1.9万 件 ・ 関連度順
Generates Bruno collection files (.bru) from Express, Next.js, Fastify, or other API routes. Creates organized collections with environments, authentication, and folder structure for the open-source Bruno API client. Use when users request "generate bruno collection", "bruno api testing", "create bru files", or "bruno import".
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。
Defines caching strategies with cache keys, TTL values, invalidation triggers, consistency patterns, and correctness checklist. Provides code examples for Redis, CDN, and application-level caching. Use when implementing "caching", "performance optimization", "cache strategy", or "Redis caching".
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。
Orchestrates multi-agent AI systems with task delegation, agent communication, shared memory, and workflow coordination. Use when users request "multi-agent system", "agent orchestration", "AI agents", "agent coordination", or "autonomous agents".
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 ready-to-run cURL commands from Express, Next.js, Fastify, or other API routes. Creates copy-paste commands with proper headers, authentication, and request bodies. Use when users request "generate curl commands", "curl examples", "api curl", or "command line api testing".
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 semantic commit messages following the Conventional Commits specification with proper types, scopes, breaking changes, and footers. Use when users request "write commit message", "conventional commit", "semantic commit", or "format commit".
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。
Hardens API security with rate limiting, input validation, authentication, and protection against common attacks. Use when users request "API security", "secure API", "rate limiting", "input validation", or "API protection".
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。
Systematically improves Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS) with prioritized fixes and verification. Use for "Core Web Vitals", "performance", "LCP", "INP", or "CLS".
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。
Defines ROI-based coverage targets with critical path identification, layer-specific targets, and explicit "don't test this" guidelines. Use for "test coverage", "coverage strategy", "test priorities", or "coverage targets".
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 API documentation using OpenAPI/Swagger specifications with interactive documentation, code examples, and SDK generation. Use when users request "API documentation", "OpenAPI spec", "Swagger docs", "document API endpoints", or "generate API reference".
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 a Spark branch or pull request needs final diff hygiene, validation selection, commit scope, remote topology, and readiness checked before publication.
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 a running Spark or DSH web service needs real-browser verification — page load, client-plugin boot errors, console errors, failed requests, or onboarding/dialog rendering — with the repository's own Playwright chromium.
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 a working Spark implementation should be simplified without changing its observed behavior, ownership, compatibility, or public contract.
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 Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.
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 AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind it.
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 a high-stakes analysis, citation set, or decision should be checked by a second independent AI agent that verifies rather than decides, or when disagreement between agents must be surfaced for the human to adjudicate.
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 before sensitive, clinical, identifying, or raw interview data is placed in front of an AI tool, when transcripts or student materials need de-identification, or when a data-minimization gate must run before any analysis or drafting.
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 a researcher asks where to start, which project skill fits the current stage of a study, or in what order literature scoping, source access, vault upkeep, drafting, citation verification, disclosure, and review response should run.
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 an ethics committee or IRB application involves AI anywhere in the pipeline, when KVKK, GDPR, or EU AI Act duties must be mapped to a study, or when consent and disclosure language about AI use needs drafting before submission.
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 before a tag, GitHub release, or Zenodo archive, when README, CATALOG, CHANGELOG, CITATION.cff, the disclosure aggregate, and skill discovery must agree, or when a go or no-go release verdict needs recorded evidence behind it.
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 adapting academic findings for a public audience (op-ed, social post, podcast) and the simplification must stay evidence-faithful, avoid overclaiming, respect embargoes, and disclose AI assistance.
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 coding interviews, focus groups, or open-ended responses with AI assistance, when a codebook needs building or auditing, when intercoder reliability must be computed, or when qualitative quotes need integrity checks before publication.
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 a research proposal needs work packages, milestones, deliverables, a timeline, a risk register, and budget-justification scaffolding, while keeping scientific claims and feasibility honest and human-owned.
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。
Transform brain dumps into polished blog posts in Nick Nisi's voice. Use when the user wants to write a blog post with scattered ideas, talking points, and conclusions that need organization into a cohesive narrative with Nick's conversational, authentic, and thoughtful tone.
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。
Z-Wave attack methodology — sniffing with Z-Force / EZ-Wave / RTL-SDR + ZniffMobile, S0 (legacy) network-key derivation flaw and key reuse, S2 (modern) ECDH commissioning analysis, replay/injection on unauthenticated nodes, default-key brute-force on test deployments, and home-automation hub pivots. Use when targeting Z-Wave smart home devices (door locks, sensors, garage controllers) — common in mid-2010s smart home deployments still in production.
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。