1.2万 件 ・ 関連度順
概要と使いどころ
Design, implement, or review dygo HTTP APIs and public App SDK contracts. Use for Record APIs, metadata and boot endpoints, query behavior, response envelopes, compatibility, and public Go interfaces.
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Implement or review dygo Studio behavior in Vue, TypeScript, Pinia, TanStack Query, Vue Router, the dygo design system, and framework renderers. Use for Studio application logic, navigation, state, API integration, and shared components.
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Drafts board-adopted charters establishing Audit and Compensation Committees for U.S. corporations, covering composition, independence, delegated powers, meeting protocol, reporting, and annual review. Adapts for public (SEC/SOX/exchange) or private governance regimes. Use when creating or refreshing committee charters, preparing for IPO governance readiness, onboarding directors, or conducting governance cleanup. Trigger keywords: audit committee charter, compensation committee charter, board governance, SOX compliance, Rule 10A-3, exchange-standard committees.
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Council — 5 independent AI perspectives + mutual critique + synthesis (adapted from karpathy/llm-council for Claude Code). For high-stakes decisions where the answer does NOT follow unambiguously from the data — go/no-go before real consequences, critiquing a methodology, choosing between competing approaches, pressure-testing a conclusion you're attached to, designing risk controls. NOT for log/data analysis (the council has no data access) and not for factual lookups. Triggers — "convene the council", "run it past the council", "go/no-go", "pressure-test this".
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。
Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).
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。
AI-powered calendar management and agent-based scheduling coordination. Covers calendar APIs (Google Calendar, CalDAV/iCal), AI scheduling assistants (Reclaim, Clockwise, Motion, Cal.com), building custom calendar agents with MCP, multi-calendar merging, timezone management, focus block protection, meeting fatigue detection, and agent-to-agent meeting negotiation protocols. Activate on: "calendar agent", "AI scheduling", "calendar coordination", "meeting scheduling", "calendar API", "focus time protection", "calendar optimization", "Google Calendar MCP", "Reclaim", "Clockwise", "Motion", "Cal.com", "smart scheduling", "calendar-aware agent", "timezone scheduling", "agent negotiation meetings". NOT for: manual calendar UI component design (use form-validation-architect), project management scheduling or Gantt charts (use project-management-guru-adhd), general time-tracking or pomodoro apps (use adhd-daily-planner for time-awareness), building the agent itself from scratch (use agent-creator).
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 negotiating a file-based sprint contract between the generator (developer) and evaluator before code is written. Translates a product-level spec into testable acceptance criteria with rubric tie-ins. Triggers on /mk:sprint-contract, "draft a sprint contract", "negotiate scope for sprint", or before any harness-driven sprint kicks off.
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。
Django Redis caching with django-cacheops. This skill should be used when implementing caching, adding cache invalidation, optimizing API performance, modifying models that affect cached data, or debugging cache-related issues in the Django backend.
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Identify direct miRNA-target interactions from AGO HITS-CLIP, AGO-CLEAR-CLIP (chimeric reads), HEAP (Halo-Ago2 mouse), chimeric eCLIP / miR-eCLIP (deep miRNA-target profiling), or CLASH using chimeric-read processing pipelines, seed-pairing analysis, and 3' auxiliary pairing rules. Use when distinguishing direct miRNA targets from indirect, integrating CLIP-derived target maps with TargetScan / miRDB / DIANA predictions, applying canonical 7mer-8mer seed matching with 3' UTR context, or recovering miRNA-mRNA chimeras at scale.
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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。
Complete bedside prescribing reference for Mirago (mirabegron, beta-3 adrenoceptor agonist) for overactive bladder — covering contraindications, safety screening, drug interactions, dose selection in special populations, titration, and administration. Use when a clinician asks how to start mirabegron, what dose to use in renal or hepatic impairment, is mirabegron safe in this patient, mirabegron drug interactions, or Mirago for OAB.
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。
Build, modify, run, test, screenshot, record, and export Godot 4.x games with the gdx CLI. Use when Codex needs to create a new Godot game project, attach to an existing Godot project, generate GDScript, build scenes/resources from JSON specs, edit a running scene through the gdx daemon, capture screenshots, record animation clips, send input, inspect game state, run Godot tests, or produce exports through gdx.
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。
Analise dados do Google Analytics, revise métricas de desempenho do site, identifique padrões de tráfego e sugira melhorias orientadas por dados. Use quando o usuário pergunta sobre análise de dados, métricas de site, análise de tráfego, taxas de conversão, comportamento do usuário ou otimização de desempenho.
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to ...
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。
Builds comprehensive identity governance and lifecycle management processes including joiner-mover-leaver automation, role mining, access request workflows, periodic recertification, and orphaned account remediation using IGA platforms. Activates for requests involving identity lifecycle management, JML processes, role-based access provisioning, or identity governance program design.
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Baut und betreibt ein anbieterneutrales Self-Care-Kernset für geplante LLM-Aufgaben und Desktop-App-Automationen. Ergänzt deterministisches Policy-Linting, Lock- und Modell-Governance, semantische Prompt-Prüfung, konsistente Mehrflächen-Updates, Mini-Checks und Regeldatei-Hygiene. Nutzen, wenn ein Agent seinen nativen Scheduler entdecken oder eine bestehende Automations-Flotte mit Rollback, Readback und Löschschutz kontinuierlich verbessern soll. Löst aus bei automation self-care, Scheduler-Task-Pflege, Desktop-App-Automations-Wartung, Automations-Flotten-Audit, selbstheilende Zeitpläne, core-set-textautomations, basic-text-automations, textbased-automation-core, textbased-automation-drivers, textbased-governance-automations oder textbased-desktopapp-automations.
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。
Designs a pre-launch evaluation plan for a declarative agent from its instructions text, skills, capabilities, knowledge sources and sample requests: a behaviour contract of testable statements quoted from the text, test prompts by scenario family and tier with setup, expected behaviour, pass and fail criteria and red flags, a red-flag catalogue, a blank scoring sheet, a coverage table and a go or no-go checklist the owner completes and decides. Use when the user asks to "write test cases for my agent", "how do I evaluate this agent before launch", "build a test plan for the agent", "what should I check before publishing this agent" or "give me a go no-go checklist". Do not use for finding injection or leakage exposures in the instructions, use agent-instructions-red-team instead; do not use for reviewing one SKILL.md, use skill-file-reviewer instead. Drafts for human review; never approves, authorises or signs off.
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。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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 the user asks to "map the category narrative", "tear down how competitors tell their story", or "find the language conventions in our market"; produces a category narrative map — the dominant stories and points of view in the category, its language conventions and framing clichés, and a per-competitor narrative teardown (arc, claimed onlyness, proof pattern) plus how each rival's messaging has shifted over time (scraped copy vs archived copy). Not for the positioning canvas itself — use positioning-mapper; not for the beachhead's beliefs and objections — use audience-belief-mapper; not for SERP keyword targeting — use keyword-research; not for claim adjudication — use offer-claims-registry. 品类叙事/竞争叙事拆解/语言惯例/叙事演变
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。
Integrates Google Mobile Ads (AdMob) into Flutter using google_mobile_ads v7.x with Banner, Interstitial, Rewarded, and Native ad formats. Use this skill whenever implementing app monetization, adding AdMob ads to Flutter, fixing ad loading or display errors, managing ad lifecycle (preload/dispose), preventing memory leaks from undisposed ads, handling GDPR/ATT consent flows, troubleshooting AdMob dashboard integration, or any time the words 'AdMob', 'google_mobile_ads', 'banner ad', 'interstitial', 'rewarded ad', 'native ad', or 'ad monetization' appear in the request. Supports Android (GMA SDK 24.9+) and iOS (GMA SDK 12.14+).
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。
Search Grants.gov for federal funding opportunities by agency, category, and eligibility. 4 tools.
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。
SAM.gov contract opportunities, USAspending awards, and entity lookup. 3 tools for government contracting.
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。
Manage MongoDB Atlas Organizations as Azure ARM resources using Azure.ResourceManager.MongoDBAtlas SDK. Use when creating, updating, listing, or deleting MongoDB Atlas organizations through Azure M...
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。