external/antfu-skills/pinia/SKILL.md
Pinia official Vue state management library, type-safe and extensible. Use when defining stores, working with state/getters/actions, or implementing store patterns in Vue apps.
npx skillsauth add seikaikyo/dash-skills piniaInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Pinia is the official state management library for Vue, designed to be intuitive and type-safe. It supports both Options API and Composition API styles, with first-class TypeScript support and devtools integration.
The skill is based on Pinia v3.0.4, generated at 2026-01-28.
| Topic | Description | Reference | |-------|-------------|-----------| | Stores | Defining stores, state, getters, actions, storeToRefs, subscriptions | core-stores |
| Topic | Description | Reference | |-------|-------------|-----------| | Plugins | Extend stores with custom properties, state, and behavior | features-plugins |
| Topic | Description | Reference | |-------|-------------|-----------| | Composables | Using Vue composables within stores (VueUse, etc.) | features-composables | | Composing Stores | Store-to-store communication, avoiding circular dependencies | features-composing-stores |
| Topic | Description | Reference | |-------|-------------|-----------| | Testing | Unit testing with @pinia/testing, mocking, stubbing | best-practices-testing | | Outside Components | Using stores in navigation guards, plugins, middlewares | best-practices-outside-component |
| Topic | Description | Reference | |-------|-------------|-----------| | SSR | Server-side rendering, state hydration | advanced-ssr | | Nuxt | Nuxt integration, auto-imports, SSR best practices | advanced-nuxt | | HMR | Hot module replacement for development | advanced-hmr |
storeToRefs() when destructuring state/getters to preserve reactivity@pinia/testing for component tests with mocked storestools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.