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概要と使いどころ
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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 Phase 1c (spec review gate) for the active VCSDD feature. Spawns a fresh vcsdd-adversary instance to review the behavioral spec and verification architecture. Records PASS/FAIL gate verdict.
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。
Use this skill when writing Phase 1a behavioral specifications in VCSDD. Provides EARS format requirements writing, purity boundary analysis, edge case enumeration, and spec quality validation patterns.
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 Phase 1a (behavioral specification) and Phase 1b (verification architecture) for the active VCSDD feature. Invokes vcsdd-builder to write EARS-format requirements and purity boundary analysis.
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。
Use when a feature or code change made by Claude is complete and the developer wants to confirm they actually understood it before shipping. Triggers on "handoff", "quiz me", "comprehension check", "did I understand this", "verify I read the code", "test my understanding", or after finishing a feature when the developer wants to take ownership of AI-written code. Also triggers on requests for an interactive or clickable quiz ("interactive mode", "let me answer with the mouse", "mode interactif", "je réponds à la souris"). Quizzes the developer on WHERE the logic lives (file/function) and WHY decisions were made (trade-offs, behavior, debugging), with the number of questions scaled to the size of the change. Multiple-choice questions are clickable by default (asked through `AskUserQuestion`) and fall back to typed answers. Points to file:line on wrong answers, allows one retry, then reveals the answer, and ends with a score plus the weak areas to re-read. Conducts the quiz in the developer's language.
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。
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
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。
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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。
Use when implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent behavior.
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。
Initialize or improve AGENTS.md files that define how coding agents operate in a repo. Use when asked to set up or replace an agent init command (Codex, Claude), standardize multi-agent behavior, or audit an existing AGENTS.md for clarity, commands, boundaries, and repo-specific context. For Claude Code, also create CLAUDE.md as a symlink to AGENTS.md.
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。
Investigate and fix bugs, failing tests, regressions, build failures, or unexpected behavior using boundary localization, evidence, and bounded hypotheses.
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 risk-based test-driven development to bugs, domain logic, state transitions, parsers, contracts, migrations, and behavior where a failing test sharpens the design.
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。
Analyze historical VS Code GitHub Copilot Chat sessions by model, reasoning effort, AIU, time, reliability, workflow behavior, and external quality evidence, or safely prune workspace-scoped local chat history by age. Use for session analysis, repeated-task retrospectives, model evaluation, cost/performance analysis, and old session cleanup.
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。
Use when asked to debug, fix a bug, investigate an error, or do root cause analysis, and when users report errors, stack traces, unexpected behavior, or say something stopped working.
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 Social Identity Theory to analyze how group categorization, identification, and intergroup comparison drive behavior, bias, and conflict. Use this skill when the user needs to explain in-group favoritism or out-group hostility, diagnose organizational silo dynamics, design inclusive team structures, or when they ask 'why do groups polarize', 'how does team identity affect collaboration', or 'what drives us-vs-them thinking'.".
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 Bhaskar's critical realism to analyze phenomena through three ontological domains (real, actual, empirical), identify generative causal mechanisms via retroduction, and examine structure-agency interplay. Use this skill when the user needs to go beyond surface correlations to underlying causes, design research that distinguishes mechanisms from events from experiences, or when they ask 'what causes this beyond the observed pattern', 'what structures enable or constrain this behavior', or 'how do I move from correlation to causal explanation'.".
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 public choice theory to analyze political decision-making as rational self-interested behavior. Use this skill when the user needs to evaluate government policy failures, rent-seeking costs, voting outcomes, or bureaucratic incentives, especially when the assumption of benevolent government is questionable.".
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 Granovetter's embeddedness theory to analyze how economic behavior is embedded in ongoing social relations, avoiding both over-socialized and under-socialized accounts. Use this skill when the user needs to explain why market transactions deviate from pure economic rationality, analyze how trust and social ties shape business dealings, evaluate structural vs relational embeddedness in inter-firm networks, or when they ask 'why do firms prefer existing partners over cheaper alternatives', 'how do social relationships shape economic outcomes', or 'is this market truly arms-length'.".
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 basic game theory concepts including Nash equilibrium, dominant strategies, and the Prisoner's Dilemma to analyze strategic interactions. Use this skill when the user needs to model competitive decisions, predict rival behavior, design incentive mechanisms, or evaluate cooperation vs competition scenarios — even if they say 'what will our competitor do', 'should we cooperate or compete', or 'how do we set up the right incentives'.".
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。
"Perform RFM (Recency, Frequency, Monetary) customer segmentation from transaction data. Use this skill when the user needs to segment customers by purchase behavior, identify high-value buyers, design retention campaigns, or prioritize marketing spend by customer value — even if they say 'who are our best customers', 'which customers are at risk of churning', or 'how do we target our marketing'.".
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。
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output. Use when a task requires complete code or exhaustive unabridged output without placeholders.
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 Consumer Culture Theory to analyze consumption as a cultural practice shaped by identity, marketplace cultures, and ideology. Use this skill when the user needs to interpret consumer behavior through cultural lenses, analyze brand communities or subcultures of consumption, decode marketplace ideologies, or when they ask 'why do consumers behave this way culturally', 'what does this consumption mean', or 'how does identity shape buying'.".
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。
Simplify working code while preserving behavior—remove dead paths, flatten nesting, clarify names, reduce duplication. Use after features work but code feels over-engineered.
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。
Structured debugging session — reproduce, isolate, diagnose, and fix. Trigger with an error message or stack trace, "this works in staging but not prod", "something broke after the deploy", or when behavior diverges from expected and the cause isn't obvious.
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 session-based recommendation from short-term user behavior sequences without long-term profiles. Use this skill when the user needs to recommend in anonymous sessions, predict next click from browsing sequence, or build recommendations for non-logged-in users — even if they say 'what should they click next', 'anonymous user recommendations', or 'browsing sequence prediction'.".
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。