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Knowledge base from MIL-STD-40051-2C (15 Dec 2015), Preparation of Digital Technical Information for Page-Based Technical Manuals. Use for TM/TDP structure, work packages, front/back matter, style/format, warnings/HAZMAT, change packages, content selection matrices, and plate exemplars. Primary Training & Documentation pack (cluster 25) with Ops & Maintenance procedure use—page-based (-2C) only, not IETM 40051-1.

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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.

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Схема-терапия Джеффри Янга: схемы, режимы, концепция внутреннего ребенка и копинговые стили — психообразовательная подача.

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Terapia de Esquemas según Jeffrey Young: Esquemas, modos, concepto del niño interior y estilos de afrontamiento — presentado psicoeducativamente.

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杰弗里·杨（Jeffrey Young）图式疗法：图式、模式、内在儿童概念与应对风格——心理教育呈献。

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ジェフリー・ヤングによるスキーマ療法：スキーマ、モード、インナーチャイルド概念、コーピング・スタイル — 心理教育的アプローチ。

Entfernt KI-Spuren, Chat-Reste, Platzhalter und LLM-Stilmuster aus fertigen Texten und prüft die AI-Disclosure auf Vollständigkeit und korrekten Sitz.

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Standard-Gerüst für rotierende Pipeline-Checks: Pro Lauf genau ein Ziel aus einer Menge (Projekte, Ordner, Repos) wählen — bevorzugt das am längsten ungeprüfte —, den Check durchführen, Ergebnis in einer Check-Registry und einem Verlaufslog festhalten. Nutze diesen Skill, wenn ein wiederkehrender Check über viele Projekte verteilt werden soll („prüfe regelmäßig alle X auf Y"), wenn eine Automatisierung Doppelprüfungen vermeiden muss, wenn eine Check-Registry/CHECKS-LOG-Struktur angelegt oder benutzt wird, oder wenn eine periodische Qualitätsrunde (Quellencheck, Style-Check, Health-Check, Audit) über eine Pipeline fair verteilt werden soll.

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Turns a list of merged changes, closed work items or commit messages the user provides into DRAFT release notes under the version heading and date the user supplies, grouped as features, fixes and other, in the organisation's tone from the style guide or prior notes given, with every entry traced to its source item, breaking changes and required actions flagged first, and internal-only items held back for the release owner to confirm. Use when the user asks to "write the release notes for this version", "turn these merged pull requests into a changelog", "summarise what shipped this sprint for customers", "draft the what's new for this release" or "group these closed tickets into release notes". Do not use for an announcement email or intranet post about a launch, use announcement-drafter instead; for a change ticket, use change-request-pack; for a how-to article about one fix, use knowledge-article-drafter. Drafts for human review; never approves, authorises or signs off.

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Drafts one internal or external announcement (email, intranet post, town hall script, customer notice or press statement) in the organisation's voice from the facts, audience, sender and style guide the user provides, with a fact trace, reader-questions check, pre-send checks and an approvals checklist left blank for the named approvers. Use when the user asks to "announce this change to all staff", "draft the customer notice", "write the town hall script", "prepare a holding statement" or "rewrite this in our voice". Do not use for a digest of several items, use internal-newsletter-drafter instead; to pre-test a drafted message against personas, use communication-pretest-panel. Drafts for human review; never approves, authorises or signs off.

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Render a web page on the host and measure it - screenshots, computed styles, element boxes and post-script text - when a page only exists after its scripts run or when the question is about layout. Covers choosing between web_fetch and a render, reading a design's real measurements, comparing viewports, and the egress policy that decides what may be reached.

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Work with SuperCollider projects as files - the shape of a .scd piece, how to read and write one with sc_project, how to send the file that is on disk into the live session with sc_load, what state belongs in the session and what belongs in the file, and how to package a piece the SuperCollider way (a folder with its .scd, its SynthDefs, and a Quark-style layout) instead of inventing a format.

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Read Figma files, component libraries, styles, comments, and export rendered assets (PNG / SVG / JPG / PDF) via Figma's REST API. Use when the user needs programmatic access to design files, to pull node data into code generation, or to export assets without opening the Figma desktop app.

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Manage Railway projects, services, deployments, environments, variables, and deployment logs via Railway's public GraphQL API — one endpoint, relay-style pagination, two token flavors (account vs project), typed mutations for deploys and env vars. Use when the user wants to deploy, check service status, manage env vars, or read deployment logs programmatically without the Railway MCP installed.

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Prepare and launch LoRA, LoKr, or T-LoRA training through lora-scripts-next (SD-Trainer), Anima-first. Use when the user asks to train a character, style, or concept LoRA, choose parameters or repeats and epochs, start a run, or monitor training on Anima, SD1.5, SDXL, or Flux. Organize and caption the dataset, run dataset-doctor, choose a documented starting preset from image count and VRAM, show one confirmation card, then call the mikazuki API and monitor its log.

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Audit and repair a kohya-style LoRA dataset before training. Use when the user asks to check, validate, inspect, fix, clean, 体检, or 修 a dataset, captions, or tags. Inspect image count, repeats and step budget, resolution and aspect buckets, duplicates, corrupt or non-RGB images, missing or empty captions, trigger consistency, and tag-frequency hygiene. Return a structural PASS, WARN, or FAIL report and apply only confirmed fix_dataset.py actions, dry-run first with displaced originals quarantined.

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Build an Anima LoRA from a single-character or style name, from Danbooru collection through curation, section-ordered WD14 captions, dataset checks, confirmed training, fixed-seed checkpoint validation, and a staged Civitai draft. Use for requests such as make a LoRA of X, collect images and train a character LoRA, train and upload to Civitai, or build a dataset from scratch and publish. Delegate training to lora-trainer and structural checks to dataset-doctor; never train without confirmation and never auto-publish.

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Reimagine a supplied photo as a tactile fuse-bead mosaic keepsake on a spacious editorial canvas. Use for 拼豆纪念画、照片拼豆效果、fuse bead photo art or perler-style visual mockups, not exact craft patterns or bead-count charts.

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Use when deciding whether to implement UI from native HTML/CSS, accessible primitives, shadcn-style source components, or visual component registries such as 21st.dev, Aceternity, React Bits, Motion Primitives, Magic UI, or Animate UI.

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Build a complete but efficient Nature-style Chinese PPTX presentation from a remote-sensing, Earth-observation, geospatial AI, or broader scientific paper, preprint, PDF, article text, abstract, figure legends, or reading notes. Use this skill whenever the user asks to make slides/PPT/PPTX for journal club, group meeting, paper sharing, thesis seminar, lab meeting, department report, or academic presentation from a remote-sensing research paper. It identifies the paper type and argument, selects only the figures needed for the story, writes Chinese slide content and speaker notes, creates the actual .pptx deck, and runs an explicit self-review/corrective revision loop focused on figure quality, text overflow prevention, and non-template visual design before delivery. Also trigger on general academic-presentation requests even without the word "Nature", such as turning a paper into slides, building an academic talk deck, conference/defense presentations, and Chinese phrasings like 论文做PPT、遥感论文汇报、组会PPT、文献汇报、学术汇报、做幻灯片、讲paper、读书报告PPT.

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Teach a micro-task in the style of the Feynman Technique. Start with a small concrete observation or action, explain the underlying concept from what the learner sees, then walk the learner step-by-step through the task. Before marking the micro-task done, require the learner to explain the underlying concept back in their own words; correct any misunderstanding before advancing.

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Builds a WooCommerce-style AJAX product search select (the selectWoo / wooselect dropdown) — class="wc-product-search" + the data-action attribute pointing to woocommerce_json_search_products (products only) or woocommerce_json_search_products_and_variations (products AND variations, often the right choice). Pre-selected items rendered server-side as <option selected> via wc_get_product() + get_formatted_name(); WC's wc-enhanced-select script auto-enqueued on WC admin screens, explicit enqueue required on non-WC pages. Solves the "load 20k products into a select" antipattern AI assistants commonly emit. Use when adding a product picker meta box, a custom WC admin page selector, or any UI where the user must search and pick from many products. Triggers on wc-product-search, woocommerce_json_search_products, woocommerce_json_search_products_and_variations, selectWoo, wc-enhanced-select, "select2 products in WooCommerce", or product-picker meta box scaffolding.

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Handle UTF-8 and text encoding safely in WordPress plugins, especially on WP 6.9+ where wp_is_valid_utf8(), wp_scrub_utf8(), and noncharacter helpers replace older seems_utf8-style checks. Covers when to validate, scrub, reject, or preserve invalid bytes; wp_check_invalid_utf8 behavior; XML/JSON/feed/export boundaries; and avoiding data loss from premature replacement. Use when processing imported text, CSV, XML, feeds, email, REST payloads, AI prompts, logs, filenames, or external API data.

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AI-powered design intelligence with 67 UI styles, 161 color palettes, 57 font pairings, 99 UX guidelines, and 25 chart types across 15+ tech stacks. Generates complete design systems for any product type with industry-specific reasoning rules.

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