新機能の作成、バグ修正、コードのリファクタリング時にこのスキルを使用します。ユニット、統合、E2Eテストを含む80%以上のカバレッジでテスト駆動開発を強制します。

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.

Configures Jahro lifecycle controls for safe production deployment including JAHRO_DISABLE, auto-disable, and build validation. Use when the user mentions production builds, release builds, disabling Jahro, shipping, CI/CD, lifecycle controls, or production safety.

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.

Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.

Implement Fireflies.ai rate limiting, backoff, and request queuing. Use when handling rate limit errors, implementing retry logic, or optimizing API request throughput for Fireflies.ai. Trigger with phrases like "fireflies rate limit", "fireflies throttling", "fireflies 429", "fireflies retry", "fireflies backoff".

Implement Firecrawl rate limiting, backoff, and request queuing patterns. Use when handling 429 errors, implementing retry logic, or optimizing API request throughput for Firecrawl. Trigger with phrases like "firecrawl rate limit", "firecrawl throttling", "firecrawl 429", "firecrawl retry", "firecrawl backoff".

Configure Firecrawl team access control with per-key credit limits and domain restrictions. Use when managing multiple API keys per team, implementing credit budgets per consumer, or controlling which domains each team can scrape. Trigger with phrases like "firecrawl RBAC", "firecrawl teams", "firecrawl enterprise", "firecrawl access control", "firecrawl permissions".

Implement Exa reliability patterns: query fallback chains, circuit breakers, and graceful degradation. Use when building fault-tolerant Exa integrations, implementing fallback strategies, or adding resilience to production search services. Trigger with phrases like "exa reliability", "exa circuit breaker", "exa fallback", "exa resilience", "exa graceful degradation".

Use when writing or reviewing Java code in this repo that enables Deepgram intelligence overlays on `/v1/listen` audio transcription - diarization, entity detection, sentiment, summarize, topics, intents, language detection, and redaction. Same endpoint as plain STT, but with extra request fields on `ListenV1RequestUrl` or `MediaTranscribeRequestOctetStream`. Use `deepgram-java-speech-to-text` for plain transcripts and `deepgram-java-text-intelligence` for analysis on existing text. Triggers include "audio intelligence", "diarize", "summarize audio", "sentiment from audio", "topic detection", and "redact".

Run all quality checks including linting, type checking, and tests. Use when the user wants to verify code quality, before committing, or when preparing a PR.

Extract Python examples from markdown docs and run them (including LLM examples). Use when validating documentation, after doc changes, or to verify all doc examples execute correctly.

Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".

Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.

Manage model risk governance in Domino using policies, bundles, and evidence. Covers creating governance bundles, attaching model artifacts and MLflow results as evidence, progressing through policy stages, and documenting findings. Use when the user mentions governance, compliance, bundles, policies, model risk management, SR 11-7, NIST AI RMF, or audit trails.

Use the domino-data Python SDK (dominodatalab-data) for programmatic data access in Domino. Covers DataSourceClient for SQL queries and object storage, DatasetClient for dataset files, TrainingSets for ML data versioning, Feature Store, and VectorDB (Pinecone) integration. Use when querying data sources, downloading datasets, managing training sets, or working with vector databases in Domino.

Recommend the right agents and skills for any task. Covers both heavyweight agents (Task tool) and lightweight skills (Skill tool). Triggers on: which agent, which skill, what tool should I use, help me choose, recommend agent, find the right tool.

Patterns for running long-lived processes in tmux. Use when starting dev servers, watchers, tilt, or any process expected to outlive the conversation.

Provides React patterns for hooks, effects, refs, and component design. Covers escape hatches, anti-patterns, and correct effect usage. Must use when reading or writing React components (.tsx, .jsx files with React imports).