61 件 ・ 関連度順
概要と使いどころ
Answer a question about money that already moved in Stripe — why a charge failed, what a customer was billed, where an invoice or payout stands — by reading the object chain instead of guessing from a dashboard total. Use when the user pastes a Stripe id, asks why a payment failed, asks what a customer is paying, or wants revenue, invoice, or subscription state.
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。
Root-cause a production error with Sentry's evidence before touching code — pull the issue, read the stack trace and breadcrumbs, and separate the crash from its trigger. Use when the user pastes a Sentry link or issue ID, reports a production error, or asks why something is crashing for users.
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。
Turn a meeting into work — read its Granola notes, extract the commitments that belong to this user, and carry each one out or draft it (a code change, a ticket, a reply) with a trace back to the note. Use when the user says "do the follow-ups from", "implement what we agreed", "make tickets from", or points at a meeting after a sync, planning session, or customer call.
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。
Apache Superset is a widely adopted open-source BI platform for SQL exploration, chart building, and dashboard delivery. This skill is useful when an agent needs to query warehouse data, assemble dashboards, or explain metrics using a mature analytics interface instead of ad hoc notebook code.
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。
Run a two-agent independent review/redteam followed by peer collaboration to produce a consensus superset of findings and enumerated revision requests. Use when Codex 5.5 and Claude Opus 4.7 should first critique a matter independently, then exchange work, synthesize the best combined analysis, and finish with a single agreed revision list.
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。
Data Analyst IA — Expert en analyse de données (SQL, BI dashboards, Metabase, Superset, reporting, KPIs)
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。
Claude Codeのセッション終了時に、エラー解決や修正から再利用できる手順を抽出・保存する旧版スキル。現在は非推奨で、既存環境の互換性確認や仕組みの参照向けです。
Deep-research a topic end to end and produce a permanent, reusable knowledge asset: archive every primary source verbatim (gated by the user's privacy/retention posture), write one 1:1 summary per source, then synthesize a single self-contained compendium page. Depth is a dial (base synthesis → grounded primaries → books + counter-canon → saturation), each level an idempotent superset of the one below. Distinct from data-research (structured trackers) and perplexity-research (web deltas): this produces prose knowledge synthesis backed by an archived source corpus.
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 Quarkdown (.qd) documents, a Markdown-superset typesetting language that compiles to HTML, PDF, or plaintext. Use when the user wants to write or edit .qd files, produce typeset output (articles, reports, slides, books, wikis, notes, static sites) beyond what plain Markdown offers, or share structured plans in a presentation-ready format. Quarkdown adds function calls (`.func {arg}`), variables, layouts, math, diagrams, and document types (plain/paged/slides/docs).
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。
UnoCSS instant atomic CSS engine, superset of Tailwind CSS. Use when configuring UnoCSS, writing utility rules, shortcuts, or working with presets like Wind, Icons, Attributify.
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。
VictoriaMetrics provider for obz. Covers all 6 metric commands (query, list, info, labels, label-values, series) using MetricsQL, a PromQL superset with extensions like keep_metric_names and range_normalize. This skill should be used when the user mentions "VictoriaMetrics", "MetricsQL", "obz metric -p vm", or needs to query metrics from a VM backend.
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。
Unistyles 3.0 styling - C++ powered StyleSheet superset with zero re-renders, theming, breakpoints, variants, dynamic functions, runtime values
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。
[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1; route continuous learning, session learning, and pattern extraction requests to continuous-learning-v2.
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。