Build students' capacity to place historical documents in their temporal and social context. Use when students read sources without considering what was happening at the time, or know the context but don't deploy 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。
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概要と使いどころ
Build students' capacity to place historical documents in their temporal and social context. Use when students read sources without considering what was happening at the time, or know the context but don't deploy 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。
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。
Produces an adversarial attack on a legal argument that survives reply. Runs the opposing-counsel discipline twice: an unrestrained first pass, then the same instrument turned on that pass to cut every point that collapses under challenge - attacks on conceded facts, wrong-forum objections, speculation about documents and motives, gotchas with innocent explanations, overclaims, self-refuting assertions, and padding. The deliverable is one standalone attack containing only what can be defended, capped at five heads, not a discussion of the discarded draft. Use to attack, stress-test, red-team or rebut a submission, brief, motion, witness statement, letter or structured legal reasoning. Triggers on "attack this but only with points that hold", "no cheap shots", "what survives reply", "which points can I actually defend", "give me the version I can file", "double-pass adversarial review". Also use when an earlier adversarial review came back overlong or scattershot. Formal British English.
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。
Ricerca giuridica su fonti italiane e UE: normativa, prassi e giurisprudenza in ogni materia (civile, penale, amministrativo, lavoro, tributario e specialistiche). Usare quando l'utente chiede di trovare, inquadrare o citare una norma ("cosa dice l'articolo...", "quale legge disciplina...", "è ancora in vigore...", "che estremi ha..."), cercare sentenze, massime o orientamenti, verificare la vigenza di una disposizione, verificare una citazione o l'esistenza di una pronuncia ("questa sentenza esiste?", "controlla le citazioni di questo atto"), cercare precedenti a favore e contro una tesi ("conformi e difformi", "sentenze pro e contro"), trovare un CCNL o le decisioni di ABF, ACF, AGCM o del Garante, creare un documento fondato su fonti (atti, pareri, clausole, contratti, memorie, diffide), o impostare una strategia processuale ("come imposto la causa", "come gestiresti questo caso", "conviene agire o transigere"), anche quando la fonte non è nominata. Non usare per domande non giuridiche.
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。
Verifies UK case-law citations, pinpoint references and quotations against the official public register — The National Archives' Find Case Law — and statutory references against legislation.gov.uk, before a document that cites them is relied on, served or filed. Every check returns a graded verdict: VERIFIED, MISMATCH (the citation resolves to a different case — the classic AI miscitation), NOT ON REGISTER, OUTSIDE COVERAGE (the register cannot answer — absence proves nothing), or UNCHECKABLE (a law-report citation). The grading exists because there are two ways to get this wrong: citing a case that does not exist, and accusing a real case of not existing. Use when asked to check citations, verify a case exists, confirm a quotation is verbatim, check a pinpoint paragraph, audit a draft's authorities, screen a document for hallucinated cases, or check a statutory provision is in force. Not a substitute for reading the judgment: existence is not authority.
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。
Mandatory external verification workflow for ALL non-trivial factual claims before presenting them as true. This skill MUST be used whenever Claude is asked to research any topic, answer factual questions, provide current information, draft documents containing factual claims, give legal advice or cite legal authority, discuss current events or public figures, provide technical or scientific information, state statistics or data points, or answer ANY question where the answer could have changed over time. Also trigger when the user asks Claude to 'check', 'verify', 'confirm', 'research', 'look up', or 'find out' anything, or when the user needs information that requires freshness, precision, or source accuracy. This skill overrides any default tendency to answer from memory. If a task involves stating facts, citing sources, or providing current information — use this skill.
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。
Verification-first methodology for the ECCC (Khmer Rouge Tribunal). Every citation is verified against eccc.gov.kh, the ECCC archive or legal-tools.org. Covers Case File numbering, the 001/002/002-01/002-02 structure, the genocide findings against the Cham and the Vietnamese, and the Internal Rules revision discipline. Research aid, not legal advice. Part of the open-source "Skills for International Justice" library — methodology: github.com/jeannesulzer/international-criminal-tribunals-skills
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。
Draft, adapt, and review contracts and clauses aligned with The Chancery Lane Project's methodology for reducing carbon emissions through legal agreements. Use when Claude needs to: (1) Draft new climate-aligned clauses (e.g., net zero commitments, carbon accounting, supply chain decarbonization), (2) Adapt or modify existing contracts to incorporate climate objectives, (3) Review and analyze clauses for alignment with climate goals and decarbonization strategies, (4) Provide guidance on The Chancery Lane Project's house style and drafting methodology for climate-conscious legal 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。
Expert blueprint for idle/clicker games including big number handling (mantissa + exponent system), exponential growth curves (cost_growth_factor 1.15x), generator systems (auto-producers), offline progress calculation, prestige systems (reset for permanent multipliers), number formatting (K/M/B suffixes, scientific notation). Use for incremental games, idle games, or cookie clicker derivatives. Trigger keywords: idle_game, big_number, exponential_growth, generator_system, offline_progress, prestige_system, number_formatting.
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 patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.
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 idle/clicker games including big number handling (mantissa + exponent system), exponential growth curves (cost_growth_factor 1.15x), generator systems (auto-producers), offline progress calculation, prestige systems (reset for permanent multipliers), number formatting (K/M/B suffixes, scientific notation). Use for incremental games, idle games, or cookie clicker derivatives. Trigger keywords: idle_game, big_number, exponential_growth, generator_system, offline_progress, prestige_system, number_formatting.
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 patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.
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。
Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.
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。
SwiftUI's actual mental model — view identity, lifetime, and dependencies (the Demystify canon), state ownership decision rules, Observation's per-property tracking, body-performance discipline, and the main-actor concurrency contract. Use when state resets mysteriously, views re-render too often, animations glitch between branches, choosing @State vs @Bindable vs plain property, or debugging "why did body 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。
SwiftUI layout beyond stacks — the Layout protocol (when custom layout beats GeometryReader), Grid vs lazy grids, custom containers with sections and container values, and lazy-stack/ScrollView performance rules (what breaks laziness, prefetch discipline, scroll APIs). Use when building custom layouts or containers, fixing lazy-stack jank or memory growth, or wiring programmatic/snapping scrolling.
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 wants to optimize configurable system parameters against a measurable scalar objective, especially for model training, inference, quantitative strategies, reinforcement learning, scientific workflows, or other expensive black-box evaluations where reading the project can improve trial selection.
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。
The cellxgene data portal (https://cellxgene.cziscience.com/) provides a graphical user interface to collections of single-cell sequence data processed in standard ways to 'count matrix' summaries. The cellxgenedp package provides an alternative, R-based inteface, allowind data discovery, viewing, and downloading.
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。
The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor
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。
Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).
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 and build expressive 3D scenes, explainers and interactive models with grounded subject knowledge. Use for 3D creation or edits, including scientific visualization and spatial puzzles.
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。
Enumerate every end-to-end feature as strict JSON entries with passes:false, editable-passes-only discipline, and priority order. The ledger fresh-context sessions read to know what's done, what's next, and what they're forbidden to touch.
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。
Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.
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。
Your AI research and engineering brain trust. 59 named personas across 8 cells covering frontier labs, applied product, model architecture, reasoning/RL/agents, alignment and interpretability, theory and science of DL, multimodal and…
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。
Your education and edtech brain trust. 25 named personas across 7 cells covering learning science, curriculum design, AI tutoring, higher-ed strategy, edtech platforms, assessment, and workforce development.
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。