1,146 件 ・ 関連度順
概要と使いどころ
OpenSearch provider for obz. Supports log search and trace operations using Lucene-based query syntax. Requires --index flag. This skill should be used when the user mentions "OpenSearch", "obz -p os", or needs to search logs or traces from an OpenSearch cluster.
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。
Grafana Mimir provider for obz. Covers all 6 metric commands using standard PromQL. Mimir is a horizontally-scalable Prometheus-compatible TSDB. This skill should be used when the user mentions "Mimir", "Grafana Mimir", "obz metric -p mimir", or needs to query metrics from a Mimir cluster.
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。
VictoriaMetrics provider for obz. Covers all 6 metric commands (query, list, info, labels, label-values, series) using MetricsQL, a PromQL superset with extensions like keep_metric_names and range_normalize. This skill should be used when the user mentions "VictoriaMetrics", "MetricsQL", "obz metric -p vm", or needs to query metrics from a VM backend.
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。
Jaeger provider for obz. Covers trace search, trace retrieval by ID, and extension commands for service and operation discovery. This skill should be used when the user mentions "Jaeger", "obz trace -p jg", or needs to search distributed traces from a Jaeger backend.
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。
VictoriaLogs provider for obz. Supports log search using LogsQL, a purpose-built query language with _msg, _time, and _stream filters plus pipes for transformation. This skill should be used when the user mentions "VictoriaLogs", "LogsQL", "obz log search -p vl", or needs to search logs from a VL backend.
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。
Grafana Tempo provider for obz. Covers trace search, trace retrieval by ID, and extension commands for tag discovery. This skill should be used when the user mentions "Tempo", "Grafana Tempo", "TraceQL", "obz trace -p tempo", or needs to search traces from a Tempo backend.
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-backend observability CLI for querying metrics, logs, and traces across 12 backends. This skill should be used when the user runs obz commands, constructs metric/log/trace queries, configures providers, parses obz JSON output, or troubleshoots obz errors. Covers all core commands (metric query/list/info/labels/label-values/series, log search, trace search/get), global flags, time formats, output modes, config files, and exit codes.
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。
Grafana Loki provider for obz. Covers log search using LogQL, a label-based query language for log aggregation. This skill should be used when the user mentions "Loki", "Grafana Loki", "LogQL", "obz log search -p loki", or needs to search logs from a Loki instance.
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。
GreptimeDB provider for obz. Covers PromQL metric query, labels, label-values, and series commands via GreptimeDB's Prometheus-compatible API. Use this skill when the user mentions "GreptimeDB", "Greptime", "obz metric -p greptimedb", or needs to query metrics stored in a GreptimeDB instance.
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。
VictoriaTraces provider for obz. Covers trace search, trace retrieval by ID, and extension commands for service and operation discovery via the Jaeger-compatible HTTP API. This skill should be used when the user mentions "VictoriaTraces", "obz trace -p vt", or needs to search distributed traces from a VT backend.
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。
Elasticsearch provider for obz. Supports log search and trace operations using Elasticsearch Query DSL (Lucene-based). Requires --index flag. This skill should be used when the user mentions "Elasticsearch", "obz -p es", or needs to search logs or traces from an Elasticsearch cluster.
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, migrating, or debugging Agent Evals on Inngest: scoring AI agent or workflow outcomes, deferred scorers, sessions, traces, step experiments, experiment variant attribution, Insights queries, or production eval loops for prompts, models, tools, providers, and agent behavior. Covers TypeScript SDK v4 scoring beta APIs, `scoreMiddleware`, `step.score`, `inngest.score`, `createScorer`, `defer`, `group.experiment`, `experimentRef`, `meta.sessions`, and when to use durable workflow primitives for outcome-based 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 building durable AI agents or agentic workflows with Inngest and AgentKit, including model calls, tool calls, multi-agent networks, human approval, realtime progress, provider rate limits, crash-safe execution, and Agent Evals handoff. Covers AgentKit, `step.ai`, `step.run`, `step.waitForEvent`, native realtime, and when to use lower-level Inngest primitives instead of an in-memory agent loop. Use `inngest-agent-evals` with this skill when the user wants scoring, sessions, experiments, deferred scorers, or outcome-based evaluation for the agent.
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。
Investigate stuck runs and execution failures by tracing Symphony agent-provider logs with issue/session identifiers; use when runs stall, retry repeatedly, or fail unexpectedly.
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 authentication and authorization with Better Auth - a framework-agnostic TypeScript authentication framework. Features include email/password authentication with verification, OAuth providers (Google, GitHub, Discord, etc.), two-factor authentication (TOTP, SMS), passkeys/WebAuthn support, session management, role-based access control (RBAC), rate limiting, and database adapters. Use when adding authentication to applications, implementing OAuth flows, setting up 2FA/MFA, managing user sessions, configuring authorization rules, or building secure authentication systems for web applications.
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。
Complete operational workflow for implementer agents (Codex, Gemini, etc.) making code changes and writing tests. Drives all work through atomic commits — each loop operates on the smallest complete, reviewable change. Defines the Code Change Loop, Test Writing Loop, Lint Gate, and Issue Filing process with circuit breakers, severity levels, and escalation rules. Requires `committer` for all commits. Includes bundled provider-aware review scripts that keep same-model shell-outs as the last resort, plus a fresh-context Codex fallback for code review and test audit. Use this skill when starting any implementation task.
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。
Bootstrap new 33GOD ecosystem agents with standardized configuration. Use when creating new agents, spawning workers, deploying Yi nodes, or when the user says "spin up an agent", "create a new agent", "deploy a new worker", or needs a new agent for a specific pipeline role. Handles workspace creation, config injection, skill installation, provider mirroring, channel binding, and 33GOD ecosystem onboarding (GOD Docs, Plane, Bloodbank, memory).
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 Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code int...
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 Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
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 conversational AI agents using Vercel AI SDK + OpenRouter. Use when creating Next.js frontends with streaming UI, tool calling, and multi-provider support.
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 the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.
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, run, and review fair performance, token, and cost comparisons across GitHub Copilot CLI, Codex CLI, and direct model APIs. Use for AI CLI benchmark, Copilot vs Codex, prompt-cache diagnosis, cache read/write analysis, fresh-process latency measurement, token-cost comparison, or when a benchmark must separate provider caching from local CLI caches.
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 diagnosing or fixing user-reported application bugs. Guides evidence-backed root-cause analysis from symptoms, screenshots, logs, provider failures, background tasks, storage, or desktop lifecycle behavior through a scoped patch and regression 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。
Use when implementing or improving a user-facing app workflow. Guides product-grade UX, frontend, backend/API behavior, AI/provider or long-running task states, tests, and end-to-end verification from rough requirements to a shippable feature.
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。