クラウド、CI/CD、監視、デプロイ（7,253 件）
Audit one bounded Proto UI deployment or publication evidence slice against an exact revision and delivery surface. Use to verify revision identity, environment result, artifacts, and observable health. Do not deploy, promote, roll back, publish, release, or change environment protection.
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 one bounded Proto UI Actions or CI failure from an exact workflow run and revision, then route the exact repair, validation, or recheck transition. Use to locate the owning failure and distinguish infrastructure from change failures. This leaf remains read-only.
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 project and generate Docker configuration: Dockerfile (multi-stage dev/prod), compose.yml, compose.override.yml (dev), compose.production.yml (hardened), and .dockerignore. Includes production security audit. Use when user says "dockerize", "add docker", "docker compose", "containerize", or "setup docker".
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 Odylith Discipline pressure behavior, zero-credit hard laws, host/lane parity, or benchmark-proved learning-spine contracts need validation.
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 a user wants to deploy ClickHouse to the cloud, go to production, use ClickHouse Cloud, host a managed ClickHouse service, or migrate from a local ClickHouse setup to ClickHouse Cloud.
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。
Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal. For ClickHouse Cloud analytics, use the configured direct ClickHouse Query API endpoint with per-user CH_API_KEY and CH_API_SECRET credentials; do not use clickhousectl cloud service query. For local or host/port servers, use clickhousectl local client. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see Scope).
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 tabular data (pandas DataFrame, parquet, csv, Arrow, json) and wants to filter, group, aggregate, join, or speed up slow pandas. Provides chDB DataStore - same pandas API, ClickHouse engine underneath. Also handles reading from S3, MySQL, PostgreSQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake as DataFrames and joining across sources. TRIGGER when: user mentions DataFrame, parquet, csv, "fast pandas", "speed up pandas", or cross-source DataFrame joins; user imports `chdb.datastore` or `from datastore import DataStore`. SKIP this skill for raw SQL syntax (use chdb-sql instead), ClickHouse server administration, or non-Python DataStore API work.
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 and build LLM-powered projects from ideation through deployment. Use when starting new agent projects, choosing between LLM and traditional approaches, or structuring batch processing pipelines.
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。
SurrealDB Surrealism WASM extension development. Write Rust functions, compile to WASM, deploy as database modules. Part of the surreal-skills 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。
Fix Node.js CLI tools crashing inside Docker containers when host-installed node_modules require a newer Node version than the container provides. Use when: (1) "SyntaxError: Invalid regular expression flags" with /v flag in string-width or similar packages, (2) node_modules installed on host with Node 20+ but container has Node 18, (3) `npm install` with file: protocol creates symlinks that break inside Docker, (4) pnpm workspace packages become broken symlinks in containers. Covers version detection, Node binary mounting, and npm install strategies for cross-version compatibility.
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。
Fix docker exec hanging when starting background processes (servers, daemons) inside containers. Use when: (1) docker exec never returns despite using & or nohup, (2) background server started in container causes docker exec to hang indefinitely, (3) env_startup_command in SWE-bench or similar frameworks times out, (4) setsid/disown needed for proper process detachment in Docker. Root cause: docker exec tracks ALL processes in the exec session, not just the top-level PID.
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。
Fix RFDB V2 graph data silently not persisting to disk after analysis. Use when: (1) rfdb-server reports "0 nodes, 0 edges" on restart despite successful analysis, (2) segment directories exist but are empty (no .bin files), (3) manifest_index.json shows total_nodes: 0 despite analysis logging 70k+ nodes, (4) Docker builds produce empty graph databases, (5) --clear flag used before analyze command. Root cause: GraphEngineV2::clear() replaces the store with MultiShardStore::ephemeral() which has path: None, causing all flush operations to write to in-memory buffers only.
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。
Evaluates fresher-specific hiring signals that generic resume tools ignore. Scores 9 dimensions critical for new-grad hiring (CGPA, DSA, project depth, GitHub quality, deployment evidence, etc.) and identifies the weakest signal with improvement recommendations.
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。
Evaluate new-grad hiring evidence across education, DSA, projects, repositories, deployment, internships, and role alignment without inventing a universal fresher score.
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。
Query Ayunis deployed-environment telemetry in AppSignal — incidents, occurrence counts and error traces via the `appsignal-cli` binary; structured log attributes (user.id, org.id, nestjs.context, custom metadata) via the v2 logs API. Use when investigating a production/staging incident or log data — NOT for local dev logs (see backend-debugging).
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。
Start, stop, and manage the local dev stack (Docker infra, backend, frontend). Works in any directory — worktree or main repo.
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 AI performance monitoring. TRIGGERS - Use when user needs help with ai-performance-monitor related 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。
Deploy AI models to mobile applications. TRIGGERS - Use when user needs help with ai-mobile-deployment related 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。
Set up observability for AI systems. TRIGGERS - Use when user needs help with ai-observability-setup related 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。
Build AI monitoring systems with drift detection. TRIGGERS - Use when user needs help with ai-monitoring-system related 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。
Design model serving infrastructure for AI. TRIGGERS - Use when user needs help with ai-model-serving related 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。
Create AI governance policies for responsible development and deployment. TRIGGERS - Use when user needs help with ai-governance-policy related 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。
Deploy AI models to edge devices. TRIGGERS - Use when user needs help with ai-edge-deployment related 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。
Design AI model deployment strategies with rollout. TRIGGERS - Use when user needs help with ai-deployment-strategy related 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。