Capture Unreal Engine traces, inspect Trace Store files, keep Unreal Insights GUI open, and export/summarize timing/counter data.
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。
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概要と使いどころ
Capture Unreal Engine traces, inspect Trace Store files, keep Unreal Insights GUI open, and export/summarize timing/counter data.
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。
Author the committed release-notes file for a Prisma 8 release (stable or `8.0.0-rc.N`) by enumerating the merged PRs since the previous release `v*` tag (stable or `-rc.N`), resolving opaque `TML-NNNN:` titles via Linear context (never copied verbatim), triaging public-worthiness, and writing categorized notes — breaking changes first — into `docs/releases/v<version>.md` plus a mirrored `CHANGELOG.md` entry. Use when cutting a release, when the `publish-npm-version` skill reaches its "draft the release notes" step, when asked to "draft the release notes", "write the changelog for this release", "author docs/releases/v<x>.md", or "summarize what shipped since the last release".
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。
Fetches canonical PR review state and renders derived state artifacts. Use when the user wants the state acquisition phase only (fetch, render, summarize) for a review-framework PR.
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-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" request.
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。
Read, create, or edit Microsoft Word .docx files — extract/summarize text and tables, generate reports/letters/memos with headings, tables, images, TOC and page numbers, do find-and-replace, or apply tracked changes (redlines) and comments. Use whenever the user has a .docx or wants a Word deliverable. Not for PDF, .xlsx, .pptx, or Google Docs.
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-based creation of a reusable personal course-making Skill from the user's own classroom and chat history. Use when the user asks to summarize, analyze, or learn from their past course-making records/history and create a personal, exclusive, or reusable Skill, such as “总结我的做课记录,给我做个专属 Skill” or “从我过去的课程和对话里提炼一个个人技能”.
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。
Analyzes git diffs or staged changes and generates narrative commit messages that explain WHY a change was made, not just what changed — following Conventional Commits format. Use when asked to "write a commit message", "generate a commit", "describe my changes", "what should I commit this as", "commit this", "summarize my diff", or "help me commit". Works with git diff output, staged files, or plain descriptions of changes.
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。
Read and summarize text-based file types only. Prefer read_file for text formats; use execute_shell_command for type detection when needed. PDF/Office/images/archives are handled by other skills.
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 a MISP (Malware Information Sharing Platform) instance via PyMISP to compute event statistics, IOC type breakdowns, threat actor galaxy clusters, and tag trends, and generate threat landscape reports with temporal trends. Use when asked to analyze threat intelligence data, summarize top threat actors or malware families, or produce a CTI landscape report from MISP events.
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。
Chat / code generation via 9Router using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through 9Router.
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。
Turn a call transcript or call notes into a customer follow-up email draft, an internal chat summary, and proposed CRM updates. Use when the user says "call summary", "follow up on my [company] call", "summarize my call with [account]", "write the recap", "process this transcript", "process my call notes", "capture the objections and next steps", or pastes rough notes or a transcript after a discovery, demo, or negotiation call.
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。
Combines search results from multiple sources into coherent, deduplicated answers with source attribution. Handles confidence scoring based on freshness and authority, and summarizes large result sets effectively.
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。
Summarize the last N agent sessions for the current project, grouped by date, with highlight observations per session. Use when the user asks "recap", "what have we been doing", "today", "this week", or wants a rollup of recent 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。
Authoring playbook for building agents that triage and reply to customer messages — support tickets, email inquiries, chat questions, refund requests, or product issues. Use this when the user wants an agent that handles inbound customer questions, drafts replies, escalates hard cases, summarizes tickets, or follows a support playbook.
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。
Authoring playbook for building agents that search, read, and synthesize information into a report. Use this when the user wants an agent to research a topic, summarize sources, compare options, do competitive analysis, monitor news, generate briefs, or pull together a citation-backed report from the web or internal documents.
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 context-mode tools (ctx_execute, ctx_execute_file) instead of Bash/cat when processing large outputs. Triggers: "analyze logs", "summarize output", "process data", "parse JSON", "filter results", "extract errors", "check build output", "analyze dependencies", "process API response", "large file analysis", "page snapshot", "browser snapshot", "DOM structure", "inspect page", "accessibility tree", "Playwright snapshot", "run tests", "test output", "coverage report", "git log", "recent commits", "diff between branches", "list containers", "pod status", "disk usage", "fetch docs", "API reference", "index documentation", "call API", "check response", "query results", "find TODOs", "count lines", "codebase statistics", "security audit", "outdated packages", "dependency tree", "cloud resources", "CI/CD output". Also triggers on ANY MCP tool output that may exceed 20 lines. Subagent routing is handled automatically via PreToolUse hook.
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 coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics, experiments, discovery, roadmaps, spec-to-repo, landing pages, SaaS scaffolding) or the 4 standalone product-team plugins (user stories, Apple HIG, code-to-PRD, research summarizer). Triggers on 'help me prioritize', 'plan a product experiment', 'we ship features nobody uses', 'run the discovery loop', 'is our OST sound'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a continuous-discovery loop (Torres cadence tracker + OST linter as machine gates) or a full goal→plan→execute→verify→close run through the repo-wide agent-harness. Distinct from project-management (how to deliver vs what to build), marketing/landing (from-scratch pages), and engineering/agent-harness (the generic loop engine this orchestrator plugs into).
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 asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.
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 asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry CLI; perform read-only queries using the `sentry` 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。
Produce a scannable review brief for a branch or PR so the maintainer can approve without reading the whole diff. Use when the user asks "how do I review this", "summarize the changes", "what should I look at", or wants to understand a PR in under two minutes.
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。
Summarize one project against its stated milestones using recent work and verified outcomes.
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。
Summarizes data lineage graphs on Google Cloud to help users debug data quality issues and understand data provenance for BigQuery and Cloud Storage. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).
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。
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.
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。