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When the user wants to create Pinterest Pins, optimize Pin descriptions, or grow Pinterest presence. Also use when the user mentions "Pinterest," "Pin," "Pinterest SEO," "Pinterest description," "Pinterest board," or "Pinterest marketing." For asset specs, use visual-content.
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Remove repeated NuGet restores from multi-step .NET builds safely. USE FOR: build/test/publish steps that each restore, Directory.Build.rsp with -restore, safe restore suppression, NETSDK1004/NETSDK1047 after --no-restore. DO NOT USE FOR: slow first restore, only one restore, version or lock errors, unranked build slowness (use build-perf-baseline).
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Assess REST, GraphQL, and gRPC APIs for authentication, access control, input validation, and business logic weaknesses. Use OWASP API Security Top 10, a framework of common API risks, to organize testing and document findings with reproduction steps and remediation.
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Expose REST APIs as tools for AI agents through Google Cloud API Gateway using MCP, a protocol for connecting agents to tools. Covers OpenAPI migration, authentication, client connections, validation, and troubleshooting.
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Configure Backup for GKE to protect Kubernetes configurations and persistent data. Set backup schedules, retention periods, and customer-managed encryption keys, then prepare restore plans with explicit policies for handling existing resources.
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Build custom WordPress themes, plugins, and editor blocks, extend WooCommerce stores, and add REST API endpoints. The skill also guides input protection, permission checks, caching, and database query tuning to improve security and performance.
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Test REST, gRPC, and WebSocket APIs for weaknesses in authentication, access controls, input handling, and configuration. Provides protocol-specific checks, tool guidance, and detection indicators to help document reproducible findings and severity during authorized assessments.
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Review Apache Pinot changes against naming and API conventions, including public names, method signatures, REST endpoints, JSON fields, and documentation. Use it when adding or renaming elements exposed to other code or users.
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Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc + binscatter. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step Stata pipeline an applied economist runs on every paper — (1) data import & cleaning (use/import, destring, misstable, duplicates, merge assert), (2) variable construction (gen/egen/winsor2/xtile/xtset with L./F./D.), (3) descriptive statistics & Table 1 (tabstat/balancetable/asdoc), (4) classical diagnostic tests (sktest/swilk/hettest/imtest/xtserial/xttest3/vif/dfuller/kpss/hausman/estat overid), (5) baseline modeling (reg/xtreg/reghdfe/ivreg2/ivregress/csdid/did_imputation/eventstudyinteract/sdid/rdrobust/synth/psmatch2/teffects/heckman/qreg/ppmlhdfe), (6) robustness battery (bacondecomp/honestdid/rwolf/ritest/wildbootstrap/oster), (7) further analysis (subgroup/triple-diff/interactions/medsem/marginsplot/binscatter by group), (8) publication-ready tables & figures (esttab/outreg2/estout/coefplot/marginsplot/rdplot/twoway combined). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `teffects ipw` / `teffects ipwra` / `teffects aipw` / `eltmle`, Mendelian randomization via `mrrobust` (IVW / Egger / weighted median) and `mregger` / `mrpresso`, KM / Cox / AFT / RMST survival via `sts` / `stcox` / `streg` / `strmst2`, E-value sensitivity via `evalue` (Linden-Mathur), principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `ddml` / `pdslasso`, S/T/X/R/DR meta-learners via `crforest` and `ddml interactive`, causal forest via `crforest` / `cforest`, BART/BCF via `bart` / `bartCause`-style externals, CATE distribution + policy tree via `crforest`, off-policy evaluation, conformal causal externals, fairness audit, DAG learning via `pcalg` / external Python callouts). Use when the user asks for a complete Stata empirical analysis, wants a reproducible .do-file pipeline, needs a Stata counterpart to the Python StatsPAI / Full-empirical-analysis-skill, or names a specific Stata step in isolation ("run reghdfe with two-way clustering", "csdid event study", "winsor2 at 1%", "esttab to LaTeX", "coefplot with CI", "ivreg2 weak-IV test", "synth_runner placebos", "teffects psmatch balance check"). Mode A triggers on "target trial emulation Stata", "teffects ipw aipw", "eltmle", "mrrobust", "mregger weighted median", "stcox AFT survival", "strmst2", "evalue Stata", "STROBE Stata", "公共健康 Stata", "流行病学 Stata". Mode B triggers on "ddml Stata", "pdslasso", "crforest causal forest Stata", "policy tree Stata", "因果机器学习 Stata".
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GDPR Legitimate Interest Assessment (LIA) — Guided assessment for Art. 6(1)(f) GDPR using the EDPB three-step test. Based on EDPB Guidelines 1/2024, EDPB Opinion 28/2024 (AI models), the OSS Case Digest on Legitimate Interest (McIntyre 2026), CNIL AI guidance (June 2025), ICO guidance, and key CJEU case law. Use when: (1) user needs to assess whether legitimate interest is appropriate, (2) user asks about Art. 6(1)(f), "Interessenabwägung", "berechtigtes Interesse", "balancing test", or "LIA", (3) user wants to document a legitimate interest assessment, (4) user mentions the three-step test, (5) user evaluates necessity or proportionality under Art. 6(1)(f), (6) user discusses direct marketing, fraud prevention, IT security, employee monitoring, AI training, web scraping, or credit checks in context of legal basis, (7) user handles a right to object (Art. 21), (8) user asks about children's data, profiling, or cross-border data sharing under legitimate interest, (9) user compares legitimate interest against other legal bases. Do NOT use for: consent assessments (Art. 6(1)(a)), contract performance (Art. 6(1)(b)), DPIA workflows, or pure ePrivacy/cookie compliance questions — though the skill does address the ePrivacy/GDPR overlap where relevant.
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Handles GDPR Article 18 right to restriction of processing requests, covering the four grounds for restriction (accuracy contest, unlawful processing, erasure opposition, legitimate interest pending), technical flagging mechanisms, and lifting procedures. Activate for restriction request, Art. 18, processing freeze queries.
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Fix features broken by REST API responses that flatten Nostr events, losing tag data. Use when: (1) A feature works for WebSocket-loaded events but not REST API-loaded ones, (2) A model field (like sha256, textTrackRef) is null for REST API data but set for WebSocket data, (3) REST API returns denormalized fields (d_tag, video_url) but omits raw tags array, (4) hasSubtitles/hasFeature returns false for REST-loaded videos. Common in Nostr clients that use both REST APIs (for analytics/bulk queries) and WebSocket (for real-time events).
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Audit Pinterest Ads measurement, Pinterest Tag and Conversions API, catalog and shopping readiness, visual creative, audiences, Performance+ intent, budgets, brand safety, and reporting. Use for Pinterest Ads, promoted Pins, shopping ads, catalog sales, Pinterest Tag, Pinterest Conversions API, or Pinterest Performance+.
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Audit Pinterest Ads measurement, Pinterest Tag and Conversions API, catalog and shopping readiness, visual creative, audiences, Performance+ intent, budgets, brand safety, and reporting. Use for Pinterest Ads, promoted Pins, shopping ads, catalog sales, Pinterest Tag, Pinterest Conversions API, or Pinterest Performance+.
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stacked PRの下位PRがマージされた後に上位branchをrestack（rebase/cherry-pick再構成）する際に使用。「restackして」「上位PRを更新して」「restack after merge」「PRのbaseを更新」「スタックを整理」という依頼でトリガーする。対象sliceの特定→rebase→変更ファイル確認と代表テスト実行→force-with-leaseでpush→PR base更新→auto-merge判定の順で進める。
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汇集使用Kotlin和Ktor构建HTTP服务器的结构与实现示例，涵盖API路由、认证、JSON转换、组件组装、双向通信及集成测试。
Design APIs and interfaces between modules with clear inputs, outputs, naming, and errors. The skill guides compatible extensions, input validation, and retry handling so callers can use interfaces consistently without accidentally repeating state-changing operations.
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Rebuild modified packages in the Storybook monorepo and restart its internal UI after code changes. The workflow provides the running URL and can optionally create a UI review of stories related to the changes.
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Test REST, GraphQL, and gRPC APIs with Strix using schemas, credentials, and example data. Investigate authorization flaws, excessive data exposure, and other API risks, then verify findings with requests that reproduce the issue.
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Choose between REST, GraphQL, and tRPC based on who uses an API and how it is deployed. Define consistent responses, pagination, authentication, and versioning, supported by concrete request examples and failure cases.
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Build Node.js APIs and backend services with Express/Fastify. The skill guides authentication, database integration, error handling, and operational practices such as logging and health checks, which report whether a service is working.
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Organize Confluence team wikis and project documentation with clear page hierarchies, labels, and templates. Use macros, built-in content tools, to assemble indexes and reports, with REST API guidance for creating and updating pages.
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Design REST or GraphQL APIs by defining data relationships, requests, responses, and authentication. Produce OpenAPI specifications, machine-readable API descriptions, with consistent errors, pagination, and versioning plans, then validate contracts using a mock server.
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Build Python APIs with FastAPI and Pydantic V2, including input validation, database operations that avoid blocking other work, and token-based authentication. Implement REST or WebSocket endpoints, then check their behavior with automated tests and generated API documentation.
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