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概要と使いどころ
Mine Claude Code session logs for skill idea candidates. Use when running the weekly skill generation pipeline to extract, score, and backlog new skill ideas from recent coding sessions.
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Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism. Use when strategy_drafts/*.yaml exists and needs quality gate before pipeline export. Outputs PASS/REVISE/REJECT verdicts with confidence scores.
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Select the best MetaTrader 5 trading robots (Expert Advisors) that have not been backtested yet, by running the MT5 Strategy Tester from the command line through a 3-round pipeline. Use when the user wants to batch-test MT5 bots/EAs, screen robots across all symbols, optimize EA parameters, or move candidate bots to finalists based on profit, drawdown, positive months/years and equity-curve criteria. Runs terminal64.exe headless; Windows + MetaTrader 5 required at run time.
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Synthesize the three Jason Shapiro contrarian-pipeline verdicts (COT crowding, news-reaction failure, weekly price-action confirmation) into one actionable setup_status via a fail-closed precedence state machine. Pure, offline synthesis -- no network, no API keys, no computation beyond validation and precedence.
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Use when the user asks to "script this short video", "write a TikTok / Reels / Shorts script", "给这条抖音或视频号视频写脚本", or "fix the hook — viewers drop off in the first seconds"; produces timestamped beat-sheet scripts on the retention-gate model (0-2s hook / 2-5s confirmation / 5-15s payoff / loop-or-CTA) with per-scene script lines, on-screen text for muted viewing, asset keywords, and 9:16 format-param rows per platform norm card for TikTok, Reels, Shorts, 抖音, and 视频号 — plus 2-3 hook options from named hook families and an AI-content disclosure line by default on realistic synthetic media. Spec-only: rendering, TTS, and publishing stay with the user's own tools — no pipelines, no upload automation. Not for creator video briefs — use brief-generator; long-form video SEO belongs to content-writer. 短视频脚本/抖音分镜/开头钩子/竖屏9:16
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 asks to "write influencer outreach", "follow up with a creator", "pitch a journalist, hunter, or launch partner", or "negotiate partnership terms"; produces personalized pitches, multi-touch follow-up sequences, negotiation scripts with objection handling, and a status pipeline tracker — the shared outreach mechanics engine for creator, media/analyst, launch-partner, and social-selling / advocate-recruitment targets. Not for finalizing signed agreements — use contract-helper; not for media-list tiering, embargo terms, or press-release structure — use press-media-relations. 达人邀约建联/合作谈判话术
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Guide for upgrading Grails applications from Grails 7.x to Grails 8, covering Java 21, Groovy 5 name resolution and static compilation, Spring Boot 4.1, Spring Framework 7, dependency management, Micronaut, Jackson 3, Hibernate 7, TagLibs, testing, content negotiation, asset pipeline wildcard paths, and validation behavior changes
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SkillOpt-flavored offline training loop for any SKILL.md. Treats accumulated learn-rule corrections as training trajectories, proposes bounded patches via an optimizer LLM, gates each candidate against a held-out validation set built from the user's own past corrections, and ships only candidates that demonstrably improve the score. Inspired by Microsoft SkillOpt's ReflACT pipeline (rollout → reflect → aggregate → select → update → evaluate) adapted to pro-workflow's SQLite store. Use when a skill has accumulated 8+ learn-rule rows and the user wants the skill itself to get better, not just longer.
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Creates and automates custom image builds with EC2 Image Builder - Linux, Windows, and macOS AMIs, and container images to ECR. Covers the build IAM role, Amazon-managed and custom components, image recipes, infrastructure and distribution configuration (launch templates, SSM parameters, other Regions), one-off builds, recurring scheduled pipelines for golden AMI automation and OS patching, custom image workflows, and diagnosing failed builds. Applies when creating, automating, or scheduling AMI or container image builds with Image Builder, or when debugging a failed build. Not for launching instances from existing AMIs, AMI lifecycle/retirement, or general EC2 fleet management.
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Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses, failures, discrepancies. Covers Concurrent Agreements (CustomerAWSAccountId + LicenseArn), multi-product, CloudTrail Event History (90 days; never CloudTrail Lake), Seller Reports (Billed Revenue/Usage columns + CSV/SDDS parsing), existing-stack detection, metering region for BatchMeterUsage/MeterUsage (DisabledApiException), metered AMI/Container + IAM roles, where registration data lives (customer-profile table), legacy ProductCode + CustomerIdentifier, DuplicateRecord/CustomerNotSubscribed, bad LicenseArn. Also SCOPES adjacent asks — flat-rate/SaaS-Subscription "do I still meter", CCP included-units + overage, contract term/annual renewal, forecasting future bills/usage — with the right answer or a one-line redirect. Use for any BatchMeterUsage/ResolveCustomer or SaaS usage-billing question.
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Tests Amazon MWAA workflow execution end-to-end: trigger a run and monitor it to completion for Provisioned (Python DAG, via Airflow REST API) and Serverless (YAML workflow, via StartWorkflowRun). Verifies the artifact is deployed and parse-ready, triggers with confirmation, polls to terminal state, and on failure delegates diagnosis to debugging-mwaa-workflow and artifact/redeploy fixes to authoring-mwaa-workflow, then retests up to a capped number of attempts. Triggers on: test my DAG, test my workflow, run my DAG, trigger a test run, does my DAG work, smoke-test the pipeline, verify my workflow runs, execute my DAG to check it. Not applicable to writing or deploying a new workflow (handled by authoring-mwaa-workflow), or for diagnosing why a run failed or root-causing an error (handled by debugging-mwaa-workflow).
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Designs, reviews, and debugs DynamoDB data layers from design axioms — enumerates access patterns, chooses partition/sort keys and GSIs, decides single-table vs. multi-table, configures Streams, Global Tables, TTL, vector indexes for similarity search, and zero-ETL integrations to OpenSearch/Redshift/SageMaker Lakehouse, and produces a defensible data-layer design with a monthly cost estimate and optional live validation. Applies whenever a user is designing, reviewing, or refactoring anything backed by DynamoDB — schemas, access patterns, GSIs, single- vs. multi-table choices, Streams consumers, transactional outboxes, Global Tables, zero-ETL pipelines, or storing embeddings and running semantic/vector similarity search with SearchVectors on items already in DynamoDB — even when they don't say "axioms" or "design review." Also applies when debugging hot partitions, throttling, unbounded Scans, LWW conflicts, or surprise bills on DynamoDB workloads.
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Build and submit iOS and Android apps with EAS to TestFlight, the App Store, or Google Play. Supports Expo and other React Native projects, plus existing native apps. Use for eas.json setup, release pipelines, signing, app versions and build numbers, store submissions, and listing metadata. For Expo websites and API routes, use eas-hosting; for adding React Native screens to a native app, use expo-brownfield.
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。
Helps understand and write EAS workflow YAML files for Expo projects. Use this skill when the user asks about CI/CD or workflows in an Expo or EAS context, mentions .eas/workflows/, or wants help with EAS build pipelines or deployment automation.
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。
Analyze and design an AssemblyAI architecture spanning pre-recorded jobs, Streaming v3, LLM Gateway, callbacks, queues, retention, and audit evidence. Use when performing system design or review. Trigger with "AssemblyAI architecture" or "design AssemblyAI pipeline".
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。
Implement Apollo.io webhook and event-driven integrations. Use when receiving Apollo notifications, syncing data on changes, or building event-driven pipelines from Apollo activity. Trigger with phrases like "apollo webhooks", "apollo events", "apollo notifications", "apollo webhook handler", "apollo triggers".
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。
Configure CI/CD pipeline for AppFolio property management integrations. Trigger: "appfolio CI".
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。
Production-grade architecture patterns for Apify-powered applications. Use when designing scraping infrastructure, building multi-Actor pipelines, or integrating Apify into a larger system architecture. Trigger with "apify architecture", "apify best practices", "apify project structure", "scraping architecture", "apify system design".
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。
Deploy Apify Actors and integrate scraping into external applications. Use when deploying an Actor to the platform, integrating Actor results into a web app (Next.js, Express), wiring webhooks, or scheduling scraping pipelines. Trigger with "deploy apify actor", "apify Vercel integration", "apify production deploy", "integrate apify results", "apify API endpoint".
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。
Implement reference architecture for Anima design-to-code automation. Use when designing a design system automation pipeline, structuring a Figma-to-React project, or planning team-scale design handoff. Trigger with: "anima architecture", "design-to-code architecture", "anima project structure", "figma automation architecture".
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。
Configure CI/CD pipeline for automated Figma-to-code generation with Anima. Use when automating design-to-code in GitHub Actions, setting up PR-based component generation, or integrating Anima into design handoff workflows. Trigger with: "anima CI", "anima GitHub Actions", "anima automated generation".
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 production-ready patterns for the Anima SDK design-to-code pipeline. Use when building reusable Anima client wrappers, implementing output caching, or establishing team standards for design-to-code automation. Trigger with: "anima SDK patterns", "anima best practices", "anima code patterns".
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。
Production readiness checklist for Anima design-to-code pipelines. Use when deploying automated design-to-code services, preparing CI/CD Figma-to-code automation, or validating output quality before production. Trigger with: "anima production", "anima go-live", "anima prod 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。
Use Figma webhooks to trigger automatic Anima code generation on design changes. Use when building event-driven design-to-code pipelines, auto-generating components when Figma files change, or integrating design updates into CI. Trigger with: "anima webhook", "figma webhook", "anima auto-generate on change".
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。