Socratic spec refinement — clarify WHAT a phase delivers with ambiguity scoring before discuss-phase. Produces a SPEC.md with falsifiable requirements locked before implementation decisions begin.
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。
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概要と使いどころ
Socratic spec refinement — clarify WHAT a phase delivers with ambiguity scoring before discuss-phase. Produces a SPEC.md with falsifiable requirements locked before implementation decisions begin.
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。
Extract decisions, lessons, patterns, and surprises from completed phase artifacts
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。
Ingest external plans with conflict detection against project decisions before writing anything.
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 ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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。
Convert a vague mini-program idea, feature request, or partially documented product into an evidence-calibrated product specification with target users, core problem, version-one scope, main and exception flows, page responsibilities, state matrices, and testable acceptance criteria. Use when users ask to define an MVP, clarify requirements, organize product flows, specify page behavior, resolve ambiguous product states, or prepare a stable handoff before architecture or implementation. Separates facts, user decisions, assumptions, unknowns, and future ideas; never invents product logic merely to complete a screen or technical plan.
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。
Translate a confirmed mini-program product specification or bounded feature into an implementable architecture covering modules, pages, components, services, canonical state sources, data models, interfaces, permissions, failures, caching, concurrency, idempotency, migration, rollback, external dependencies, and architecture decision records. Use when users ask how to structure a mini program, design data or APIs, divide frontend and cloud responsibilities, evolve an existing system safely, or prepare implementation after product semantics are stable. Preserves product meaning, current repository constraints, user-owned changes, and verifiable acceptance behavior rather than redesigning the product for technical convenience.
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。
Interpret learning analytics data and translate dashboard findings into actionable teaching decisions. Use when reviewing LMS data, quiz patterns, or engagement metrics.
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。
When the user wants help with revenue operations, lead lifecycle management, or marketing-to-sales handoff processes. Also use when the user mentions 'RevOps,' 'revenue operations,' 'lead scoring,' 'lead routing,' 'MQL,' 'SQL,' 'pipeline stages,' 'deal desk,' 'CRM automation,' 'marketing-to-sales handoff,' 'data hygiene,' 'leads aren't getting to sales,' 'pipeline management,' 'lead qualification,' or 'when should marketing hand off to sales.' Use this for anything involving the systems and processes that connect marketing to revenue. For cold outreach emails, see cold-email. For email drip campaigns, see emails. For pricing decisions, see pricing.
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。
When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," "in-app pricing," "free users won't upgrade," "trial to paid conversion," or "how do I get users to pay." Use this for any in-product moment where you're asking users to upgrade. Distinct from public pricing pages (see cro) — this focuses on in-product upgrade moments where the user has already experienced value. For pricing decisions, see pricing.
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。
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' or 'should I offer a free plan.' Use this whenever someone is figuring out what to charge or how to structure their plans. For in-app upgrade screens, see paywalls.
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。
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
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。
Grounds every implementation decision in official documentation. Use when you want to verify an approach against the official docs before implementing it, or when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.
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 a finished epic folder in the ticket tree against the evidence it left behind — the epic file, each ticket plan, diffs, commits — and produce a retrospective with sourced findings, action items, and an acceptance decision. Use when the user says "run a retrospective" or "lets retro the epic [epic]". Supports -H/--headless
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。
Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"
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。
Work out and record the architecture decisions that keep separately built parts of a system consistent, in a short architecture document. Creates, updates, or validates one; works from a spec, a raw idea, or an existing codebase. Use when the user says "create the architecture", "create technical architecture", "architecture spine", or "create a solution 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。
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill 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。
Audit the decisions in .ank/ against the current code and report what no longer holds. Use when asked whether ADRs, specs, or tasks are still accurate, after a milestone, or when the corpus and the code seem to disagree.
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。
Interview a goal into decisions and tasks recorded in .ank/. Use when someone brings a feature, change, or problem to plan before implementation in a repository with a .ank/ directory.
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。
Create distinctive, production-grade frontend interfaces with high design quality using Mobile First strategy. Analyzes design systems from screenshots, generates Tailwind CSS + Shadcn UI configurations, and retrofits existing projects. Optimized for Claude Opus 4.5 with structured decision trees and self-verification checkpoints.
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。
Active Directory attack reference — BloodHound Cypher queries, Kerberos attack decision tree, ACE/ACL abuse, ADCS ESC1-8, and AD misconfig checklist
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。
Convert run artifacts into calibrated interpretation and next decisions.
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。
Step-by-step complex reasoning for multi-variable problems. Breaks interconnected decisions into ordered logical steps with bias detection, reversibility classification, and second-order effect tracking.
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。
Meta-enforcement layer that routes EVERY agent action through the correct skill. MUST check this routing table before ANY response involving code, files, or technical decisions. Default: route to rune:cook for code tasks. Prevents rationalization, enforces check-before-act discipline.
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。