「table」の検索結果

Analyze any OFAC or OFSI enforcement action — by URL, pasted text, or uploaded document — and produce a structured root cause analysis as a formatted Excel (.xlsx) spreadsheet. Use this skill whenever a user names, links to, pastes, or uploads an OFAC or OFSI enforcement action and asks for any of the following: root cause analysis, compliance gaps, what went wrong, lessons learned, organizational self-assessment, or remediation planning. Also trigger when a user asks "analyze this enforcement action", "what were the root causes", "turn this into a checklist", or "how do I make sure this doesn't happen to us". Outputs a single-sheet .xlsx table with six columns: Root Cause | What Went Wrong | How It Went Wrong | What Could Have Stopped It | Is my organization immune to this? (Yes/No/Partial) | Notes.

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EU Data Act (Regulation (EU) 2023/2854) skill for lawyers. Use when the user asks about Data Act classification, drafting, lookup, analysis, or audit. Triggers include "Data Act", "Regulation 2023/2854", "connected product", "related service", "data processing service", "DPS switching", "Article 3(2) pre-contract", "Article 25 contract", "trade-secret handbrake", "international government access", "Chapter VI cloud switching", "Article 50 timeline", "FAQ Q22a", "data holder", "exportable data", "functional equivalence", "Art. 4(10) competing product", and similar EU Data Act phrases. The skill produces lawyer-style Word output and cites verbatim from bundled regulation and FAQ source texts.

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Searches the domestic courts of 122 jurisdictions — 153 databases, 49 automated — for extradition and arrest-warrant surrender decisions, each in its own language and vocabulary. Answers the question no commercial database does: how are OTHER executing states treating this requesting state, or this ground? Searching by requesting state localises its name per jurisdiction (AE becomes 'Emiratele Arabe Unite' in Romania, 'Emirati Arabi Uniti' in Italy), so the sweep finds what those courts actually wrote. Every hit passes a relevance gate; every search leaves a dated report, so the research is reconstructable months later. Use when asked what foreign courts have said about surrender to a given state, whether any European court has refused extradition on prison conditions, assurances or Article 3, for comparative extradition research, or to build a foreign-authority section of an extradition argument. Not for domestic case law of the user's own jurisdiction, and never a substitute for reading the judgment.

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Build a client instruction schedule — a plain-English, Scott Schedule-style Word table that gathers a struggling client's evidence and instructions issue by issue, with a one-page covering note. Use whenever the user asks for a "client instruction schedule", "instruction schedule", "client questionnaire", "schedule of questions for the client", "get instructions from the client on the papers", or says the client is overwhelmed and needs the case broken into manageable questions. Also trigger when asked to turn case papers into a structured request for client input. Do NOT use for court-facing Scott Schedules, pleadings, witness statements, or advice letters — this skill produces a client-facing working document only. Output is always a .docx draft for solicitor review, never a final document.

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When your bar comes asking "show me how you billed AI-assisted work" — and ABA 512, Florida 24-1, California, New York, and DC all have opinions out — you need an artifact that survives review. billable-time produces it. From your Claude Code session logs, it drafts reviewable time entries plus a printable HTML audit packet with: SHA-256 chain of evidence (source files + matter.yml + active disclosure pack + verifiable artifact self-hash), attorney identity and signature block, a bar-opinion disclosure pack with starter language for five jurisdictions, and content-aware deterministic narratives derived from filename and tool shape — never from prompt text by default. The tool refuses to bill on its own. --strict mode refuses to ship the artifact if any audit invariant fails (broad routes, missing attorney, missing/unverified disclosure). Comes as a Node CLI and a self-contained browser version (no backend; JSONL never leaves the page). 15 invariant tests verify the contract. AGPL-3.0.

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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".

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Archéologie des sources juridiques anciennes via Gallica (BNF, API stables, sans clé) : débats parlementaires du JO depuis 1871 (genèse des lois de la IIIe République), notes d'arrêt et doctrine d'origine dans les recueils Sirey et Dalloz, Bulletins civil et criminel anciens, Recueil Lebon, JO Lois et décrets 1881-2015, thèses et traités du XIXe-début XXe, Gazette des tribunaux, Bulletin de l'Inspection du travail. Déclencher dès que l'utilisateur cherche l'origine historique d'un texte, d'un concept ou d'une jurisprudence : « débats de la loi de 1884 », « note de Josserand », « que disait la doctrine en 1900 », « première apparition de la notion de… », « généalogie / histoire de l'article… », « arrêt ancien », « thèse d'avant-guerre », « Gallica », « BNF », ou toute recherche juridique antérieure aux bases modernes (Légifrance ne remonte pas avant l'époque contemporaine, Judilibre non plus). Déclencher aussi en COMPLÉMENT de travaux-preparatoires quand la loi étudiée est antérieure à 1958.

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Turn an interpretive-ambiguity audit of a legal text — contract, statute, regulation, or judicial opinion — into a polished deliverable. Produces a multi-page website (default), a single-page interactive site, a Microsoft Word document, a PowerPoint deck, or a LaTeX/PDF. Use whenever a user has a stress-test result, ambiguity audit, or "where will this be litigated" scenarios and wants to publish, present, or share them. Triggers on "publish the audit," "make a report from this," "turn this into a website / deck / brief / Word doc," "make a Netlify site," "build slides of these ambiguities," "render the scenarios," "package this stress test," "produce a LaTeX version," and similar. Pairs with the ambiguity-stress-test skill (the underlying analysis) but works on any structured or semi-structured ambiguity analysis. Visual design is opinionated but the user can override colors, fonts, and brand label. Most formats need Python and a writable filesystem; single-file HTML works where the host has neither.

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AI co-counsel for divorce and family-law attorneys — a jurisdiction-portable scaffold spanning the full matter lifecycle. Eight operating modes mirror how a matter actually moves: intake and onboarding, financial disclosure, children and support, property division and QDRO, discovery and document review, drafting, negotiation and mediation prep, and court prep — plus post-judgment modification and enforcement. The methodology is jurisdiction-agnostic: it forces real, verifiable research for every local form, formula, or rule rather than inventing one, handling common-law, community-property, civil-law, and MENA personal-status regimes as variables. Built around one non-negotiable: privilege. It drafts, analyzes, organizes, and pressure-tests. It is not the lawyer.

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When the user wants to create, generate, edit, or optimize images for marketing — blog heroes, social graphics, product mockups, profile banners, listing visuals, or brand assets. Also use when the user mentions 'AI image generation,' 'generate an image,' 'create a graphic,' 'product mockup,' 'hero image,' 'social media graphic,' 'banner image,' 'cover photo,' 'profile banner,' 'listing screenshot,' 'Flux,' 'Flux Kontext,' 'Midjourney,' 'DALL-E,' 'GPT Image,' 'ChatGPT Images,' 'Ideogram,' 'Gemini image,' 'Nano Banana,' 'Recraft,' 'Stable Diffusion,' 'Canva,' 'Figma,' 'image optimization,' 'compress images,' 'WebP,' or 'OG image.' Use this for general-purpose marketing image creation and optimization. For paid ad image creative and platform-specific ad specs, see ad-creative. For video production, see video.

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When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.

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Expert blueprint for Battle Royale games including shrinking zone/storm mechanics (phase-based, damage scaling), large-scale networking (relevancy, tick rate optimization), deployment systems (plane, freefall, parachute), loot spawning (weighted tables, rarity), and performance optimization (LOD, occlusion culling, object pooling). Use for multiplayer survival games or last-one-standing formats. Trigger keywords: battle_royale, zone_shrink, storm_damage, deployment_system, loot_spawn, networking_optimization, relevancy_system, snapshot_interpolation.

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Bevy ECS economy: Wallet components, a PriceTable resource, Purchase and Transfer messages, vendor stock. Use when a debit must see the price row and two wallets must not be written by unordered systems. Keywords: Bevy, economy, wallet, price, Purchase, get_many_mut.

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Bevy 0.20 dialogue data: line tables in a resource, the current line index on a component, and choice flags filtered before the write. Use when lines or choices advance. Keywords: Bevy, dialogue, line index, choices, ECS.

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Bevy 0.20 kinematic character movement: intent components, FixedUpdate integration, coyote time, and jump buffer. Use when a player or actor walks or jumps and the step must stay stable. Keywords: Bevy, movement, FixedUpdate, coyote, jump buffer, ECS.

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When you want to clean and reformat content (usually from your terminal) for pasting into Slack, Notion, Twitter/X, LinkedIn, email, GitHub, or plain text. Strips ANSI codes, box-drawing chars, terminal prompt artifacts, and applies destination-specific formatting. Default input is the system clipboard; default output is both the clipboard and a chat preview. Triggers on "/paste", "/paste [destination]", "clean this for X," "format for slack/notion/twitter/linkedin/email/github," "render as markdown," "paste-ready," "strip formatting," "make this copy-pastable." Default destination is plain. Also scans for secrets (API keys, tokens, .env values) and warns before copying anything sensitive.

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When you want to model personal financial scenarios — house purchase + rental income (ADU, bedroom rentals, house-hacking), renovation budgets, monthly cash flow, big-purchase decisions, savings/investment what-ifs for a household. Ships with a house scenario template; other scenarios (refi, car, education, retirement, side income) slot in as templates. Outputs markdown scenario comparison tables. Saves scenarios to ~/Documents/personal-cfo/ with an index in ~/.config/makerskills/personal-cfo/archive/. Composes with decide, deep-research (rental comps, rates), business-brainstorm, second-brain. Triggers on "/personal-cfo," "model this scenario," "house math," "rental forecast," "monthly cash flow," "what if I rent out the ADU," "compare these housing scenarios," "should we buy this house," "house-hack math," "renovation budget."

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Static analysis of UEFI/BIOS firmware dumps using Intel's chipsec framework. Decode firmware structure, detect known malware and rootkits (LoJax, ThinkPwn, HackingTeam, MosaicRegressor), generate EFI executable inventories with hashes, extract NVRAM variables, and parse SPI flash descriptors. Use when analyzing firmware .bin/.rom/.fd/.cap files offline without requiring hardware access.

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Turn a one-line description of a repetitive task into a reusable, self-guarding slash command. loop-forge diagnoses the task into one of 5 loop shapes (Batch / Pipeline / Refine / Watch / Explore), interviews for the blanks, and auto-injects two safety devices the user didn't know they needed — an independent verifier (maker ≠ checker) and a hardstop (a budget/count/cooldown ceiling) — then previews the result and stamps it as a `/command` they can run forever. Use when the user says "/loop", "/loop-forge", "/make-it-loop", "automate this", "make this repeatable", "turn this into a command", "do this for all 100 items", "do X every time Y happens", "generate several and pick the best", or otherwise wants to capture a recurring task as a reusable slash command instead of re-typing the prompt by hand. Works in any language: it interviews the user and writes the stamped command in the user's own language. Non-goal — it does not schedule unattended runs (launchd/cron) or publish externally on its own; it stamps the reusable command and stops there.

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Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, annotate, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, timeline markers, chapters, beat cues, review notes and ranges, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth-assisted relighting, grayscale depth-video conversion, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor evaluation.

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Expert blueprint for Battle Royale games including shrinking zone/storm mechanics (phase-based, damage scaling), large-scale networking (relevancy, tick rate optimization), deployment systems (plane, freefall, parachute), loot spawning (weighted tables, rarity), and performance optimization (LOD, occlusion culling, object pooling). Use for multiplayer survival games or last-one-standing formats. Trigger keywords: battle_royale, zone_shrink, storm_damage, deployment_system, loot_spawn, networking_optimization, relevancy_system, snapshot_interpolation.

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Post-earnings quarterly update reports for A-share companies under coverage. Analyzes 业绩快报/正式财报, generates variance tables (actual vs 一致预期 vs prior), flags key drivers, and drafts structured earnings notes in Chinese sell-side format. Use instead of the original earnings-analysis skill for Chinese equities. Triggers on "A股财报分析", "季度业绩点评", "年报/中报点评", "earnings review", or "[company] earnings".

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Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

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Create runbooks, playbooks, and technical documentation for engineering teams. Use when the user wants to document a process, create a runbook, build operational docs, or formalize any repeatable technical procedure. Triggers on requests like "create a runbook for...", "document this process", "write a playbook", or any technical documentation request.

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。