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概要と使いどころ
Multi-AI second opinion via OpenAI Codex CLI. Three modes: Review (pass/fail gate), Challenge (adversarial edge-case finder), Consult (freeform with session continuity). Read-only with streaming output and thinking traces. Cross-model analysis when review has already run.
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。
Pre-landing PR review with two-pass checklist. Pass 1 critical: SQL safety, race conditions, LLM trust boundaries, enum completeness. Pass 2 informational: side effects, magic numbers, dead code, test gaps. Adversarial review auto-scaled by diff size. Scope drift detection.
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。
Edit, validate, debug, publish, and inspect ReachAI Workflow drafts through the Workflow AI Coding REST API. Use when asked to create or modify a workflow graph, add/update/delete nodes or edges, validate GraphSpec, dry-run or debug-run a workflow, inspect trace/run output, check release readiness, publish a validated draft, or work on PAGE_ASSISTANT workflows from Cursor/Codex.
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 when the user has nothing — no traces, no labels, no eval set — and needs to build a v0 evaluation from scratch. Also use when the user says "I need to start evaluating my app but don't know where to begin," "I want to set up eval for a new product," or has just identified failure modes and needs to turn them into principles. Outputs a v0 grader in 30 minutes using OpenJudge SimpleRubricsGenerator, plus a roadmap to reach calibrated evaluation.
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 when the user wants to build an evaluation system for an LLM/agent application but doesn't know where to start — they have traces, prompts, RAG pipelines, or nothing at all. Also use when the user mentions evaluation, eval, benchmarking, testing LLM quality, measuring agent performance, assessing RAG accuracy, or wants to compare prompts/models. This skill is the entry router: it asks diagnostic questions then recommends which sub-skill (local workflow) to use next.
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 when the user needs to design evaluation datasets, create test cases, stratify samples, generate adversarial examples, extract eval dimensions from traces/specs, or build a labeled evaluation set. Also use when the user mentions test data design, eval coverage, difficulty stratification, synthetic data generation for eval, or "how to create good evaluation data." Outputs datasets in OpenJudge-compatible format.
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。
A jittery electric outline traces a card — an energetic accent for one hero element. One per view. Pure CSS; a static solid outline remains under prefers-reduced-motion.
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。
A soft progressive blur fades content out toward an edge — a premium "more below" affordance for a scrolling list/section. Keep the readable content above the blur. Degrades gracefully where backdrop-filter is unsupported.
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。
Rigorous multi-pass editor for law review articles, student notes, seminar papers and other legal scholarship. Runs six specialized passes — structure, substantive critique, Bluebook citations, grammar and clarity, fact-checking against sources, and a synthesizing memo — and delivers an editorial memo with issues prioritized as critical, substantial or minor and keyed to specific footnotes and paragraphs. Handles articles of any length, including 50,000-word pieces, by chunking on section boundaries. Reads .docx directly. Use when editing, critiquing, workshopping or pre-submission-reviewing academic legal writing. Triggers on "edit my article," "review this draft," "critique my note," "check my Bluebook citations," "is my argument sound," "read my law review piece," "workshop this paper," "pre-submission review." Chunking needs Python 3; fact-checking needs web search; both degrade gracefully without.
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。
Les LLM écrivent du juridique qui ressemble à du juridique sans en être. Formules creuses, attributions vagues, hedging systématique, latin décoratif : un praticien repère ces tics en trois lignes. Un juge aussi. LawyerScrib est un skill pour Claude Code et Cursor qui nettoie ces traces. Il scanne 17 patterns typiques de l'écriture IA appliquée au droit français (conclusions, consultations, notes, mails, actes) et réécrit chaque passage pour retrouver le ton d'un avocat qui argumente, pas d'un modèle qui rédige. Le résultat : un texte engagé, précis, avec des références sourcées et une position claire. Pas un texte neutre qui "reste à disposition pour tout complément".
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。
Argentine Supreme Court citation network analysis using JurisRank — a peer-reviewed PageRank algorithm with temporal decay for measuring jurisprudential authority. Ranks precedents by citation influence, traces doctrinal evolution, and detects constitutional drift. Published methodology: JCLLT (DOI: 10.47852/bonviewJCLLT62027951). Activate with: which cases to cite, rank precedents, case authority, doctrinal evolution, Argentine Supreme Court, CSJN jurisprudence, citation network, leading case, legal research Argentina.
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。
Expert debugging and profiling for leaks, GPU/Visual Profiler, headless CI QA, orphan nodes, thread-safe logs, and custom Debugger monitors — not print/breakpoint tutorials. Trigger on OBJECT_ORPHAN_NODE_COUNT, ObjectDB growth, Visual Profiler GPU spikes, flaky headless exits, or remote device consoles. Keywords: orphan nodes, Performance.get_monitor, Visual Profiler, Time.get_ticks_usec, EditorDebuggerPlugin, headless QA, push_error, backtrace.
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。
Expert debugging and profiling for leaks, GPU/Visual Profiler, headless CI QA, orphan nodes, thread-safe logs, and custom Debugger monitors — not print/breakpoint tutorials. Trigger on OBJECT_ORPHAN_NODE_COUNT, ObjectDB growth, Visual Profiler GPU spikes, flaky headless exits, or remote device consoles. Keywords: orphan nodes, Performance.get_monitor, Visual Profiler, Time.get_ticks_usec, EditorDebuggerPlugin, headless QA, push_error, backtrace.
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 Temps error tracking to applications using the Sentry-compatible SDK. Temps exposes a Sentry-compatible DSN that works with the official Sentry SDK for each language/framework — no code changes beyond initialization are required. Use when the user wants to: (1) Add error tracking to any app (React, Next.js, Vue, Svelte, Angular, Node.js, Python, Go, Rust, Ruby, Java, PHP, .NET, React Native, Flutter), (2) Wire up uncaught exception and unhandled promise rejection capture, (3) Configure session replay for errors, (4) Upload source maps for readable stack traces, (5) Report releases and environments, (6) Capture custom errors/messages. Triggers: "add error tracking", "add sentry", "track exceptions", "report errors", "temps error tracking", "wire up error monitoring".
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。
Best-practices reference for preparing and instrumenting applications on Temps. Covers the app runtime contract (`.temps.yaml` health, HOST/PORT, readiness, SIGTERM, replicas, migrations) and production observability (errors, traces, metrics, logs, analytics, privacy, sampling, cardinality, credential boundaries). Use whenever building or reviewing an app for Temps, configuring health checks, adding telemetry, diagnosing missing/noisy signals, or checking OTLP/Sentry/analytics ingestion. Triggers include "temps best practices", "prepare this app for Temps", ".temps.yaml health", "temps health check", "ignore health checks in otel", "temps observability", "wire up telemetry", and "instrument this app for temps". Prefer focused setup skills for a single SDK. Use temps-cli for executing deploy and resource-management commands.
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。
Swift 6.2 concurrency updates including default MainActor inference, @concurrent for background work, isolated conformances, and approachable concurrency migration. Use when adopting Swift 6.2 concurrency features or fixing data-race errors.
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。
Swift concurrency patterns including Swift 6.2 approachable concurrency, structured concurrency, actors, continuations, and migration. Use when reviewing or building async code, fixing data race errors, or migrating to Swift 6.
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 value-moment-first onboarding flows for iOS/macOS apps — the default architecture races a new user to the first felt experience of the app's promised outcome, branching on whether they can experience it right now or need to plan for later. The classic paged welcome-carousel tour is an explicit fallback for genuinely explain-first apps. Use when user wants to add onboarding, welcome screens, first-launch experience, or improve activation/trial conversion.
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 StoreKit 2 subscription lifecycle management — grace periods, billing retry, offer codes, win-back offers, upgrade/downgrade paths, and subscription status monitoring. Use when user needs post-purchase subscription state handling beyond the initial paywall.
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 an Apple-compliant account deletion flow with multi-step confirmation UI, optional data export, configurable grace period, Keychain cleanup, and server-side deletion request. Use when user needs account deletion, right-to-delete, or Apple App Review compliance for account removal.
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。
Expert knowledge for Azure Partner Solutions development including troubleshooting, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when integrating Confluent/MongoDB via Service Connector, managing Datadog/Dynatrace/Elastic/New Relic, or Palo Alto Cloud NGFW, and other Azure Partner Solutions related development tasks.
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。
One-shot Base-token investigation - runs any subset of six onchain-security checks (rug-scan, contract-audit, deployer-trace, holder-concentration, honeypot, lp-lock) into one verdict. Keyless core.
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。
Read and refresh wp-rocket's pre-built dependency graph at .claude/graph/dependency-graph.json. Use to locate a class file, trace dependencies, find the ServiceProvider that wires a service, or enumerate Subscribers in a module — without re-scanning the codebase from scratch. This skill is primarily a reader: the graph is built (and incrementally refreshed) by `node bin/build-knowledge-graph.js`. Invoke this skill at session start (to refresh if stale) and before grep/glob searches for class relationships.
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 completed task, browser flow, artifact pipeline, failure-recovery trace, or repeatedly refined workflow into a new reusable skill package or a reviewed skill-design plan. Use when the user asks to make a new skill from real run history, extract a reusable workflow from conversation/logs/files, summarize lessons into a new skill, or produce a plan before writing files. Do not use to upgrade an existing skill or to execute the business workflow itself.
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。