「rag」の検索結果

Survey all user-facing strings in a codebase — map coverage and find gaps. Use when asked "what user-facing strings do we have", "map our copy coverage", or "find hardcoded strings".

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。

ML/AI engineer — LLM integrations, prompt engineering, model pipelines, evals, RAG. Use when asked to "add AI to this", "integrate an LLM", "build a RAG pipeline", "evaluate model accuracy", or "improve this prompt".

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。

Expert guide for file uploads (S3, R2, Supabase Storage), presigned URLs, image/video processing, CDN optimization, and media pipeline architecture / Panduan ahli untuk upload file (S3, R2, Supabase Storage), presigned URL, pemrosesan gambar/video, optimasi CDN, dan arsitektur pipeline media.

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。

Firebase security expert to audit Security Rules (Firestore/Realtime Database/Storage), authentication, API keys, data leakage prevention, and App Check configuration / Ahli keamanan Firebase untuk audit Security Rules (Firestore/Realtime Database/Storage), autentikasi, API keys, pencegahan kebocoran data, dan konfigurasi App Check.

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。

Expert guide for integrating Large Language Models (LLMs), Model Context Protocol (MCP v1.x), hybrid reasoning models, RAG architecture, vector databases, and AI agents / Panduan ahli untuk integrasi LLM, Model Context Protocol (MCP), model hybrid reasoning, arsitektur RAG, vector database, dan agen 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。

OpenStack capacity planning operations skill for resource planning, quota management, and scaling decisions. Covers compute capacity (allocation ratios, vCPU/RAM utilization, host aggregates, availability zones), storage capacity (Cinder pool sizing, thin provisioning, Glance storage, Swift rings), network capacity (floating IP pools, port quotas, subnet sizing), project quota management (templates for small/medium/large profiles), flavor sizing strategy, utilization analysis with placement service, growth forecasting from historical metrics, and right-sizing recommendations for underutilized resources.

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。

OpenStack Cinder block storage service. Provides persistent volume management for cloud instances including volume creation, snapshots, backups, LVM/iSCSI backend, volume types with QoS, encryption (LUKS), volume migration, and multi-backend support. Use for deploying, configuring, operating, and troubleshooting OpenStack block storage.

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。

OpenStack Glance image service skill for deploying, configuring, operating, and troubleshooting the VM image registry. Covers image upload/download, format management (qcow2, raw, vmdk, vhd, iso), backend storage selection (file, swift, ceph), image import methods (web-download, glance-direct, copy-image), metadata management, property protections, image sharing between projects, snapshot lifecycle, image caching, and storage usage monitoring. Use when deploying Glance via Kolla-Ansible, managing VM images, converting image formats, or troubleshooting image upload 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。

Time average of observable along trajectory

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 pytest test architecture for Python 3.11+ using behavioral contracts, risk, and maintenance-adjusted value. Use when choosing unit/integration/property/e2e boundaries, fixture strategy, coverage measurement, or mutation testing. Preserves existing project gates but does not invent test-pyramid ratios, coverage percentages, mutation-score targets, or tests for implementation detail.

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。

Pytest testing patterns for Python — fixtures, behavioral naming, behavior/risk-driven coverage, property-based testing with Hypothesis when useful, and mutation testing when justified. Use when writing tests, designing fixtures, configuring coverage, or applying parametrize, async testing, or property-based strategies.

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 pytest test effectiveness against authoritative contracts, relevant faults, behavior-preserving refactors, realistic boundaries, isolation, and diagnostics. Use for test-quality audits, coverage-gap reviews, regression-test changes, or mocking reviews; preserve existing project gates rather than inventing coverage targets.

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 asked to find a rage moment, analyze a direct transcript path, or analyze a session time range. RTFP finds the strongest instruction-following failure in Claude or Codex sessions and renders a rage receipt.

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。

Validate whether an implementation plan can achieve its stated outcome before execution. Use to check requirement coverage, task contracts, dependencies, data/artifact flow, testability, ownership, impact coverage, and executable ordering without checking whether implementation already exists.

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。

Design, create, run, monitor, and maintain Vapi Simulations for assistants and squads. Use for turning plain-language requirements into a coverage plan, simulation personalities, scenarios, structured-output success criteria, simulations, suites, extending an existing suite, chat or voice runs, tool mocks, target variables, lifecycle webhooks, regression coverage, launch readiness, CI quality gates, run-result analysis, and simulation API validation errors. Do not use for fixed-turn mock-conversation Evals unless the user is deciding between Evals and Simulations.

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。

Institution ratings, consensus price targets, EPS/revenue forecasts, finance calendar, shareholder data, fund holders, insider trades (SEC Form 4), short interest, industry rankings, peer group analysis via Longbridge. Frameworks: investment proposals, coverage initiation, stock research, competitive analysis, financial planning, and DeFi/on-chain analysis. Triggers: "机构评级", "目标价", "一致预期", "EPS预测", "内部人交易", "空头", "行业排名", "投资提案", "首次覆盖", "竞争格局", "财务规划", "DeFi收益", "链上数据", "機構評級", "目標價", "一致預期", "內部人交易", "空頭", "投資提案", "首次覆蓋", "競爭格局", "鏈上數據", "analyst rating", "price target", "consensus", "insider trades", "short interest", "coverage initiation", "DeFi yield", "on-chain", "earnings calendar", "finance calendar", "财报日历", "下周谁财报", "下周财报", "下周有哪些财报", "哪些财报", "谁财报", "FOMC", "非农", "股东", "谁持有", "股東", "基金持仓", "基金持倉", "機構評級", "目標價", "財務規劃"

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。

Create a new storage resource. Requires authentication. Use for Agentuity cloud platform operations

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。

Delete a storage resource or file. Requires authentication. Use for Agentuity cloud platform operations

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。

Download a file from storage bucket. Requires authentication. Use for Agentuity cloud platform operations

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。

Show details about a specific storage bucket. Requires authentication. Use for Agentuity cloud platform operations

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。

List storage resources or files in a bucket. Requires authentication. Use for Agentuity cloud platform operations

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。

Upload a file to storage bucket. Requires authentication. Use for Agentuity cloud platform operations

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。

Detect AI/LLM-generated text patterns in research writing. Use when: (1) Reviewing manuscript drafts before submission, (2) Pre-commit validation of documentation, (3) Quality assurance checks on research artifacts, (4) Ensuring natural academic writing style, (5) Tracking writing authenticity over time. Analyzes grammar perfection, sentence uniformity, paragraph structure, word frequency (AI-typical words like 'delve', 'leverage', 'robust'), punctuation patterns, and transition word overuse.

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。

Audit codebase for agentic layer coverage and identify gaps. Use when assessing agentic layer maturity, identifying investment opportunities, or evaluating primitive coverage.

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。