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概要と使いどころ
Design a focused lesson observation protocol with specific look-fors and evidence collection methods. Use when planning peer observations, coaching visits, or developmental classroom visits.
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。
Structure a student's self-determined project with mentoring checkpoints, competency alignment, and reflection. Use when guiding student-led projects within a competency-based framework.
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。
Select evidence-based study strategies matched to material type, learning goal, and student habits. Use when advising students on revision techniques, homework, or independent study approaches.
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。
Author learning targets for a competency across developmental bands with precise, observable progression language. Use when writing 'I can' statements for competency-based programmes.
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 document set for a document-based lesson — selecting and sequencing sources for analytical tension around a central question. Use when assembling sources for a new lesson or when an existing set produces flat responses.
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 developmental band system mapping student growth from early childhood through upper secondary. Use when building competency-based curriculum architecture for a school or programme.
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。
Evaluate a teacher-drafted central historical question for its capacity to drive genuine historical inquiry. Use when assessing whether a question will generate real evidence-weighing or produce shallow responses.
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 an uninterrupted work cycle with choice-based activities structured within a realistic time block. Use when planning Montessori-style independent work periods or extended choice time.
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。
Map knowledge components and skill hierarchies for a cognitive tutoring system or adaptive learning platform. Use when designing intelligent tutoring software or skill-based mastery systems.
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 sequence where students compare AI's handling of the same question across disciplines, developing a mental model of where AI is reliable vs. distorting based on knowledge type.
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 an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.
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 an inquiry sequence anchored in a local ecosystem that embeds science or geography curriculum content. Use when teaching through local living systems like gardens, ponds, or hedgerows.
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。
Oxylabs proxy networks: Residential, Mobile, shared Datacenter/ISP, and Dedicated Datacenter/ISP proxies with geo-targeting, IP rotation, session persistence, and port-based sticky IPs. Use when routing traffic through proxies, building scrapers with proxy auth, rotating or sticky sessions, whitelisting IPs, or accessing geo-restricted content.
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。
Sanctions and export control analysis tool for Claude Desktop. Real-time individual screening across 30+ official lists (UN, EU, OFAC, OFSI, French DGT...), sectoral analysis, dual-use goods (EU Reg. 2021/821), US/China extraterritorial regimes (EAR, ITAR, FDPR, ECL), USD/SWIFT risk and jurisdictional mapping across 30+ countries. All results sourced and verified in real time — no memory-based answers. Responds in French, English, German, Spanish, Russian and Chinese. Updated 19 May 2026 (EU 20th package, UK SEUC, Cuba EO). Indicative guidance only — not legal advice.
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。
Arbitrator research tool for investor-State dispute settlement (ISDS). The tool can summarize arbitrators' experience, with deliverables grounded in primary documents; it can also help find arbitrators based on the issues faced in a particular case. Use when the user asks about an arbitrator ("tell me about arbitrator X", "X, Y and Z"), wants help choosing or shortlisting arbitrators for a case, or asks about appointments, dissents, issue track records (e.g. FET, expropriation), challenge risk, double-hatting, or tribunal composition. Profiles are grounded in the UNCTAD ISDS Navigator dataset plus targeted live lookups (ICSID); deep verification retrieves the actual decisions. Sibling of isds-research.
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 Legitimate Interest Assessment (LIA) — Guided assessment for Art. 6(1)(f) GDPR using the EDPB three-step test. Based on EDPB Guidelines 1/2024, EDPB Opinion 28/2024 (AI models), the OSS Case Digest on Legitimate Interest (McIntyre 2026), CNIL AI guidance (June 2025), ICO guidance, and key CJEU case law. Use when: (1) user needs to assess whether legitimate interest is appropriate, (2) user asks about Art. 6(1)(f), "Interessenabwägung", "berechtigtes Interesse", "balancing test", or "LIA", (3) user wants to document a legitimate interest assessment, (4) user mentions the three-step test, (5) user evaluates necessity or proportionality under Art. 6(1)(f), (6) user discusses direct marketing, fraud prevention, IT security, employee monitoring, AI training, web scraping, or credit checks in context of legal basis, (7) user handles a right to object (Art. 21), (8) user asks about children's data, profiling, or cross-border data sharing under legitimate interest, (9) user compares legitimate interest against other legal bases. Do NOT use for: consent assessments (Art. 6(1)(a)), contract performance (Art. 6(1)(b)), DPIA workflows, or pure ePrivacy/cookie compliance questions — though the skill does address the ePrivacy/GDPR overlap where relevant.
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。
Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities. This skill should be used when the user asks to "map AI Act obligations", "check what we need to do under the AI Act", "create a compliance checklist", "check deployer obligations", "assess provider duties", or mentions Art. 26, Art. 16-17, AI literacy Art. 4, DPIA, fundamental rights assessment, or "Pflichtenkatalog" under the AI Act.
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。
Matter budgeting and ongoing WIP/variance monitoring. Build phase-based fee estimates at matter setup, run bottom-up budgets by jurisdiction or workstream, calculate contingency, and structure AFA arrangements (fixed fee, capped fee, phased fixed fees). Ongoing monitoring: WIP tracking against budget, proportionality assessment (spend vs progress), variance commentary with root cause analysis, forecast-to-complete, realisation monitoring, write-off analysis. Trigger on: 'build a budget', 'fee estimate', 'what will this cost', 'WIP review', 'budget vs actual', 'how are we tracking against budget', 'we're over budget', 'realisation is poor', 'what's our ETC', 'budget for the German workstream', 'model the financial impact of this scope change', 'draft a fee adjustment', 'write-off analysis', 'how much contingency', 'AFA structure', 'fixed fee estimate', 'budget update', 'forecast to complete'.
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。
Audits a website for compliance with Azerbaijan's Law on Personal Data No. 998-IIIQ and, where applicable, EU GDPR plus ePrivacy/cookie consent rules. Inventories the privacy documents present (privacy policy, cookie policy, cookie banner, consent flow, controller and DPO contact, data subject rights channel, cross-border transfer disclosures, AZ operator-registration references) and scores each against the applicable statutory requirements. Produces a dual-layer report: a plain-language traffic-light summary for business owners plus a clause-by-clause findings table with article-level citations for lawyers. Assessment-only — no drafting. Use whenever the user shares a URL or privacy/cookie policy text for an AZ-based or AZ-targeted site; also when the user mentions an .az domain, Law 998, the AZ State Register, ePrivacy, an Art. 27 EU representative, or asks "is my site GDPR compliant", "do I need to register as an operator in Azerbaijan", or "is our cookie banner lawful" — even without the word "audit".
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。
When you want to manage projects across your businesses using a kanban + Eisenhower methodology. One kanban per business (whatever portfolio of businesses, projects, or initiatives you run). Tool-agnostic — connects via API/MCP to whatever PM tool each business uses (Notion, GitHub Projects, Plane, Linear, Obsidian file-based, or manual mode). Async-first output. Six modes — setup (scaffold a new board for a business), triage (Eisenhower-sort the backlog), next (pick the next thing to work on, single board or across all), status (paste-ready async snapshot), unblock (diagnose Review/Blocked column), weekly (Friday pulse + week planning). Triggers on "/pm," "/pm setup," "/pm triage," "/pm next," "/pm status," "/pm unblock," "/pm weekly," "what should I work on next," "kanban status," "Eisenhower this," "triage my backlog," "what's blocked."
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。
When you have a decision to make and want a structured workflow that picks the load-bearing questions, walks through them, reaches a call (or "wait"), and archives the rationale for future reference. Based on the 37signals Guide to Making Decisions (38 questions) plus house additions like Q39 opportunity cost ("what does saying yes displace?"). Triages to 6–8 relevant questions per decision instead of forcing the full set. Archives every decision to ~/.config/makerskills/decide/archive/ with a revisit date so you can check later whether the call was right. Triggers on "/decide," "help me decide," "should I [X]," "I need to make a decision about," "stuck on a decision," "deciding between," "go/no-go on," "what should I do about." This is both the decision-making workflow AND the decision log — making the decision is the act of logging 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。
Expert blueprint for quest tracking systems (objectives, progress, rewards, branching chains) using Resource-based quests, signal-driven updates, and AutoLoad managers. Use when implementing RPG quests or mission systems. Keywords quest, objectives, Quest Resource, QuestObjective, signal-driven, branching, rewards, AutoLoad.
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。
Expert blueprint for RPG stat systems (attributes, leveling, modifiers, damage formulas) using Resource-based stats, stackable modifiers, and derived stat calculations. Use when implementing character progression OR equipment/buff systems. Keywords stats, attributes, leveling, modifiers, CharacterStats, derived stats, damage calculation, XP.
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。
Expert blueprint for TileMapLayer and TileSet systems for efficient 2D level design. Covers terrain autotiling, physics layers, custom data, navigation integration, and runtime manipulation. Use when building grid-based levels OR implementing destructible tiles. Keywords TileMapLayer, TileSet, terrain, autotiling, atlas, physics layer, custom data.
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。