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概要と使いどころ
Use when user shows signs of overwhelm or frustration — repeated failed attempts, tone shifts, sudden brevity, topic abandonment. Guides gentle check-ins without being patronizing or clinical.
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。
Kelly Real Estate Intel: App-in-Skill daily industry intelligence cockpit for real estate and property agencies (Busabase App-in-Skill). Use when the user asks about real estate, property agencies, listings, transactions, competitor ads, client follow-up, or a地产/中介 intelligence workflow. Prepares news/source signals, buyer-intent interpretation, approved sales actions, and channel drafts for review before any external handoff.
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。
Kelly Restaurant Intel: App-in-Skill daily industry intelligence cockpit for restaurants, cafes, and F&B groups (Busabase App-in-Skill). Use when the user asks about restaurants, cafes, food and beverage, menus, local events, daily offers,餐饮, or餐厅 scenes. Prepares news/source signals, buyer-intent interpretation, approved sales actions, and channel drafts for review before any external handoff.
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。
Kelly Insurance Intel: App-in-Skill daily industry intelligence cockpit for insurance and wealth advisory (Busabase App-in-Skill). Use when the user asks about insurance, wealth advisory, client risk reminders, market news, policyholder follow-up,保险, or financial-advisor sales scenes. Prepares news/source signals, buyer-intent interpretation, approved sales actions, and channel drafts for review before any external handoff.
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 bottom-up and top-down role mining techniques to discover optimal RBAC roles from existing user-permission assignments, reducing role explosion and enforcing least privilege.
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。
Comprehensive testing strategies including unit tests, integration tests, E2E tests, property-based testing, visual regression, and test automation. Use when writing tests, setting up testing frameworks, or designing test coverage strategies.
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。
Database optimization, query tuning, indexing strategies, migration management, and performance monitoring for PostgreSQL with Drizzle ORM. Use when optimizing slow queries, designing schemas, creating migrations, or setting up database monitoring.
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。
CI/CD pipeline design, GitHub Actions workflows, deployment automation, infrastructure as code, and release management. Use when setting up CI/CD, automating deployments, configuring build pipelines, or managing releases.
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。
Triage PostHog error tracking issues during a daily or on-call review. Use when the user asks "what's broken?", "what new errors do we have?", "show me top errors today", "what should I look at this morning", or wants a prioritized list of active issues to work on. Surfaces new and high-impact issues, ranks by users affected and recency, points at linked replays, and proposes next actions (investigate, assign, suppress, merge).
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。
Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experiment", "onboarding retention test", "landing page hero experiment", "pricing experiment"), describes it loosely ("the signup experiment", "my pricing test", "the one with the new checkout"), uses a relative reference ("latest", "most recent", "the one I created yesterday"), filters by status (running, draft, stopped, archived), or otherwise refers to an experiment by anything other than its concrete ID.
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。
Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.
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。
Computes sample size and power for clinical trials including continuous, binary, and time-to-event endpoints; superiority, non-inferiority, and equivalence designs; FDA 2016 non-inferiority margin selection with M1/M2 framework; Schoenfeld 1981 and Lakatos 1988 for survival; Schuirmann TOST and 80-125% bioequivalence; minimum clinically important difference (MCID) vs δ distinction. Use when justifying trial size in protocol or SAP per CONSORT 2025 item 7.
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。
Chains a somatic (tumor-normal) SNV/indel and structural-variant pipeline end to end with GATK Mutect2 (or Strelka2), wiring the somatic-specific machinery - panel-of-normals and gnomAD germline-resource priors, GetPileupSummaries/CalculateContamination, and LearnReadOrientationModel FFPE/oxoG orientation-bias filtering fed into FilterMutectCalls. Use when calling somatic mutations from a tumor-normal pair (or tumor-only with PoN caveats), deciding which artifact filter removes which class of false positive, reasoning about VAF/purity/ploidy and clonal-vs-subclonal detection, adding somatic SV/CNV or TMB/MSI/signatures, or routing variants to AMP/ASCO/CAP tier and oncogenicity interpretation (never germline ACMG).
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。
Assess drug-drug interactions — CYP metabolic interactions (substrate/inhibitor/inducer), transporter (P-gp, BCRP, OATP) effects, pharmacodynamic synergy/antagonism, clinical significance scoring, and management recommendations. Use for polypharmacy review, prescribing decision support, and safety analysis when adding or switching drugs.
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 release order, carrier, consignee, pickup location, goods, and validity fields from delivery orders.
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。
Writes an autonomous agent for the CARLA Leaderboard — an AutonomousAgent subclass with setup/sensors/run_step/destroy, a sensor suite inside the track's budget, and the right constructor signature for the leaderboard version (1.0 and 2.x differ). Generates a working skeleton, validates the sensor configuration against the real per-track limits offline, and covers the ROS1/ROS2 agent base classes. Use when the user asks to "write a leaderboard agent", "make my agent work with the leaderboard", "add sensors to my agent", "port my agent to 2.1", or hits SensorConfigurationInvalid.
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。
Follow these patterns when implementing activity emission and audit logging in OptAIC. Use for emitting ActivityEnvelopes on mutations (create, update, delete, execute), designing payloads, and ensuring audit compliance.
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。
Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.
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 WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
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 you need to design, review, or improve security in Micronaut applications — including micronaut-security authentication, @Secured and intercept-url-map rules, JWT/session strategies, SecurityService checks, CORS, CSRF awareness for browser apps, rejection handlers, and sensitive-data-safe logging. This should trigger for requests such as Add Micronaut security support; Review Micronaut security configuration; Improve API authorization in Micronaut; Add JWT security in Micronaut; Harden Micronaut route authorization rules. Part of cursor-rules-java project
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 you need to design, review, or improve security in Quarkus applications — including Quarkus Security with JWT/OIDC, basic auth, @RolesAllowed / @Authenticated / @PermitAll, SecurityIdentity, permission checks, path-based authorization in configuration, exception mapping for auth failures, and sensitive-data-safe logging. This should trigger for requests such as Add Quarkus security support; Review Quarkus security configuration; Improve API authorization in Quarkus; Add JWT/OIDC security in Quarkus; Harden Quarkus authorization rules. Part of cursor-rules-java project
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。
Integrate Red Hat Ansible Automation Platform (AAP) with HashiCorp Vault Enterprise for dynamic SSH credential management. Use when: (1) Configuring Vault SSH secrets engine with AppRole auth for AAP, (2) Creating AAP credentials backed by Vault signed SSH certificates, (3) Provisioning infrastructure with Terraform/Ansible for AAP-Vault integration, (4) Setting up multi-tenant credential management, (5) Configuring golden images to trust Vault SSH CA, (6) Implementing credential rotation strategies. Based on HashiCorp validated pattern.
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 you need to design, review, or improve security in Spring Boot applications — including SecurityFilterChain, OAuth2/JWT resource server patterns, form login basics, method security (@PreAuthorize), CSRF and CORS for APIs, session fixation, security headers, exception handling, password encoding, and sensitive-data-safe logging. This should trigger for requests such as Add Spring Boot security support; Review Spring Boot security configuration; Improve API authorization in Spring Boot; Add JWT resource server security in Spring Boot; Harden Spring Boot security headers and CSRF settings. Part of cursor-rules-java project
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。
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
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。