データ・AIのスキル

Reads a project or processing description and returns a DRAFT data protection impact assessment pack: processing description, necessity and proportionality questions, a risk table with blank rating cells, mitigations to consider and open questions. Never rates risk, determines the lawful basis or judges adequacy; the DPO assesses and signs. Works from descriptions, never personal data. Use when the user asks to "start a DPIA for the new monitoring tool", "draft a data protection impact assessment", "scaffold a DPIA from this processing description" or "what would the DPO need for a DPIA on this". Do not use for redacting or de-identifying a document, use document-deidentification-pass instead; do not use for working out what data an incident exposed, use data-incident-impact-brief instead. Drafts for human review; never approves, authorises or signs off.

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Extract structured data from receipts and invoices for bookkeeping, expense tracking, and tax preparation. Supports email, photos, scanned images, PDFs, and accounting exports. Outputs vendor, date, amount, tax, line items as table, CSV, or JSON. Trigger on "process receipts", "extract receipts from email", "scan invoices", "capture expenses".

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Convert a BMad skill into a downloadable web bundle (Gemini Gem + ChatGPT Custom GPT) with a persona, install instructions, and knowledge files. Use when a user wants to publish a skill to consumer LLM platforms (Gemini, ChatGPT).

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概念データモデルの新規作成・更新・レビューを支援する。業務上の概念(エンティティ)とその関連を Mermaid ER 図で表す D2 成果物で、論理 ER 図・テーブル定義(D3)の上流にあたる。PRD・ドメイン要求仕様書群の整備後、データ観点を整理する段階で呼び出す。

Diagnose or enable Session Cartographer semantic search in Codex, including least-privilege localhost access to local Qdrant and the embedding server. Use when setup, Qdrant health, localhost reachability, sandbox network denial, or semantic indexing is in question.

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。

Query PostHog product analytics via REST API — event analytics, HogQL SQL queries, feature flags, experiments, session recordings, insights, persons, cohorts. Use when the user wants to answer an analytics question, toggle/inspect a flag, or pull event data programmatically without opening the PostHog UI or installing the PostHog MCP.

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Query Sentry issues, events, releases, replays, and org/project metadata via REST API. Use when the user wants to diagnose a production error, pull stack traces, list recent issues, inspect a release, or fetch event data programmatically — prefer this over asking for UI screenshots or guessing from memory.

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。

Query and mutate Linear issues, projects, cycles, teams, workflow states, and comments via its GraphQL API. Use when the user wants to read or change Linear data programmatically — without the MCP server, and without hand-navigating the Linear UI.

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。

Operate Stripe's REST API — customers, payments (PaymentIntents / Charges), refunds, subscriptions, invoices, Checkout Sessions, products/prices, payouts, disputes. Use when the user wants to query or mutate Stripe data programmatically without the MCP server or the Dashboard.

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。

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.

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。

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.

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。

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.

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。

モデルに送るプロンプト面（system prompt / tool 記述・スキーマ / 注入ブロック / 副プロンプト）を 整理・変更するときに、前後で同じ物差しで計測してから完了とする手順。「プロンプト整理して」 「プロンプト削って」「system prompt の重さを見て」といった依頼で使う。ユーザーが /prompt-budget と入力したら使う。

ScalarDB Analytics設計エージェント - ScalarDB Analyticsを使用した分析基盤の設計。Apache Sparkベースの分析クエリ、マルチDB横断分析を策定。/design-scalardb-analytics [対象パス] で呼び出し。

Use when explaining or writing TBQ3 language syntax, including Params, Vars, Events, data types, variables, sequence variables, arrays, Map variables, control flow, operators, assignment, functions, and formula execution rules.

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。

Refresh WhatsApp text into an Obsidian vault (data layer, dashboard, group labels, contact notes). Text only, never downloads media, and pulls the recent window the live companion bridge exposes rather than a full multi-year archive. Semi-automatic by design: it drives the live bridge and needs the phone nearby. Triggers: "/whatsapp-sync", "pull whatsapp".

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- Research companies, directors, shareholders and ultimate beneficial ownership in official corporate registries, filings and offshore datasets — OpenCorporates, UK Companies House and the PSC register, SEC EDGAR, US Secretary of State registries, EU business registers, GLEIF LEI… Use when asked who owns or controls a company, to find a person's other directorships, or to unpick a group structure

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。

ПОДКЛЮЧИТЬ Telegram на ЭТОЙ машине — оба стека сразу: Telethon-рельса (роботы, 0 LLM) и MCP (живые сессии). Триггеры «/tg-connect», «/tg-login», «подключи телегу», «подключи телеграм на этой машине», «залогинь телегу», «телега отвалилась», «AuthKeyDuplicated», «перелогинь аккаунт <имя>», «настрой telethon и mcp», «connect telegram», «relogin telegram»

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。

Squeeze three to five durable lessons out of the owner's own words from the last seven days into a weekly note in the insights folder. The LLM reads only a collector's digest, never the raw corpus. Triggers: "/wisdom-distill", "distill my week", "weekly wisdom".

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Registry of reusable agent sessions and slot allocation: claim a free scheduled-task slot instead of creating a new session, set its prompt and fire time, and release it when done. Use when you need to spawn or reuse a visible background session.

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Weave a new node (concept, framework, theory, project, principle) into the whole vault graph rather than just creating a note. Mode A links one new node against the vault by top-K retrieval, with the LLM judging only those candidates; mode --deep finds orphaned islands and wires them in. Backup before edits, preview before writing. Triggers: "/relink", "integrate this concept".

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⭐ ПРАВИЛО (anton 23.09 голосом): «подними сессию/декомпозируй» адресовано ТЕБЕ = поднимай У СЕБЯ, своими средствами (Cursor → Task-tool/background agents, Codex → свои сессии, Claude → планировщик); нести задачу в другую LLM = ересь. Мост spawn_queue → Claude-планировщик — ТОЛЬКО когда нужна именно видимая scheduled-задача приложения. Триггеры: «подними сессии», «декомпозируй на сессии», lift-spawn.

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。

Пометить КАЖДУЮ сессию Claude Desktop (Code tab) ИКОНКОЙ её группы прямо в заголовке — «⚙️ Имя», «💰 Р+ Имя». Пока сайдбар-инструмент ccd_sidebar заперт серверным флагом (anthropics/claude-code#92621), иконка в имени = единственная видимая группировка. Триггеры "/session-groups", "/sg", "проставь группы сессиям", "разложи сессии по группам", "иконки сессий", "группы в заголовки", а также САМ на СТАРТЕ сессии, как только ясна тема (приказ Антона 10.09.2026: «мало пикселей на экране, нужна иконка»), и на /retro шаг 6a-кватер как перепроверка. Движок session_groups.py (0 LLM) строит план, переименовывает сессия через MCP set_session_title. НЕ путать с /sessions (что сейчас крутится) и /retro (закрытие).

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。

Add a 'Read with AI' widget under published content: a copy-the-prompt button plus deep links that open the material already loaded into an agent (Codex, ChatGPT, Claude). Triggers: /read-with-ai, read with AI buttons, add AI buttons, widget under the article.

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。