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概要と使いどころ
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
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-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast 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。
RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.
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。
Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.
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。
Rails 7+ specialist that optimizes Active Record queries with includes/eager_load, implements Turbo Frames and Turbo Streams for partial page updates, configures Action Cable for WebSocket connections, sets up Sidekiq workers for background job processing, and writes comprehensive RSpec test suites. Use when building Rails 7+ web applications with Hotwire, real-time features, or background job processing. Invoke for Active Record optimization, Turbo Frames/Streams, Action Cable, Sidekiq, RSpec Rails.
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。
Spin up a live local Omnigent server + runner and exercise the native Pi TUI harness (pi-native) end-to-end — launch the real `pi` CLI via `omnigent pi`, drive turns through the web/bridge, smoke-test, and bug-bash. Load when developing, testing, or debugging the pi-native harness (omnigent/inner/pi_native_executor.py, pi_native_harness.py, omnigent/pi_native.py, pi_native_bridge.py, pi_native_credentials.py) or its bridge / extension / auth / model 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。
Spike an idea through experiential exploration, or propose what to spike next (frontier mode)
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。
Initialize a new project with deep context gathering and PROJECT.md
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。
Write minimal, reliable bug reproducers (repros) for any project. Use when: (1) a bug report or issue needs a test that reliably demonstrates the failure, (2) converting a described failure scenario into runnable code, (3) minimizing an existing complex test to its essential trigger conditions. Covers the full repro workflow: failure characterization, scope selection, writing the repro, verifying it fails for the right reason, and minimizing to the smallest possible trigger.
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。
Operate professional paid advertising across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for account intake, source-grounded audits, strategy, budget and measurement planning, creative production, experiments, reporting, monitoring, and explicitly approved campaign changes. Also trigger on PPC, paid social, retail media, attribution, tracking, landing pages, cross-platform conversion totals, negative keywords or search terms, beta-feature scoring, stale platform claims, API-token or credential setup, campaign deletion, and safe Claude Ads installation or uninstall.
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 source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or worker failure, missing-platform weighting, beta-feature eligibility and scoring, spend audits, tracking audits, or prioritized opportunities and risks.
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。
Review marketing copy for claims that need substantiation, reframing, or cutting. Use when the user says "review this marketing copy", "check these claims", "can we say this", "is this puffery or a problem", or pastes marketing content (landing pages, emails, ads, taglines).
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。
Freedom-to-operate triage — a structured first look at potentially blocking patents, not an FTO opinion. Use when a product, process, or feature is being evaluated for blocking patents, when asked whether anything stops a launch, or to build a claim-chart first pass against the most plausible patents before patent counsel review. This skill never concludes a product is clear to launch.
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。
Entity compliance tracker — initialize, report upcoming deadlines, update status, run health audit, export to CSV. Maintains a compliance-tracker.yaml built from the entity table, calculates filing deadlines by entity and jurisdiction, and surfaces what's due in the next 30/60/90 days. Use when user says "entity compliance", "filing deadlines", "annual reports due", "entity tracker", "what filings are due", "entity health", or "good standing".
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。
Post-closing M&A integration tracker — phased workplan, consent tracking, contract assignment at scale, weekly status reports. Initializes from whatever deal artifacts are available (purchase agreement, deal summary, closing checklist) and connects to deal-context.md and closing-checklist.yaml from the M&A cold-start. Use when user says "integration", "post-close", "post-closing", "consents outstanding", "contract assignment", "integration status", or "what's left on the deal".
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。
Initialize the productivity system and open the dashboard. Use when setting up the plugin for the first time, bootstrapping working memory from your existing task list, or decoding the shorthand (nicknames, acronyms, project codenames) you use in your todos.
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。
Resolve unresolved PR review comments across an entire Graphite (gt) stack of many PRs, bottom-up, in one working directory. Use when asked to "go through this stack and resolve comments", "clean up review comments across the whole stack", or given a list/range of PR numbers that form (or partially form) a gt stack. Distinct from the single-PR resolve-pr-comments skill, which this one uses as its per-branch inner 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。
Secret management expert. ALWAYS invoke this skill when you need to read API keys, tokens, or other secrets configured by the user. Never hardcode credentials — use this skill to retrieve them securely.
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。
Workspace Git identity and credential management. ALWAYS invoke this skill when the user asks about configuring Git user info, adding HTTPS tokens, importing SSH keys, or managing workspace-level Git authentication.
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。
Dashboard panel component pattern for aggregator/summary panels that accept pushed partial data updates via updateData(), defer rendering until first data arrives, and incrementally re-render metrics without re-fetching — ideal for panels that synthesize data already fetched by other panels.
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。
Adaptive polling pattern with exponential backoff on failure, automatic recovery on success, and visibility-aware scheduling
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。
How to implement sidebar/widget UI components that receive pushed data updates from a caller, using a singleton module pattern with exported factory and update functions plus module-level DOM refs for efficient partial re-renders.
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。
Unified guide for authoring dashboard panel components in vanilla TypeScript — covers the Panel base class architecture, localStorage state persistence, exponential-backoff retry, and CircuitBreaker integration. Shows how to wrap any existing fetchX() service call with CircuitBreaker.execute() as a one-liner and clarifies when each resilience layer is appropriate.
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-method PDF extraction with sequential fallback and OCR for scanned 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。