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Conducts Privacy Impact Assessment for health data processing under GDPR Article 9, HIPAA, and sector-specific health privacy regulations. Covers special category data safeguards, clinical research data, patient portals, health wearables, genetic data, and cross-border health data transfers. Keywords: health data PIA, DPIA, Article 9, HIPAA, special category data, clinical research, patient privacy, genetic data.

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Guides implementation of EU Standard Contractual Clauses under Commission Decision 2021/914 across all four modules (C2C, C2P, P2P, P2C). Covers clause-by-clause completion, Annex I-III drafting, and SCC module selection. Keywords: SCCs, standard contractual clauses, module selection, data transfers, Annex completion.

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Classifies personal vs non-personal data per GDPR Art. 4(1) definition test with decision tree for borderline cases. References Breyer v Germany CJEU C-582/14 dynamic IP ruling and WP29 Opinion 4/2007. Keywords: personal data, GDPR Art 4, data classification, Breyer ruling, identifiability test, PII.

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Guides systematic mapping of international personal data flows across an organisation. Covers system-by-system inventory methodology, third-party identification, transfer mechanism assignment, gap analysis, and data flow visualisation. Keywords: data flow mapping, international transfers, data inventory, transfer register, cross-border data flows.

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Use when implementing Kafka, RabbitMQ, Pulsar, or JMS producers and consumers in Spring Boot 3. Covers event contracts, idempotency, retries, dead-letter handling, ordering, and outbox delivery.

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Use when working in a multi-module Maven project. Covers parent POM conventions, shared dependency management, inter-module rules, build ordering, and Spring Boot 4 modular starter selection.

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Use when working in a multi-module Maven project. Covers parent POM conventions, shared dependency management, inter-module rules, and build ordering.

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。

This skill should be used when the user asks to "write a query letter", "query", "querying", "pitch", "blurb", "back cover copy", "jacket copy", "comp titles", "comparable titles", "synopsis for agents", "submit to agents", "submission tracker", "self-publishing description", "retailer description", "ready to query", "submission readiness check", "submit a short story", "magazine submission", "short-fiction markets", "simultaneous submission", "reprint rights", "order a short story collection", or wants to prepare and track a finished manuscript's submission to agents, publishers, magazines, anthologies, or retailers. NOT for pitching a series of several books (use series-continuity), or self-publishing production, metadata, or book rights deals (use publishing). The blurb, retailer description, and the rights a short-fiction market buys, such as reprint rights, stay here.

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Converges an underspecified request into a typed IntentSpec before planning or acting. Use when the user asks to implement, add, change, refactor, fix, migrate, configure, handle, triage, sort out, look into or decide something and the request leaves decisions open (which objects, which approach, what happens on failure, which trade-off), contradicts itself, admits two readings, or rests on an approach its sources may rule out — in a codebase, a ticket queue, a research brief or a runbook — or when the user says "clarify the intent", "what do you need from me", or invokes intent-router. Looks up what its sources hold (code, history, decision records, a ticket log, an order record, the policy in force) before asking; asks only preference or irreversible questions, one at a time, with a recommended default; halts instead of guessing; checks the delivered work against the spec. Silent on a fully stated task its sources do not contradict. Not for explaining existing state ("what does X do", "why is Y slow").

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Write code through a disciplined, BDD-framed Test-Driven Development loop: build a behavior test list, then drive each behavior through red-green-refactor with an enforced observed-failure gate. Use when the user wants to implement, build, or write code test-first, "do TDD", follow "red-green-refactor", drive code from tests, choose the next test by the Transformation Priority Premise (TPP) or ZOMBIES ordering, or grow a feature behavior-by-behavior with tests leading. This skill writes and changes code; it does not produce a test plan document (use automated-test-planning, or manual-test-planning for a plan a person runs by hand), review or audit existing code (use code-review), restructure existing code outside a TDD loop (use refactor, or plan-a-change to plan a multi-module restructure), specify what a feature should do (use plan-a-feature), or find the root cause of a bug (use investigate). Runs its loop to completion without pausing for review; to review each behavior as it lands, use pairing.

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Splits a body of context into a sequence of vertical-slice build phases where each phase is independently demonstrable to a real user and each builds on the previous. Use when the user wants to plan, sequence, phase, slice, break down, or order the build of a feature, capability, system, or initiative, and produces a plain-language phased build outline. Does not produce implementation detail — use plan-implementation. Does not specify behavior that has not been decided — use plan-a-feature. Does not perform gap analysis between two artifacts — use gap-analysis. Does not break a plan into independently-grabbable work items — use plan-work-items.

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Write model-native Seedance 2.0 video prompts from text, images, video, or audio references. Use for text/image generation, multimodal reference, video editing, extension, track fill, or combined tasks that need stable subjects, explicit asset roles, coherent event order, camera, sound, visible text, and a 4–15 second feasibility check.

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Create original short videos using the 地面召集天空编队｜近距确认、首领降落与乘骑离场 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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Create original short videos using the 毛坯房顺序完工｜表面施工、木作、家具与照明验收 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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Create original short videos using the 固定人台逐层着装｜衣物投送、层级闭合与触感验收 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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Build DSPy 3.2.x programs through spec, program, metric and baseline; extend to optimization and export when requested and justified by task budget. Orchestrates the other four DSPy skills (dspy-fundamentals, dspy-evaluation-harness, dspy-gepa-optimizer, dspy-rlm-module) in the correct order. Use for greenfield DSPy builds; prototypes may stop at a validated baseline.

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BigCommerce integration. Manage Products, Customers, Orders, Carts, Coupons, GiftCertificates and more. Use when the user wants to interact with BigCommerce data.

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BaseLinker integration. Manage Products, Orders, Shops, Users. Use when the user wants to interact with BaseLinker data.

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Fix duplicate Nostr events in ClickHouse when using ReplacingMergeTree for NIP-33 addressable events (Kind 30000+). Use when: (1) Edited videos/events appear as duplicates, (2) Same d_tag shows multiple events with different IDs, (3) FINAL keyword doesn't deduplicate properly for parameterized replaceable events. The issue is that FINAL deduplicates by ORDER BY key (typically `id`), not by (pubkey, kind, d_tag).

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Use when implementing allow users to reorder items intuitively.

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Create narrow iMessage/PTT Border-Light HyperCard style nine-grid cards in Chinese or mixed Chinese-English. Use when the user says "iMessage 九宮 HyperCard", "iMessage 九宮", "做成 iMessage 九宮", "用 iMessage 九宮 HyperCard 整理", asks for a phone-readable short card with Context below, or wants Mandala/九宮/HyperCard content formatted for blue-bubble/iMessage sharing with long links, paths, and rules moved out of the card.

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Analyzes test suites and suggests optimal test execution order based on code change impact and project requirements. Use when optimizing CI/CD pipelines, deciding which tests to run before committing, or selecting critical tests under time constraints. Prioritizes tests by analyzing recently modified files, test dependencies, and coverage overlap. Outputs detailed rankings with priority scores and reasoning to help teams run the most impactful tests first.

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Automatically infer formal correctness properties from Verilog/SystemVerilog RTL code and generate SystemVerilog Assertions (SVA). Identifies control-flow invariants (mutual exclusion, valid-ready handshakes, pipeline ordering, safety properties), liveness expectations, and temporal properties. Use when working with RTL designs that need formal property generation, when adding assertions to existing RTL, or when users ask to infer properties, generate assertions, or create formal specifications from hardware designs.

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Extract abstract mathematical models from functional code (Haskell, OCaml, F#) for formal reasoning in Isabelle/HOL. Use when users need to: (1) Convert functional programs to Isabelle definitions, (2) Extract high-level algorithm essence from implementation code, (3) Generate formal specifications and properties from code, (4) Create verification-ready models that capture mathematical properties while abstracting away implementation details. Focuses on structural recursion, algebraic data types, higher-order functions, and invariant extraction.

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。