398 件 ・ 関連度順
概要と使いどころ
Orchestrates multi-step tasks autonomously using a 3-tier agent hierarchy (Director/Manager/Worker). Use when user says "run this end-to-end", "handle everything", "execute all tasks", or needs parallel task execution with queuing, course correction, and session resume. Provides FIFO task queue, escalation policy, git worktree isolation, and context persistence across agent sessions.
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 whenever several decisions are pending or have accumulated -- whether within a topic, project, document, or over the course of a session: inventory them, present a numbered briefing with options A/B/C/D and a marked recommendation, accept letter answers (including batches), record the results, and write them back into the source documents.
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。
Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy
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。
When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.
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。
Apply when tempted to ask 'should I do X?' on reversible work. Proceed, present the result, let the human course-correct after the fact; reserve confirmation for irreversible actions.
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。
Evaluate recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.
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。
Create custom external web service APIs for Moodle LMS. Use when implementing web services for course management, user tracking, quiz operations, or custom plugin functionality. Covers parameter validation, database operations, error handling, service registration, and Moodle coding standards.
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 Busabase-backed sandbox desk for scoring and triaging course-instructor ("讲师") candidates found on a recruiting-style platform. Use whenever the user invokes $kelly-instructor-sourcing or /kelly-instructor-sourcing, wants a lightweight instructor candidate tracker, needs to score sourcing-platform leads against a three-axis rubric (background endorsement, expertise depth/breadth, teaching-service ability) before reaching out, or wants to log a WeChat add without building a live-connected outreach tool. Three subcommands - setup, criteria, review - plus the desk itself. v1 is sandbox-only — every dataset is deterministic mock data, it never connects to a real sourcing-platform or messaging account, and it never sends a message or automates a WeChat add - that stays entirely human-performed outside the app.
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。
Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.
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 interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.
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。
Generate a professional certificate image with recipient name, course title, and completion date for digital sharing, social media, or email delivery.
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。
Generate a professional achievement certificate with recipient name, course details, date, and a QR code for formal download or print.
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。
会場別のコース適性を分析する。会場を省略すると全会場の成績を表示する。「コース分析」「会場別の適性を見たい」といった依頼で発動する。
Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.
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。
Analyzes pooled CRISPR screens with MAGeCK (Li et al 2014), covering count generation (mageck count), the RRA two-condition workflow (mageck test using alpha-RRA over per-sgRNA negative-binomial p-values), the MLE multi-condition workflow (mageck mle with explicit design matrix and beta-score output), normalization choice (median vs total vs control-sgRNA vs spike-in), sgRNA efficiency injection, paired-sample testing, time-course design, drug-screen versus dropout-screen design matrices, MAGeCKFlute and MAGeCK-VISPR downstream visualization, and decision logic for when to use MAGeCK vs JACKS / BAGEL2 / drugZ / Chronos. Use when running a fresh CRISPR screen analysis, picking RRA vs MLE for the experimental design, choosing a normalization method from QC signatures, debugging MLE convergence failure or NaN beta scores, comparing MAGeCK output across tools, or building a batch-aware multi-cell-line / multi-condition MLE design matrix.
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 OpenSpec backlog delivery — validate BACKLOG.md, plan TaskCards, orchestrate agents by phase, review gate, and update backlog 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。
Evaluate deliverable quality — scorecard, outcome tracking, regression checklist, and aggregate stats.
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。
CodeConductor pagespeed workflow
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 the API contract workflow for public interface changes, compatibility constraints, contract tests, documentation, and review.
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 durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.
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。
Maps incoming work to the CodeConductor slash command and workflow skill. Use when starting a session or deciding which /cc-* command applies.
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。
Performs simple mutation testing to verify test coverage and assertions.
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。
Guides the creation of complete Spring Boot features following a structured, layer-by-layer workflow: entity, repository, service, controller, and tests. Applies Kotlin idioms, Bean Validation, and MockK test patterns throughout.
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。
Provides expert knowledge of Spring Boot conventions, Kotlin idioms, and MVC patterns for backend API 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。