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概要と使いどころ
ファーストクラスコレクションパターンの設計・実装を支援。コレクションをラップする専用クラスの 設計、ドメインロジックの集約、不変性の確保をガイド。コードレビュー、新規実装、リファクタリング 時にコレクション操作ロジックが散在している場合に使用。 対象言語: Java, Kotlin, Scala, TypeScript, Python, Ruby, Go, Rust。 トリガー：「コレクションをラップしたい」「リストのロジックを集約」「ファーストクラスコレクション」 「コレクション操作が散在」「List<Order>をOrdersクラスに」といったコレクション設計関連リクエストで起動。
Use when fixing HustleXP revenue collection bugs including Stripe platform fee not being collected (application_fee_amount missing), escrow fee miscalculation using task.price instead of escrow.amount, self-insurance pool never funded, tip platform cut absent, subscription renewal revenue not logged, or XP tax path unreachable. Covers all platform fee issues and financial invariant checks.
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。
This skill should be used when the user asks about "production management", "film budget", "scheduling", "crew management", "location logistics", "risk assessment", "act as a production manager", "production manager mode", "line producing", "production budget", "crew roles", "film insurance", "production timeline", "location permit", "production paperwork", or needs expertise in film budgets, production scheduling, crew management, location logistics, and risk mitigation for film projects. Part of the AlterLab FC Skills collection (Cinema & Digital Media department).
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 a compromise assessment — hunting scope, methodology, and evidence collection. Use when asked "are we compromised", "run a compromise assessment", or "scope a threat hunt".
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。
View modes, row selection, mass actions, sorting, filters, search and table patterns. Use when designing data tables, listings, file browsers or any collection.
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。
Batch download academic paper full-text (PDF/XML) from a list of DOIs. Handles 25 DOI prefixes across 19 publisher families via three layered routes: (1) publisher TDM APIs requiring institutional subscription (Elsevier ScienceDirect, Wiley Online, Springer Nature), (2) Open Access sources (Crossref, Unpaywall, OpenAlex), and (3) a browser-based fallback for paywalled publishers without TDM access (ACS, RSC, IEEE, AIP, IOP, APS, Annual Reviews, T&F, Chinese journals). Browser fallback offers two routes — Route A drives the user's logged-in Chrome via the OpenClaw `browser` tool with `profile="user"` (best for interactive sessions), Route B uses the standalone `auto-paper-harvester` CLI with its built-in Playwright (best for unattended bulk runs). Use when the user wants to harvest, scrape, fetch, or bulk-download papers from a DOI list, savedrecs export, or Excel; or wants to fill missing full-text PDFs for an existing literature collection. Triggers on phrases like "批量下载文献", "下载全文", "harvest papers", "scrape full text", "TDM API", "下载 Elsevier 全文", "Wiley 批量下载", "下载 PDF".
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。
Creates, supersedes and validates decision records (ADRs) against the convention a collection already follows, instead of imposing a published one. Use when the user wants to record a decision, write an ADR, supersede an existing decision, audit or lint a decisions folder, check that an ADR index is in sync, or asks "why did we decide X". Deduces the filename scheme, section set and status vocabulary from the records already there; ships a validator with an exit code, so the audit is a check and not an opinion.
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。
Curated collection of ready-to-use Claude Code hook recipes for safety, automation, formatting, logging, and context injection. Use when configuring hooks, setting up safety guards, automating workflows, or when user mentions 'hooks', 'PreToolUse', 'PostToolUse', 'guard', 'automation', 'claude hooks'.
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。
Systems programming from memory management through networking. Covers memory models (stack vs heap, manual allocation, garbage collection, ownership/borrowing), concurrency (threads, mutexes, channels, async/await, actor model, data races vs race conditions), operating system concepts (processes, virtual memory, page tables, system calls, file descriptors, signals), compilation (lexing, parsing, code generation, linking, static vs dynamic libraries), networking fundamentals (TCP/IP, sockets, HTTP, DNS, TLS), and the hardware-software boundary (caches, cache lines, false sharing, memory-mapped I/O). Use when working with low-level code, diagnosing system-level bugs, understanding performance characteristics, or bridging between high-level languages and machine behavior.
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。
OpenStack monitoring operations skill for deploying, configuring, and operating the cloud health monitoring stack. Covers Prometheus metric collection and scrape targets, Grafana dashboard provisioning and visualization, Alertmanager notification channels and routing, alerting rules for service health and resource exhaustion, service endpoint health checks, log aggregation strategies, SLA tracking with availability and response time percentiles, and capacity trend analysis from historical metrics. Use when deploying monitoring via Kolla-Ansible, configuring alert thresholds, troubleshooting blank dashboards, tuning noisy alerts, or analyzing cloud performance trends.
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。
Runs the description-drift experiment — spawns all Claude Code agents simultaneously to collect self-reported capabilities, then compares them against static frontmatter descriptions to reveal how reliable orchestrator routing based on descriptions actually is. Use when measuring description drift across the agent fleet, re-running the capability collection experiment, analyzing a specific agent's self-reported capabilities, or auditing whether frontmatter descriptions accurately reflect agent behavior.
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, improve, or audit Vapi voice agent and Squad system prompts for production phone and web based voice agents. Use when the user wants help designing a Vapi assistant prompt, multi-assistant Squad prompt set, refining an existing prompt, creating prompt sections, building an intake or handoff workflow, improving tool-use instructions, adding guardrails, or optimizing voice-agent behavior for brevity, turn-taking, error handling, caller data collection, escalation, handoffs, and spoken formatting.
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。
Audits a methods section against a 45-item reporting checklist synthesized from the APSA Experimental Section rubric, JARS-Quant, CONSORT, and DA-RT, covering pre-registration, recruitment, randomization and treatments, sample flow and attrition, sample-size justification, three-tier results labeling, conjoint reporting, validity, and open-science infrastructure. Use when checking whether a methods section reports enough, preparing a submission or replication archive, asking what CONSORT, JARS, or DA-RT require, or documenting a deviation from a pre-analysis plan. Writing that plan before data collection goes to pre-registration-writing.
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。
Writes or reviews a pre-analysis plan before data collection: registry choice (OSF, AEA, AsPredicted, registered reports), locked models and decision rules, code run on simulated data, contingencies, and deviation records. Use when drafting or auditing a pre-registration or PAP, choosing a registry, or handling a deviation.
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 .NET types for performance. Seal classes, use readonly structs, prefer static pure functions, avoid premature enumeration, and choose the right collection types.
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。
Entity Framework Core best practices including NoTracking by default, query splitting for navigation collections, migration management, dedicated migration services, and common pitfalls to avoid.
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。
Organize DI registrations using IServiceCollection extension methods. Group related services into composable Add* methods for clean Program.cs and reusable configuration in tests.
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 and push reusable skills to SkillNote when repeated instructions are detected or user says "create a skill", "save this pattern", "push a skill". Guides drafting, review, collection selection, and publishing.
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 and push reusable skills to SkillNote from Codex when repeated instructions are detected or the user says "create a skill", "save this pattern", "push a skill". Guides drafting, review, collection selection, and publishing.
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。
Launch and collect independent Codex sessions (gpt-6-luna at high, xhigh or max; gpt-6.1-sol at low to xhigh) for bounded parallel work, from Claude Code or from Codex: one manifest, one detached launcher, one report a session, a drain while it runs, and a retry of the sessions that ended without a report. Owns the Codex transport when another skill sets the questions, as whole-run-investigation does for its lanes. Use when the operator asks for Luna or Sol sessions, a swarm, many sessions, a reasoning effort, a Codex subagent from Claude Code, or a later collection of reports. Tell a request to launch from one to wait and collect.
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。
Bruno is an open-source, offline-first API client that stores collections as plain-text .bru files on your filesystem. It serves as a privacy-focused, git-friendly alternative to Postman and Insomnia with no cloud sync and no account required.
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。
Manage and tag music libraries with beets, the Python-based CLI tool that auto-tags audio files using MusicBrainz metadata. Import, organize, deduplicate, and query your music collection with a powerful plugin system and flexible query language.
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。
The official AWS Labs MCP server collection provides AI agents with structured access to AWS documentation, service APIs, billing data, and infrastructure metadata through the Model Context Protocol, built and maintained by AWS for secure cloud automation workflows.
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。
Generates and validates Ansible playbooks from infrastructure requirements. Uses ansible-lint for validation and queries Ansible Galaxy API for discovering certified roles and collections.
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。