1,374 件 ・ 関連度順
概要と使いどころ
Design a Montessori three-period lesson for introducing concepts through concrete materials and naming. Use when teaching vocabulary, classifications, or concepts through hands-on materials.
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。
Design a lesson opening that activates prior knowledge and connects previous learning to today's content. Use when planning lesson starters, retrieval openers, or advance organisers.
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。
GDPR Article 28(2) sub-processor approval workflow management. Covers prior specific and general authorization mechanisms, change notification procedures, objection windows, flow-down obligation enforcement, and sub-processor chain risk 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。
Guides the creation and review of data processing agreements under GDPR Article 28(3), covering all eight mandatory clauses. References the 2021 Standard Contractual Clauses and provides a compliance checklist for processor contracts. Activate when onboarding processors, reviewing DPAs, or auditing processor compliance. Keywords: DPA, data processing agreement, Article 28, processor, mandatory clauses, standard contractual clauses.
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。
Design a Montessori three-period lesson for introducing concepts through concrete materials and naming. Use when teaching vocabulary, classifications, or concepts through hands-on materials.
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。
Design a complete lesson study cycle from research question through collaborative planning to research lesson. Use when planning jugyou kenkyuu or collaborative teacher inquiry into practice.
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。
Design a lesson opening that activates prior knowledge and connects previous learning to today's content. Use when planning lesson starters, retrieval openers, or advance organisers.
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。
Run a learning retrospective on the Kai harness. Mines gate-failure logs and 30-day performance results into lessons, triages candidate lessons (promote/keep/retire), and graduates repeated lessons into enforced gate checks with golden corpus cases. Use when "retro", "what have we learned", "triage lessons", "promote lessons", "why does this keep failing", "harness retrospective", or monthly / after any heavy content sprint.
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。
Drafts Articles of Dissolution (Certificate of Dissolution) for U.S. corporations to terminate legal existence via state filing. Reviews articles of incorporation, bylaws, board resolutions, and shareholder consents for jurisdiction-specific compliance. Use when preparing dissolution filings, terminating a corporation, or drafting dissolution certificates for Secretary of State 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。
Initialize or safely upgrade a processor project's root AGENTS.md from a maintained baseline. Use when starting a processor project, adding project-level Agent collaboration rules, or comparing an existing AGENTS.md with the package baseline. This skill only handles AGENTS.md; it does not scaffold documentation, inspect or configure environments, install tools, or modify processor source.
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。
Synthesises retrospective notes, closing reports and post-implementation reviews into a DRAFT lessons-learned document: themed lessons with source counts, anonymised quoted evidence graded by strength, repeats against a prior register, contradictions, and a recommended owner with a stated basis for each follow-up. Names no individual or vendor and assigns no blame. Use when the user asks to "compile the lessons learned", "write up the retrospective", "theme the close-out notes", "what did we learn across these projects" or "refresh the lessons register". Do not use for a single sprint's review, use sprint-review-summary instead; for an incident investigation, use incident-postmortem-drafter; for customer feedback themes, use customer-feedback-theme-synthesis. 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。
Picks the right Netlify protection layer for a deployed site and disambiguates the three unrelated things people call "auth". Use when a developer wants to password-protect a site or previews, restrict a project to their team, make a project public/private, set team visibility defaults, require SSO to view a site, or debug SSO-session symptoms like being logged out mid-session / getting 401s on an SSO-protected site / token expiry or refresh. Routes app-user login ("who is this user in my app") to the netlify-identity skill and dashboard/team SSO SSO elsewhere; this skill only chooses the perimeter layer for site/preview access.
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。
学ぶ目的やこれまでの理解に合わせて、短い対話型レッスンと復習用資料を作るスキル。学習記録を残し、複数回のセッションにわたる学びを支えます。
複雑な作業や失敗から、根本原因、次回の行動、問題を見分ける兆候を抽出し、再利用できる学習記録にまとめます。同じ原因の既存記録との重複も整理します。
Add or verify a model's chat prompt rendering and tokenization in rust/sglang-processor so it matches SGLang's Python serving path exactly (same prompt text, same token ids). Use when adding a model to sglang-processor, porting a model's rendering from sgl-router, bumping Dynamo's renderer, or debugging a processor-vs-Python prompt mismatch.
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。
Hunt SAML / SSO attacks. Patterns: XML Signature Wrapping (XSW) — modify Assertion while keeping Signature valid by relocating signed element, comment injection in NameID (admin@target.com<!--evil-->@attacker.com → some parsers see admin@target.com), signature stripping (remove Signature element entirely, server should reject but doesn't), key confusion (signed by attacker's IdP, accepted by SP), audience-restriction not validated, replay attack (same Assertion accepted twice within validity window). Tools: SAML Raider Burp extension, samlmagic, manual XML manipulation. Detection: any /saml endpoint, /Shibboleth.sso, /sso/saml/, Microsoft ADFS endpoints. Validate: account takeover via altered NameID, admin role injection via altered AttributeStatement. Use when hunting SSO flows, when SAML AssertionConsumerService is reachable, when chaining IdP-trust to SP-impersonation.
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。
Force-links a development or target environment to a Power Platform Pipelines host, overriding any existing association with a previous host. Use when creating a deploymentenvironments record fails with "this environment is already associated with another pipelines host", or when intentionally migrating an environment from one host to another (e.g., Platform Host → Custom Host, or between two Custom Hosts). Calls the documented `ManageEnvironmentStamp` Dataverse action (the API behind the "Force Link" button in the Deployment Pipeline Configuration app). DESTRUCTIVE to the previous host: makers lose access to any pipelines in that host that used this environment. Reversible by running Force Link from the previous host. Use when asked to: "force link environment", "force-link to new host", "switch pipelines host", "environment already associated with another host", "take over pipelines association", "relink environment to host".
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。
Capture, structure, and recycle lessons from active and closed legal matters. Three modes: in-flight capture (triggered by scope changes, risk events, status updates — highest value), mid-matter review (phase gates or quarterly), and matter close retrospective (full structured findings). Lessons are formatted for immediate reuse, not filed and forgotten. Use when a risk materialises, a scope change lands, a phase completes, or a matter closes and you want to convert what happened into something useful for the next matter. Trigger on: 'capture a lesson', 'what did we learn', 'matter close', 'retrospective', 'lessons learned', 'what went wrong', 'what worked', 'phase gate review', 'debrief', 'extract the learning', 'close the matter', 'what should we do differently', 'pattern from this matter', 'improve the next one'.
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。
Design a lesson that embeds PERMA wellbeing elements alongside academic learning objectives. Use when planning lessons that intentionally support both content mastery and student flourishing.
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。
Modify a lesson plan using SIOP sheltered instruction principles to support language learners across all four skills. Use when planning lessons for classes that include EAL students.
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。
Creates a Check for Understanding (CFU) for a math topic or standard: 1–3 targeted formative items whose distractors come from documented student misconceptions, plus a teacher guide routing each likely response to a specific next instructional step. Load BEFORE asking any clarifying question about grade, standard, or topic. This skill is for math; for other subjects, help as you normally would and don't mention the skill to the user. Triggers on asks to create, write, generate, or design a check for understanding, formative check, quick check, or exit ticket for a math concept or standard, and on implicit signals like "I need to see who got it before I move on." Not a quiz, test, or practice set — a CFU is read for what it reveals, not scored, so a numbered quiz or a bare answer key is a different job. Does not create a lesson (k12-lesson-plan-creation, which brings its own exit ticket), tier one (k12-lesson-differentiation), or prepare a teacher to teach one (k12-lesson-prep).
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 HIPAA Business Associate Agreements under 45 CFR §164.502(e) and §164.504(e). Covers required BAA provisions, business associate vs subcontractor obligations, breach notification chain, downstream BA requirements, and termination remedies. Keywords: BAA, business associate, subcontractor, HIPAA compliance, PHI disclosure, termination.
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。
Determines controller-processor relationships for AI services and conducts privacy due diligence. Covers SaaS AI (processor), embedded AI (joint controller), API-based AI (assessment framework), and vendor risk assessment. Keywords: AI vendor, controller-processor, due diligence, SaaS AI, joint controller, Art. 28.
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。
Genome-wide association studies (GWAS) with PLINK. Perform case-control and quantitative trait association testing using logistic/linear regression with covariates, generate Manhattan and QQ plots for result visualization. Use when running GWAS or association tests.
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。