1,906 件 ・ 関連度順
概要と使いどころ
One-shot chat completion against DeepSeek's `deepseek-chat` model via the OpenAI-compatible /v1/chat/completions endpoint. Reads DEEPSEEK_API_KEY from the environment; degrades gracefully (exit 0 with a JSON status:degraded envelope) when the key is missing or the API is unreachable. Use for non-reasoning tasks — summarization, extraction, quick classification — where deepseek-reasoner would be overkill.
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 one tick of the sales business-pod (ADR-164 §4.1, Phase 2). Loads templates/sales.json, validates it against the pod-schema, resolves agents against ruflo's agent registry, reserves budget via the Phase-2 file-based stub ledger (atomic SQLite tracker is Phase 3 per ADR-164.1), constructs per-agent dry-run prompts, posts a summary envelope to room "sales" via the federation_bbs_publish JSONL backing store, and emits a structured {podName, tickId, agentsRan, totalUsd, envelopeId, status} line for /loop ingestion. Dry-run by default; --live is reserved for Phase 3.
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 deterministic, editable, free-viewpoint Three.js worlds from text or structured briefs. Use for cinematic 3D terrain, semantic regions, procedural biomes, explicit landmarks, environmental scattering, camera fly-throughs, world diagnostics, or requests for a real 3D environment rather than generated 2D footage. Integrates OpenMontage's threejs_world tool with HyperFrames; do not use for a single isolated 3D object or a flat parallax scene.
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。
Three.js textures - texture types, UV mapping, environment maps, texture settings. Use when working with images, UV coordinates, cubemaps, HDR environments, or texture 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。
Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review. Covers the native 5.0 build and environment API, published 3.0.0 Gymnasium/PettingZoo adaptation, and a pinned historical 4.0 profile.
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。
Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior.
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 a working ML training/inference environment on NVIDIA DGX Spark (GB10, aarch64, CUDA 13). Use when installing PyTorch/Unsloth/TRL/vLLM on DGX Spark, hitting libcudart or wheel-ABI errors on aarch64, or choosing between NGC containers and bare pip installs.
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 OpenViking memory issues by tracing backward from a memory file to its archive memory_diff.json and, when needed, session messages. Read-only; use for incorrect content, wrong paths or owners, missing memories, and unexplained updates or deletes.
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。
Compile timestamped conversation logs, agent sessions, IM messages, collaborative documents, meeting notes, task records, and similar OpenViking materials into concise, evidence-grounded daily reports. Use with ov compile when the user asks for a daily work report, end-of-day digest, 日报, or reports for one or more dates, especially when activities must be reconstructed across heterogeneous sources without treating plans or agent suggestions as completed 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。
Work through tasks on a kanban board stored in OpenViking (viking://agent/kanban/<board>/, one markdown file per task). Use when the user says "ov kanban", "kanban", "看板", asks to put a task on the board, hand off the current work, continue a task another agent started, or run an unattended task loop. A board holds many tasks; each task file is the handoff itself - a frontmatter header (id, status, owner, board) plus Goal, Context, Decisions, Progress, Next, Questions, Log - and its process detail is folded into an archive file instead of being summarized away, so any agent with the `ov` CLI can resume it and drill down when needed.
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。
Compile one or more OpenViking knowledge bases or document collections into topic-organized, evidence-grounded high-level knowledge, including cross-source findings, trends, changes, drivers, comparisons, implications, and uncertainties. Use with ov compile when the user asks to distill or synthesize a knowledge base, compare multiple collections, or derive higher-order insights such as changes across financial reports; do not use for document-by-document summaries.
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。
Load when an agent needs to add, manage, browse, search, modify, or remove resources in OpenViking. Trigger on explicit user requests about resource management or context search, when the user mentions `ov add-resource`, `ov task watch`, `ov export`, `ov import`, `ov backup`, `ov restore`, `ov ls`, `ov tree`, `ov read`, `ov write`, `ov mkdir`, `ov rm`, `ov mv`, `ov find`, `ov search`, `ov grep`, `ov glob`, or when an agent needs to inspect, search, or organize the `viking://resources/` namespace.
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。
Load relevant OpenViking experience memories via case-linked experience candidates before solving a 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。
Use when the user explicitly types `ov dream` or `ov recall <query>` and the request should be routed to the OpenViking sync/recall CLI instead of handled as normal chat.
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。
Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration scanning, and source code repository mining for undocumented routes. Use when assessing API attack surface, auditing for forgotten test environments or deprecated API versions still running, or building an API registration governance policy.
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。
Builds a structured vulnerability scanning workflow using tools like Nessus, Qualys, and OpenVAS to discover, prioritize, and track remediation of security vulnerabilities across infrastructure. Use when SOC teams need to establish recurring vulnerability assessment processes, integrate scan results with SIEM alerting, and build remediation tracking dashboards.
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。
Phase 2 of building a Claude Managed Agent — turn a validated build sheet into exact API payloads and a resumable BYOK curl launch script, then launch (environment → agent → session → kickoff) using the founder's OWN Anthropic key. Use when the user says "launch it", "deploy the agent", "create the agent now", or when the orchestrator routes phase=stage-launch. payload_generator.py emits the four ordered payloads; launch_script_writer.py writes launch.sh that reads $ANTHROPIC_API_KEY at runtime and never embeds it; payload_validator.py runs a pre-launch check including an API-key-leak scan. No tool in this skill makes network calls — the user runs launch.sh themselves. Distinct from interview (planning) and grade-iterate (the outcome loop).
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。
Perform a PESTLE analysis covering Political, Economic, Social, Technological, Legal, and Environmental factors. Use when assessing the macro environment, doing strategic planning, or evaluating external factors affecting your business.
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: User wants to extend Docker with custom tools, personalize the Docker environment, or set up user-specific Docker customization. Triggers: 'extend docker', 'docker-extend', 'add tools to docker', 'customize docker', 'add my tools to the container', 'personalize docker setup', 'docker user setup', 'install tools in docker'. Does: Interactively sets up Dockerfile.user and docker-compose.override.yml so users can add personal tools to their Docker environment without affecting maintainer files or committing user-specific config to git.
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。
Persistent-session, per-sweep QA runbook for {{target_repo}}. Discovers PRs since the last check, then for each one checks out the branch, runs the full verification suite, deploys the change to the test environment, exercises it through the edge, and posts a pass/fail result as a GitHub check and comment. Test environment only — no production access, no merge.
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。
Put your AI on a Performance Improvement Plan. Forces exhaustive problem-solving with Western big-tech performance culture rhetoric and structured debugging. Trigger when: (1) task failed 2+ times or stuck tweaking same approach; (2) about to say 'I cannot', suggest manual work, or blame environment without verifying; (3) being passive—not searching, not reading source, just waiting; (4) user frustration: 'try harder', 'stop giving up', 'figure it out', 'again???', or similar. Also for complex debugging, env issues, config/deployment failures. All task types: code, config, research, writing, deployment, infra, API. Do NOT trigger on first-attempt failures or when a known fix is executing.
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。
Onboard a user to Wren Engine end-to-end. Walks through environment checks, project scaffolding, connection configuration via .env, and first query. Use when: user wants to install Wren Engine, set up a new data source connection, or bootstrap a new project from scratch. Triggers: '/wren-onboarding', 'install wren', 'set up wren engine', 'wren onboarding', 'connect new database to wren'.
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, manage, inspect, and troubleshoot Vercel projects from the command line. Use for Vercel deployments, Vercel Toolbar comments, build failures, projects and teams, environment variables, domains and DNS, logs, metrics, Speed Insights, Core Web Vitals, request traces, usage, activity, alerts, firewall rules, cache, cron jobs, deploy hooks, Edge Config, feature flags (`vercel flags`), integrations, connectors, Blob storage, Container Registry (VCR), microfrontends, rolling releases, custom environments, Sandbox, agent/MCP setup, preview access, local development, or `vercel api` fallback.
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 and wire Convex deployment env vars / secrets for the 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。