2,085 件 ・ 関連度順
概要と使いどころ
Implements Children's Online Privacy Protection Act (COPPA) compliance under 16 CFR Part 312. Covers verifiable parental consent methods including signed forms, credit card verification, government ID, knowledge-based authentication, and video call. Includes FTC safe harbor programs and enforcement actions. Keywords: COPPA, FTC, children, parental consent, safe harbor, verifiable consent.
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 CCPA Section 1798.105 right to delete and CPRA amendments including service provider obligations, statutory exceptions for legal, security, and internal uses, consumer identity verification procedures, and 45-day response timeline management. Activate for CCPA deletion, CPRA right to delete, California privacy, consumer deletion queries.
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。
Manages deletion requests for children's personal data. Covers parental-initiated versus child-initiated requests, age of capacity assessment, identity verification, scope determination, third-party notification obligations, and regulatory timelines under GDPR Art. 17, COPPA Section 312.6, and UK AADC Standard 15. Keywords: deletion, children, right to erasure, parental request, data deletion, COPPA.
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 age-gating mechanisms for online services to restrict access based on user age. Covers hard gates versus soft gates, neutral age prompts, re-verification triggers, circumvention prevention, and regulatory requirements under GDPR, COPPA, UK Online Safety Act, and DSA. Keywords: age gate, age restriction, neutral prompt, children, online services, access 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。
Manages AI model retention and machine unlearning requirements. Covers training data deletion verification, model versioning for compliance, machine unlearning techniques (SISA, gradient-based), and retraining triggers. Keywords: AI retention, machine unlearning, model versioning, training data deletion, retraining, storage limitation.
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。
Classifies sensitive data in AI/ML training datasets including bias detection for Art. 9 categories, data card documentation, provenance tracking, and consent verification for model training. Keywords: AI training data, ML dataset, bias detection, data card, model training, Art 9, consent, GDPR AI.
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。
Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment monitoring setup. Keywords: AI deployment, privacy checklist, go-live, model deployment, compliance gate.
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。
Manages privacy compliance for employee background checks including criminal record processing under Art. 10 GDPR, DBS checks (UK), national law variations, and reference verification. Applies proportionality and data minimisation to pre-employment screening, defines retention limits, and addresses role-based necessity assessments. Keywords: background check, criminal record, Art. 10, DBS, pre-employment screening, vetting, data minimisation, proportionality.
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 packaging Spring Boot 4 as an OCI image, JVM container, AOT application, or GraalVM native executable. Covers buildpacks, layers, runtime hints, probes, security, and verification.
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 packaging a Spring Boot 3 application as an OCI image or GraalVM native executable. Covers buildpacks, layered images, JVM containers, AOT hints, probes, security, and verification.
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。
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
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 coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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 or revise Godot UI from an approved design, separated art, or a visual reference when scene structure, gameplay binding, and runtime visual verification all matter. Use for complete Godot UI integration; use ordinary Godot UI guidance for isolated node or layout questions that do not require an end-to-end visual workflow.
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。
Production export from Blender to FBX, GLTF, OBJ, USD, and Alembic with scale, pivot, rotation, normals, materials, animation, and collision verification via MCP.
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。
Produce a plain-language manual test plan from the context supplied to it — an executive summary, a high-level list of named tests, and a detail section per test with the steps a person follows by hand and the outcomes they should expect. Use when you want to create, draft, generate, or outline a manual test plan, manual QA steps, hands-on verification steps, or an acceptance walkthrough for a feature, change, branch, plan, or PR. When the plan holds more than five tests and at least two natural categories emerge, both the test list and the detail sections are organized under plain-language categories. When nothing in the supplied context can be manually tested, it says so and asks for more context instead of producing a document. Does not analyze code for automated test coverage gaps — use automated-test-planning. Does not write test code — use tdd. Does not review code quality — use code-review. Does not stress-test an existing plan — use iterative-plan-review.
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。
Create original short videos using the 未来来信｜私密警告被外部世界兑现 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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。
Route substantial coding or repository-review work through a two-stage Sol commander/verifier and separate Luna Max CLI worker. Use when the user explicitly asks Sol to direct or supervise Luna, explicitly requests this router, needs an isolated auditable Luna-owned implementation with a Sol review loop, or asks to diagnose or measure the router itself. Do not use merely because a task involves coding, verification, progress reporting, or token saving. For small or straightforward tasks, keep work in Sol unless the user explicitly requests Luna; router configuration, usage, and efficiency questions should use read-only inspection without launching a worker.
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 skill is brittle, drifting, repeatedly failing, or needs a Reliable Skill Contract. Trigger for phrases like skill lifeguard, reliable skill, self-maintaining skill, negative examples, verification checkpoints, drift signals, replay hooks, or failure log to skill patch. Audits or patches skills so high-value workflows include explicit forbidden behaviors, checkpoints, machine-checkable done conditions, replay or smoke hooks, and drift detection.
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 an agent-produced diff is committed, pushed, opened as a PR, merged, landed, or applied to user files when explicit implementation approval is missing. Trigger for review gate, review pack, approve before landing, diff first then land, human approval, merge gate, commit gate, push gate, or PR readiness. Produces a concise review pack, records risks and verification, and blocks landing until a human explicitly approves or approves with required fixes.
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。
Review whether a repository's coding-agent harness can reliably carry work from intent through controlled execution, verification, delivery, and learning. Use when asked to assess agent readiness, repeated agent failures, Rules/Skills/Hooks/Memory effectiveness, missing validation or recovery loops, or whether a harness repair improved later outcomes. Do not use for code-only audits, AGENTS-only audits, individual skill reliability reviews, or executing the task itself.
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。
Guard long, ambiguous, or stateful AI-agent work from drift. Use when the user asks to run or continue a multi-step task, autonomous loop, bug fix, repo change, PR readiness check, compaction handoff, resume from previous context, cost-control checkpoint, or any task likely to span many tool calls, files, sessions, agents, or verification gates.
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 want a second-opinion review via Codex CLI, cross-verification after another agent implements changes, debugging help, or alternative implementation proposals. Requires Codex CLI to be installed and authenticated.
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。
Fix .well-known files (apple-app-site-association, assetlinks.json) being served as HTML by the @fastly/compute-js-static-publish SPA fallback instead of JSON. Use when: (1) iOS Universal Links or Android App Links are broken because the verification files return text/html instead of application/json, (2) PublisherServer with spaFile config intercepts /.well-known/ paths and returns index.html (200, text/html) instead of 404 for missing files, (3) apple-app-site-association (no file extension) gets wrong content type even when correctly stored in KV. Covers both apex domain and subdomain handler patterns.
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 implementing two-factor authentication setup and verification.
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。