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概要と使いどころ
Run the evidence loop of one long-horizon GPU kernel optimization episode. Use this skill to reconstruct the incumbent, profile and localize a bottleneck, research progressively, plan one coherent direction, implement and repair, validate development correctness and performance, and record every decisive experiment in the episode journal.
日本語の概要は準備中です。原文の説明を表示しています。
Explain system behavior, request flows, architecture, or implementation logic as short 4chan-style greentext lines. Use when the user asks for a step-by-step explanation, says "explain the logic", asks for "greentext", or wants terse sequential reasoning with each line starting with `>`.
日本語の概要は準備中です。原文の説明を表示しています。
Seed a fresh (greenfield) repository with the PRD-Driven Context Engineering scaffold — PRD.md, SoT/ knowledge files, EPIC templates, domain-profile config, and agent MEMORY starters. Invoked as /prd-ce:init when the plugin is installed. The framework itself (skills, agents, hooks, scripts) ships LIVE in the plugin; this skill only plants the consumer-owned files the plugin cannot carry as behavior. Triggers on "/prd-ce:init", "set up PRD lifecycle here", "scaffold a new PRD-CE project", "initialize the methodology". Outputs a seeded scaffold + a verification report.
日本語の概要は準備中です。原文の説明を表示しています。
Build Tier 1/2/3 cold outreach sequences differentiated by personalization depth and research signal strength during PRD v0.9 Go-to-Market. Triggers on requests to plan cold outreach, founder-led sales, or when user asks "cold email sequence", "outbound campaign", "founder outreach", "LinkedIn outreach", "Tier 1 personalization", "predictable revenue", "sales cadence", "BDR sequence". Outputs GTM-OUT-* sequence entries and lead-list references.
日本語の概要は準備中です。原文の説明を表示しています。
Synthesize behavioral personas from prior stage evidence for journey mapping and marketing during PRD v0.4 User Journeys. Triggers on requests to define personas, create user profiles, identify target users, or when user asks "who are our users?", "define personas", "user profiles", "target users", "persona creation", "who uses this product?". Consumes CFD- (v0.1-v0.3), BR- (targeting from v0.3 Moat), FEA- (v0.3 Feature Value Planning). Outputs PER- entries with behavioral profiles and feature relationships. Feeds v0.4 User Journey Mapping.
日本語の概要は準備中です。原文の説明を表示しています。
Map user missions from trigger to value moment, organizing features into coherent paths during PRD v0.4 User Journeys. Triggers on requests to map user journeys, define user flows, describe how users accomplish goals, or when user asks "map user journeys", "define user flows", "user missions", "how do users accomplish X?", "journey mapping", "what steps do users take?", "pain to value flow". Consumes PER- (Persona Definition), FEA- (Feature Value Planning), KPI- (Outcome Definition). Outputs UJ- entries with step flows, pain points, and value moments. Feeds v0.4 Screen Flow Definition.
日本語の概要は準備中です。原文の説明を表示しています。
Define and prioritize features with strategic traceability during PRD v0.3 Commercial Model. Triggers on requests to define features, prioritize capabilities, scope MVP, map features to pricing tiers, identify parity vs. delta features, or when user asks "what features do we build?", "what's in MVP?", "which features matter?", "feature priority", "parity features", "what's our delta?". Consumes KPI- (Outcome Definition), BR- (Pricing Model, Moat), and CFD- (Market Moat Analysis) from v0.3. Outputs FEA- entries with strategic traceability and BR-FEA- governance rules. Feeds v0.4 User Journeys.
日本語の概要は準備中です。原文の説明を表示しています。
Run all TMDb unit tests (Swift Testing, the TMDb test plan). Use after code changes and before a PR to verify unit tests pass — delegates the run to the tooling-runner agent (Haiku) and returns total/passed/failed counts plus each failure as Suite/test with file:line. For the live-API suite, use /integration-test.
日本語の概要は準備中です。原文の説明を表示しています。
Review and assess every issue in the TMDb project board's Backlog column — re-verify each against current main with a read-only fan-out, close the mechanically dead, promote the actionable to Ready with priority, size and execution order, and leave the rest in Backlog naming the decision they need. Use to groom the backlog, before planning a release, or on a schedule. Runs headless: it decides for itself within the rules below.
日本語の概要は準備中です。原文の説明を表示しています。
Implement features and fix bugs test-first, the Canon TDD way (test list → one test → make it pass → refactor → repeat). Use when implementing any new feature, endpoint, model, or method, fixing a bug, or executing a plan — write the test list and a failing test BEFORE production code.
日本語の概要は準備中です。原文の説明を表示しています。
Run the TMDb integration tests against the live TMDb API (the Integration test plan; requires TMDB_API_KEY/USERNAME/PASSWORD). Use before a PR, or after model/fixture changes, to validate against real API responses — delegates to the tooling-runner agent (Haiku) and returns counts + failures, distinguishing genuine failures from transient live-API/env issues. For mocked unit tests, use /test.
日本語の概要は準備中です。原文の説明を表示しています。
Explain a body of work plainly so a person actually understands it. Runs the `how` and `why` skills and weaves what they find into one clear explanation. Use for 'teach me this', 'help me really understand X', 'explain this change or subsystem to me'.
日本語の概要は準備中です。原文の説明を表示しています。
Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.
日本語の概要は準備中です。原文の説明を表示しています。
Non-animation creative direction for HyperFrames videos. Use for design spec (frame.md / design.md) handling, palettes, typography, beat planning, composition patterns, and brand / style decisions. For atomic motion patterns and scene blueprints, use `hyperframes-motion`.
日本語の概要は準備中です。原文の説明を表示しています。
Apply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.
日本語の概要は準備中です。原文の説明を表示しています。
DyNote: systematically and efficiently extract raw Douyin/DY video data and analyze videos, comments, accounts, hashtags, and short-video scenes into evidence-graded learning notes, summaries, research briefs, scripts, and knowledge-base material. Use when the user asks to 抓取/提取/整理 抖音视频字幕、视频文案、ASR 转写、Qwen3-ASR 中文转写、原始材料归档、学习笔记、analysis plan、note budget、避免返工、复用已有素材、评论洞察、账号分析、赛道/话题研究、竞品拆解、电商/本地生活视频分析、事实核查、自动搜索素材, save Douyin content as Markdown/TXT, or use subtitle/local ASR as the factual spine with logged-in Douyin Web built-in AI / Doubao fallback as visual or quick-reading supplements.
日本語の概要は準備中です。原文の説明を表示しています。
Hoyeon Socratic discussion workflow for Codex. Use when the user invokes "$hoyeon-discuss", "/discuss", asks to think through an idea, challenge assumptions, clarify requirements before planning, run a deep/scored discussion, or says Korean phrases like "같이 생각해보자", "문제 정의", "이거 어떻게 생각해?", "요구사항이 불명확", or "아이디어 구체화".
日本語の概要は準備中です。原文の説明を表示しています。
Hoyeon ambiguity-resolution interview for Codex. Use when the user invokes "$hoyeon-clarify", "/clarify", asks to keep asking until clear, remove ambiguity, clarify requirements/design/domain/plan, or says Korean phrases like "모호한 게 없게", "명확해질 때까지", "질문 계속해", or "Q&A로 정리".
日本語の概要は準備中です。原文の説明を表示しています。
"/clarify", "clarify this", "keep asking until clear", "remove ambiguity", "clarify requirements", "clarify design", "clarify the plan", "질문 계속해", "모호한 게 없게", "명확해질 때까지", "계속 물어봐", "Q&A로 정리", "질문답변 기록", "요구사항 명확화", "설계 명확화". Relentless ambiguity-resolution interview that records Q&A under .hoyeon/clarify/<topic>/ and hands off to specify/blueprint/docs when clear.
日本語の概要は準備中です。原文の説明を表示しています。
Hoyeon blueprint workflow for Codex. Use when the user invokes "$hoyeon-blueprint" or wants to turn requirements.md into a validated plan.json and optional contracts.md. This adapter loads the canonical blueprint skill and follows its Codex runtime surface.
日本語の概要は準備中です。原文の説明を表示しています。
Greenfield project architecture + harness scaffolding for AI Agent productivity. Interview-driven decisions → requirements.md → execute. Produces: Code Structure (vertical slice exemplar), Test Infrastructure, Guard Rails, conditional extensions, AND Harness (CLAUDE.md with domain/team context, rules, skills, hooks). L2: architecture decisions, L3: harness setup, L4: requirements + harness decisions (tasks generated later by /execute into plan.json). Use when: "/scaffold", "scaffold", "new project", "set up project", "프로젝트 세팅", "초기 구조"
日本語の概要は準備中です。原文の説明を表示しています。
Hoyeon execution workflow for Codex. Use when the user invokes "$hoyeon-execute" or wants to execute a Hoyeon plan.json through the Bash-first Codex adapter. This adapter loads the canonical execute skill and follows its Codex runtime surface.
日本語の概要は準備中です。原文の説明を表示しています。
Unified multi-platform paid media audit with parallel execution. Spawns scored audits for Google Ads, Meta Ads, and Microsoft Ads simultaneously, merges results into a budget-weighted aggregate health score (A-F), adds cross-platform analysis (budget allocation, tracking consistency, creative alignment, attribution overlap), and produces a prioritized action plan. Optionally generates a client-ready deck via pro-deck-builder. Use when the user asks for a full paid media audit, cross-platform review, or multi-channel ad assessment.
日本語の概要は準備中です。原文の説明を表示しています。
Google and Meta paid media account structure evaluation. Audits campaign/ad set architecture against conversion volume minimums, budget thresholds, and targeting overlap. Identifies over-segmentation, under-segmentation, budget fragmentation, and structural anti-patterns blocking algorithmic learning. Provides consolidation roadmaps with migration plans. Use when inheriting accounts, quarterly health checks, or before scaling budgets.
日本語の概要は準備中です。原文の説明を表示しています。