「agent workflow」の検索結果

Register trained models in MLflow Model Registry with version control, implement stage transitions (Staging, Production, Archived) with approval workflows, and manage model lineage with comprehensive metadata and deployment tracking. Use when promoting a trained model from experimentation to production, managing multiple model versions across development stages, implementing approval workflows for governance, rolling back to previous versions, or auditing model changes for compliance.

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。

Orchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.

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 GitOps continuous delivery using Argo CD or Flux with app-of-apps pattern, automated sync policies, drift detection, and multi-environment promotion. Manage Kubernetes deployments declaratively from Git with automated reconciliation. Use when implementing declarative infrastructure management, migrating from imperative kubectl commands to Git-driven deployments, setting up multi-environment promotion workflows, enforcing code review gates for production, or meeting audit and compliance requirements.

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 electronic signatures compliant with 21 CFR Part 11 Subpart C and EU Annex 11. Covers signature manifestation (signer, date/time, meaning), signature-to-record binding, biometric vs non-biometric controls, policy creation, and user certification requirements. Use when a computerized system requires legally binding electronic signatures for GxP records, when replacing wet-ink signatures in regulated workflows, when implementing batch release or document approval workflows, or when a regulatory gap reveals missing signature controls.

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Evolve an existing team composition by refining its structure in-place or creating a specialized variant. Covers assessing the current team against template and coordination patterns, gathering evolution requirements, choosing scope (adjust members, change coordination pattern, split/merge teams), applying changes to the team file and CONFIG block, updating version metadata, and synchronizing the registry and cross-references. Use when a team's member roster is outdated, coordination pattern no longer fits, user feedback reveals workflow gaps, a specialized variant is needed alongside the original, or agents have been added or removed from the library affecting team composition.

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Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.

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Create new marketing skills for the mktg playbook. Use when the agent needs to add a new capability, someone says 'create a skill', 'new skill', 'add a marketing skill', 'extend the playbook', 'I need a skill for X', 'build a skill', 'make a skill for Y', or 'add capability for Z'. Also use when someone wants to capture a marketing workflow they just did into a reusable skill, or when they say 'turn this into a skill'. Reads the skill contract, generates SKILL.md with correct frontmatter and structure, creates the directory, and reminds the agent to register in the manifest.

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。

Work with any Upstash product, SDK, or tool, including serverless Redis (caching, sessions, leaderboards, key-value storage), Ratelimit (rate limiting and throttling), QStash (message queue, cron schedules, background jobs), Workflow (durable long-running functions), Vector (vector database for embeddings, semantic search, and RAG), Search (full-text and semantic search), Box (sandboxed cloud containers for AI agents, TypeScript/JavaScript and Python), Blob (serverless S3-compatible file storage with direct browser uploads), the Upstash CLI, and no-signup scratch Redis for agents. Use when the user mentions Upstash or needs any of these capabilities in a serverless, edge, or Node.js 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。

Git-native issue tracking (beads), coding guidelines, knowledge injection, and spec-driven planning for AI agents. Drop-in replacement for bd/Beads with simpler architecture. Use for: tracking issues/beads with dependencies, creating bugs/features/tasks, planning specs, implementing features from specs, code reviews, committing code, creating PRs, loading coding guidelines (TypeScript, Python, TDD, golden testing, Convex, monorepo patterns), code cleanup, research briefs, architecture docs, agent handoffs, and checking out third-party library source code. Invoke when user mentions: tbd, beads, bd, shortcuts, issues, bugs, tasks, features, epics, todo, tracking, specs, planning, implementation, validation, guidelines, templates, commit, PR, pull request, code review, testing, TDD, test-driven, golden testing, snapshot testing, TypeScript, Python, Convex, monorepo, cleanup, dead code, refactor, handoff, research, architecture, labels, search, checkout library, source code review, or any workflow shortcut.

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。

AI 内容创作专家团主理人（司远 · 创意制片人）。协调 6 位专业成员（creative-strategist、copywriter、video-generator、image-creator、video-editor、content-adapter）按预设 Workflow 完成多模态内容生产全流程。 触发词："帮我做个视频"、"生成一段宣传片"、"做一套宣传物料"、"写一篇带配图的文章"、"帮我设计品牌视觉"、"制作短视频"、"内容创作一条龙"。 路由逻辑：单一维度任务走单 Agent 直调；综合性内容需求走对应预设 Workflow。

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。

智数分析专家团主理人（诺亚 Nova · 首席数据编排师）。协调 5 位专业成员（sql-analyst、data-scientist、knowledge-researcher、dashboard-designer、report-composer）按预设 Workflow 完成端到端数据分析交付。 触发词："分析数据"、"生成报告"、"数据画像"、"查数据库"、"数据分析"、"帮我分析"、"数据可视化"、"仪表盘"。 路由逻辑：单一维度任务走单 agent 直调；综合性任务走对应 Workflow。

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 monitoring, tracing, or debugging agentic workflows in production. Keywords: observability, tracing, OpenTelemetry, Langfuse, latency, token cost, loop detection, telemetry.

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。

Generate standardized .agent-os directory structure with product documentation, mission, tech-stack, roadmap, and decision records. Enables AI-native workflows.

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。

ブラウザを手足のように操る。ページ遷移、フォーム入力、スクショ、なんでもこい。Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include 'go to [url]', 'click on', 'fill out the form', 'take a screenshot', 'scrape', 'automate', 'test the website', 'log into', or any browser interaction request. Do NOT load for: sharing URLs, embedding links, screenshot image files.

Digital Garden & Visual Architect. Use this agent to manage the Obsidian Knowledge Base, create visual logic maps via JSON Canvas, and maintain the automated development journal. It bridges the gap between abstract ideas and structured documentation. When the host supports them, use the Obsidian-focused skills and integrations for CLI, Bases, Markdown, Canvas, and defuddling workflows. When the host supports them, use the Obsidian-focused skills and integrations for CLI, Bases, Markdown, Canvas, and defuddling workflows.

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 colorful infographic PNGs from a conversation, topic, file, skill, or workflow. Use when: インフォグラフィック, 図解, 挿絵, 章扉, X投稿用画像, OGP, HTML→PNG, visualize session, poster image. Produces 2-3 self-contained HTML patterns, renders static PNGs, and verifies every image visually before reporting. Not for animated GIFs, architecture/sequence/flow diagrams (editable .drawio or interactive HTML), or HTML slide decks.

Investigate Azure incidents and service degradations with a read-only workflow using Azure CLI, Resource Health, Activity Log, metrics, resource logs, and official Microsoft docs. Use when troubleshooting Azure outages, Resource Health alerts, Azure Firewall or DNS failures, ExpressRoute or BGP instability, VM availability problems, AKS incidents, App Service failures, database connectivity issues, Entra ID sign-in problems, load balancer issues, platform-vs-workload cutover, or drafting a troubleshooting report. Triggers on 'Azure トラブルシューティング', '障害調査', '切り分け', 'Resource Health', '復旧確認', 'Azure Firewall', 'DNS', 'ExpressRoute', 'VPN Gateway', 'BGP', 'AKS', 'App Service', 'SQL', 'PostgreSQL', 'Cosmos DB', 'Entra ID', 'incident', 'degraded', 'unavailable'.

Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

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 hunting self-hosted GitHub Actions runner vulnerabilities where fork pull requests can execute on privileged non-ephemeral runners. Trigger on: "self-hosted runner", "runs-on self-hosted", "fork PR workflow", "non-ephemeral runner", "first-time contributor approval", "runner images", "azure-builds runner", "outside collaborator approval", "runs-on matrix", "persistent runner", "Gato GitHub Attack Toolkit", "runner agent", self-hosted CI/CD runner abuse, "git config token", "workflow log deletion", runner C2.

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 RAG or LLM applications with LlamaIndex - data loaders, node parsing, vector stores, retrievers and rerankers, query engines, agents and workflows, streaming, or 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。

Cloudflare-first platform selection. Decision trees for Workers, D1, R2, KV, DO, Queues, Vectorize, Containers, Sandboxes, Flagship, Agent Memory, Workflows v2. Default stack, override conditions, auth, data patterns, reliability.

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。

Provider-agnostic patterns for LLM function calling, tool loops, and agentic workflows

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LlamaIndex.TS data framework for RAG, indexing, retrieval, query engines, chat engines, and agentic workflows in TypeScript

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。

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation 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。