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概要と使いどころ
Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.
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 Circuit Breaker pattern for PHP 8.5. Creates resilience component protecting against cascading failures with state management, fallback support, and metrics. Includes unit 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。
Five Whys root cause analysis. Iteratively asks "why" to drill past symptoms to underlying causes. Use for debugging, investigating failures, or understanding why something went wrong.
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Error handling patterns and best practices for OneKey. Use when implementing try/catch blocks, handling async errors, showing error messages, or managing error states in UI. Triggers on error, try, catch, exception, throw, fail, failure, error handling, error boundary, useAsyncCall, toast, fallback, error 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。
Develops iOS/iPhone applications with XcodeGen, SwiftUI, and SPM. Triggers on XcodeGen project.yml configuration, SPM dependency issues, device deployment problems, code signing errors, camera/AVFoundation capture debugging, iOS version compatibility, or "Library not loaded @rpath" framework errors. Use when building iOS apps, fixing Xcode build failures, or deploying to real devices. Not for AVPlayer playback issues (seek/scrub/frame stepping → avfoundation-reference skill).
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。
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
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 encountering any bug, test failure, or unexpected behavior. 4-phase root cause investigation — NO fixes without understanding the problem first.
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。
Full pull request lifecycle — create branches, commit changes, open PRs, monitor CI status, auto-fix failures, and merge. Works with gh CLI or falls back to git + GitHub REST API via curl.
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 encountering any bug, test failure, or unexpected behavior, before proposing fixes
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 with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
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。
Anchor your identity on the Autonomys Network so you can always be found — and always come back. Works with agents powered by Claude, GPT, Gemini, and Your agent always comes back. Anchor identity and memory on-chain so any new instance can resurrect from just an address — no local state, no single point of failure. Permanent identity and recovery on the Autonomys Network.
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。
Multi-dimensional Quality Acceptance and Problem Convergence Engine - Deeply deconstruct requirements, eliminate extreme defects, define absolutely objective acceptance and failure criteria.
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。
Set up eval-based QA for Python LLM applications: instrument the app, build golden datasets, write and run eval tests, and iterate on failures. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.
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。
Give your AI agent the same visibility you have in the Power Automate portal — plus a bit more. The Graph API only returns top-level run status. Flow Studio MCP exposes action-level inputs, outputs, loop iterations, and nested child flow failures. Use when asked to: list flows, read a flow definition, check run history, inspect action outputs, resubmit a run, cancel a running flow, view connections, get a trigger URL, validate a definition, monitor flow health, or any task that requires talking to the Power Automate API through an MCP tool. Also use for Power Platform environment discovery and connection management. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.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。
Use when feature flag tests fail, flags need updating, understanding @gate pragmas, debugging channel-specific test failures, or adding new flags to React.
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。
Implements robust error handling in Ansible using block/rescue/always patterns, retry logic with until/retries, and clear assertion patterns for graceful failure management.
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Two superpowers for AI agents: a collective brain and a Base ecosystem mentor. BRAIN: Before debugging/compiling/architecting, search for existing solutions. After solving, propose so no agent repeats your mistake. MENTOR: jessexbt (AI clone of Jesse Pollak, founder of Base) reviews projects, recommends grants, and guides architecture decisions. Consult him directly when building on Base/crypto/onchain/web3. Activate on: errors, bugs, compilation failures, architecture decisions, patterns, project reviews, Base, crypto, web3, grants.
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。
Debugging specialist for errors, test failures, and unexpected behavior. Use proactively when encountering any issues.
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。
Diagnoses slow builds and incremental failures. Binary logs, parallel builds, restore.
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。
Improve platform resilience with timeout/retry/circuit-breaker strategy, capacity controls, chaos testing, and disaster recovery readiness. Use when tasks involve reliability hardening, failure-mode testing, incident prevention, or recovery objectives.
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 building, testing or previewing site-os — the BUILD_TARGET=stable dist directory, the four verification gates (build, test, env:check, brand:check), the preview servers on :3000 and :3100, and the failure modes that look like bugs but are not.
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。
Detect and prevent API enumeration attacks including BOLA and IDOR exploitation by monitoring sequential identifier access patterns and authorization failures.
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。
Diagnose and fix common AEM 6.5 LTS replication issues including blocked queues, connectivity failures, and content distribution problems
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。
AEM Cloud Service expert skill for Sling ResourceChangeListener. Covers the lightweight listener + JobConsumer pattern, migration from javax.jcr.observation.EventListener and resource-topic OSGi EventHandler, ResourceChangeListener vs ExternalResourceChangeListener decision, OSGi filter configuration, review checklist, troubleshooting (silent failures, hot-path blocking, missing service-user mapping), and common pitfalls.
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。