「checkpoint」の検索結果

Use when you have a written implementation plan to execute in a separate session with review checkpoints

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 you resume work and the last session ended mid-phase, a .continue-here checkpoint exists, or a PLAN has no SUMMARY. Restores STATE.md context, shows status, and routes to the next command.

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 says 'm0 remember', 'record what we did', 'note for next session' or 'write a checkpoint', or after finishing a step worth handing to the next session. Appends one entry to the M0 thread (re-sending writes a second entry unless you pass the same `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。

Use when the user says m0 handoff, before I compact, end of session, save session state, resume where we left off, or continue in Cursor or Claude Code. Writes or reads a compact_checkpoint so a cold start becomes a continuation.

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 you have a written implementation plan to execute in a separate session with review checkpoints

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。

One-prompt autonomous product design and implementation. Use automatically for broad greenfield UI requests such as 'from scratch', '새 제품/화면을 알아서 만들어줘', or requests that delegate DESIGN.md creation. It decides whether to reuse, establish, refresh, or skip a project design system; asks at most one consequential question batch; then builds and verifies the real surface. Use omd:harness instead only when the user explicitly asks for guided checkpoints.

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。

One-prompt autonomous product design and implementation. Use automatically for broad greenfield UI requests such as 'from scratch', '새 제품/화면을 알아서 만들어줘', or requests that delegate DESIGN.md creation. It decides whether to reuse, establish, refresh, or skip a project design system; asks at most one consequential question batch; then builds and verifies the real surface. Use omd:harness instead only when the user explicitly asks for guided checkpoints.

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。

Instantiate or update a workspace `UNITS.csv` from a selected pipeline and units template (deps/checkpoints/acceptance).

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。

Execute exactly one eligible Unit in an existing research Workspace; use for stepwise or manual semantic execution when status, Attempt, Artifact, Manifest, checkpoint, and acceptance evidence must remain synchronized.

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。

Run a research Workflow end to end when the user requests a survey, brief, review, tutorial, or idea exploration; route an unbound goal, execute one eligible Unit at a time, and stop at checkpoints or diagnosed 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。

Route an unbound research Goal to one Workflow or materialize its initial C0 kickoff block; use during initial binding, not for later checkpoint summaries or approval.

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。

Entrypoint for managing Volcengine Flink (based on Apache Flink) workloads. Use it for developing and deploying streaming and batch jobs, diagnosing real-time issues (e.g., backpressure, checkpoint failures, OOM), troubleshooting resources, and performing SRE actions (stop/start/restart/scale/config changes). It intelligently routes requests to four specialized sub-skills and leverages flink-mcp for tool execution.

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。

Entry point + orchestrator for the recomby-geo GEO (Generative Engine Optimization) workflow on OpenAI Codex CLI. Use when the user wants to run any stage of the GEO pipeline on a client folder — intake, visibility audit, content-gap analysis, content brief, draft production, distribution, or monthly re-audit — or asks to "run GEO", "audit AI search visibility", or "GEO this client". Codex has no bare slash commands, so this skill is how the 7 stages (that Claude Code runs as /01-intake … /07-reaudit) are driven on Codex. It routes to the per-stage specs in this plugin's commands/ and enforces the orchestration rules. Does not auto-fill expert content — the human-in-loop brief checkpoint is the moat.

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。

Decision protocol for building, debugging, and operating LangGraph-based agent systems. Activates when a coder agent is asked to design a stateful LLM workflow, add human-in-the-loop, choose a multi-agent pattern (supervisor / swarm / hierarchical), pick a checkpoint backend, or migrate a fragile chain into a durable graph. LangGraph is positioned by its maintainers as a "low-level orchestration framework for building, managing, and deploying long-running, stateful agents" — this skill encodes the *when* and *why*, not the API.

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。

Evidence-before-action diagnosis of failing ML experiments. Probes the system before guessing causes, process list, dmesg, GPU stats, log scrollback, checkpoint state, then states a hypothesis as a hypothesis and runs a smoke before claiming a root cause. Use when the user asks why a run is failing, diverging, OOMing, hanging, slow, producing weird metrics, has crashed, or asks to debug, diagnose, troubleshoot, or investigate a training issue.

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 you have a written implementation plan to execute in a separate session with review checkpoints

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。

Track progress across work sessions using SESSION.md with git checkpoints and concrete next actions. Converts IMPLEMENTATION_PHASES.md into trackable session state with phase status, progress markers, and recovery points. Use when: starting projects after planning phase, resuming work after context clears, managing multi-phase implementations, or troubleshooting lost context, missing progress tracking, or unclear next steps.

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 upgrading an existing TypeScript codebase from Inngest SDK v3 to v4, or when fixing mixed v3/v4 API usage. Covers detecting current SDK usage, moving triggers into createFunction options, replacing EventSchemas with eventType/staticSchema, moving serve options to the client, updating realtime imports, rewriting step.invoke string IDs, checkpointing/serverless runtime settings, Connect option changes, and verification.

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 you have a pre-registered analysis plan to execute inline in this session with review checkpoints, on a platform without subagents

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 multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI.

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。

Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.

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。

Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.

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 choosing the model for a medical-imaging study. Picks a paper-grounded architecture family (CNN/ViT, U-Net/nnU-Net, detection, SAM/foundation, GNN), then vets the concrete repo or checkpoint for licence, version pin, weight provenance and benchmark overlap.

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。

Guides TensorFlow Fast Style Transfer training, image stylization, and video stylization workflows from checkpoints, VGG/COCO assets, and script-oriented CLIs.

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。