trigger when the user has a vision doc already written and needs mission decomposition. Prefer this skill over generic document creation whenever the GSD ecosystem is mentioned alongside building something.

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Composes three-part DACP bundles from skill library artifacts. Determines fidelity level, queries catalog, and records assembly rationale.

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Decomposes a contextualized plan into atomic, independently executable tasks with complete embedded context, registered through the plan API. Use after SAM Stage 3 Context Integration produces the contextualized plan artifact — when the plan is ready for task generation with CLEAR ordering, CoVe checks, and dependency graphs for parallel execution.

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Reviews browser-rendered HTML, CSS, JSX, TSX, JavaScript, and TypeScript for accessibility, XSS, forms, focus, rendering performance, styles, and lifecycle cleanup. Loaded by dh:code-reviewer when source or framework entrypoints establish frontend execution; composes with TypeScript checks.

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Decompose substantive work into phases, dispatch each phase to a sub-agent, and adjudicate what comes back. Use whenever a request asks for implementation, investigation, a fix, a review, or any change to files — including small ones — and whenever you are about to read source or run a diagnostic yourself instead of handing it off. Also use when a report from a sub-agent needs judging, when a phase needs re-dispatching, or when a user names one instance of a pattern. Does not apply when your own prompt begins "Your ROLE_TYPE is sub-agent." — then follow references/sub-agent-contract.md instead.

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Opt-in recreation of the Bun + TypeScript framework used to build Vapi's landing-page voice agents from a ROUGH_DRAFT.md spec, including a scenario registry, language stacks, prompt composer, assistant builder, and idempotent bootstrap script. Use only when the user explicitly invokes vapi-bootstrap-framework or specifically asks to reproduce or experiment with the landing-page-agent architecture. Do not use for ordinary Vapi assistant builds; use create-assistant, create-tool, create-squad, and vapi-prompt-builder instead. Targets Bun + TypeScript + @vapi-ai/server-sdk.

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Docker and Docker Compose patterns for local development, container security, networking, volume strategies, and multi-service orchestration.

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Decompose a task into safe parallel sub-agent slices with explicit ownership, optional worktree isolation, per-worker plans, verification, and orchestrator-led integration. Use when the user explicitly asks for delegation, sub-agents, or parallel work and the task can be split into non-overlapping scopes.

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Run a high-thoroughness end-to-end implementation loop using clean worker worktrees, per-slice planning, implementation, explicit review/fix iteration, orchestrator integration, and final commit/PR drafting. Use when the user explicitly wants a Ralph/Wiggum-style loop, autonomous multi-agent execution, a delegated feature/bugfix carried from confirmed scope through review-ready completion, or RFC-driven implementation that should be reviewed, bumped to In Progress, decomposed into phases, and executed through nested sub-loops. Supports Codex subagents by default and external CLI workers such as OpenCode when explicitly requested and available.

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Develop AuthCrunch plugins in separate repositories, maintain category reference plugins under plugins/, and compose companion host plugins. Covers repository bootstrapping, shared and local guidance, category contracts, existing APIs, and integration gaps; secrets providers have a specialized workflow.

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