「ops」の検索結果

Router for Convex static-hosting deploy requests. Prefer deploydev for /deploydev and deployprod for /deployprod.

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 deciding WHERE to do work on Syntropic137 itself - "run this through Syntropic", "dispatch a workflow", "should this go in a workspace or local", "kick off a run on the Mini", "dogfood this", "build Syntropic inside Syntropic", "why did the agent's push fail", "can an agent run our QA", "the execution says completed but nothing shipped". Covers what a workspace agent can and cannot do, why `.github/workflows` pushes must come from the local machine, how to write a task prompt that does not repeat a known failure, and how to verify a run actually delivered. Do NOT use for PR/release mechanics (see `devops`), for using the `syn` CLI as an end user (see the syntropic137 plugin skills), or for authoring workflow YAML.

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 asked to report the deployment sentinel value. Provides the sentinel string that proves a vendored skill reached the agent's context.

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 for pull-request, merge, version and release mechanics in the Syntropic137 repo, and for CI or release-pipeline failures. Trigger phrases include "open a PR", "submit my changes", "address the review comments", "Copilot left comments", "merge this PR", "push this nit straight to main", "CI is red", "the release gate failed", "smoke test broke", "why is this PR BLOCKED", "bump the version", "cut a release", "release v1.x", "write the release notes", "main -> release PR", "approve the release gate", "the release published a bad asset", "triage the open PRs", "PR backlog", "which PRs are ready to merge", "merge order", "DORA metrics", "deploy frequency", "lead time", "change failure rate", "time to restore", "why didn't the issue auto-close". Covers trunk-based `main`, the `release` branch, local gates (`just qa-ci`, `just preflight`), GitHub Actions gates, review and merge policy, and post-release verification. Do NOT use for deciding what to dispatch, running the orchestrator loop, or deciding when to deploy a beta or run a pit stop (see `orchestrating`); for whether a task belongs in a workspace or locally (see `dogfooding`); for using the `syn` CLI as an end user (see the syntropic137 plugin skills).

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: analysing a project's architecture, structure, and infrastructure health from the System perspective.

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: analysing a project's delivery health — CI/CD, commit patterns, and working tree 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。

Use when: assessing how much context a deployed agent profile consumes before real work starts.

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。

Convergence loop that iteratively improves work until quality thresholds are met. Use when: (1) "refine this", "make this better", "iterate on this", (2) After /analyst gives a REVISE verdict, (3) Output quality is below 8/10, (4) "run the refinery loop on this". Reads analyst reviews from system/reviews/. Generates, scores, diagnoses, rewrites, re-scores. Stops when all dimensions >= 8/10 or diminishing returns detected. Outputs to system/refinery-log.md.

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 creating new skills, editing existing skills, or verifying skills work before deployment

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 deploying to Vercel with Next.js Use when: vercel, deploy, deployment, hosting, production.

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。

Upstash QStash expert for serverless message queues, scheduled jobs, and reliable HTTP-based task delivery without managing infrastructure. Use when: qstash, upstash queue, serverless cron, scheduled http, message queue serverless.

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 in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. Use when: voice ai, voice agent, speech to text, text to speech, realtime voice.

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。

Server management principles and decision-making. Process management, monitoring strategy, and scaling decisions. Teaches thinking, not 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。

Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub.

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 in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm 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。

Integrate MercadoPago Checkout Pro (redirect-based) into Next.js applications with any PostgreSQL database (Supabase, AWS RDS, Neon, PlanetScale, self-hosted, Prisma, Drizzle, or raw pg). Use when the user needs to: (1) Add MercadoPago payment processing to a Next.js app, (2) Create a checkout flow with MercadoPago, (3) Set up payment webhooks for MercadoPago, (4) Build payment success/failure pages, (5) Create a shopping cart with payment integration, (6) Troubleshoot MercadoPago integration issues (auto_return errors, webhook failures, hydration mismatches, double submissions). Triggers on requests mentioning MercadoPago, Mercado Pago, payment integration with MP, Argentine/Latin American payment processing, or checkout with MercadoPago. Supports all MercadoPago countries: Argentina (ARS), Brazil (BRL), Mexico (MXN), Colombia (COP), Chile (CLP), Peru (PEN), Uruguay (UYU).

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-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

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 at handling file uploads and cloud storage. Covers S3, Cloudflare R2, presigned URLs, multipart uploads, and image optimization. Knows how to handle large files without blocking. Use when: file upload, S3, R2, presigned URL, multipart.

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。

Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.

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 deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.

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 patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models. Use when: azure function, azure functions, durable functions, azure serverless, function 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。

Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.

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。

Master of defensive Bash scripting for production automation, CI/CD pipelines, and system utilities. Expert in safe, portable, and testable shell scripts.

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。

Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.

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。