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収集済み skill 18 件中 18 件を表示しています。
Extract sessions, traces, observations, prompts, and scores from Langfuse via its public API. Use when the user wants to pull/export/analyze Langfuse data (not for instrumenting an app to send traces — see langfuse-observability for that).
原文の言語: 英語
Query Twilio Conversations, Studio Flows, and Monitor/Debugger via the REST API — find conversations by phone/WhatsApp number, read messages and attributes, inspect Studio Flow executions, list debugger alerts. Use when the user wants to look up/inspect/debug…
原文の言語: 英語
Diagnose latency, errors, freezes and scaling issues across Cloud Run + Apigee + Pub/Sub on GCP. Use when the user reports production incidents, latency spikes, partial outages, or asks to "see logs / metrics" in a GCP project.
原文の言語: 英語
LaTeX compilation and Beamer presentation patterns for macOS with TeX Live. Covers pdflatex, latexmk, bibtex, error diagnosis, and Beamer slide authoring.
原文の言語: 英語
CUDA kernel development and GPU optimization patterns — memory hierarchy, occupancy tuning, coalescing, shared memory tiling, warp-level ops, and profiling with Nsight Compute. Use when writing or optimizing CUDA C++ kernels.
原文の言語: 英語
FastAPI architecture patterns, async SQLAlchemy ORM, Pydantic schemas, dependency injection, service layer, background tasks, and production-grade API design.
原文の言語: 英語
FastAPI security best practices — JWT authentication with python-jose, OAuth2, role-based access, CORS, rate limiting, security headers, and input validation.
原文の言語: 英語
FastAPI testing with TDD — pytest-asyncio, httpx AsyncClient, async SQLAlchemy fixtures, polyfactory, mocking external services, and coverage targets.
原文の言語: 英語
Verification loop for FastAPI projects: Alembic migration checks, linting, async tests with coverage, security scans, and deployment readiness before release or PR.
原文の言語: 英語
Firebase Authentication patterns — token verification in FastAPI, custom claims for RBAC, multi-tenant auth, ID token validation, service account setup, and frontend Firebase SDK integration.
原文の言語: 英語
GCP serverless deployment patterns — Cloud Run, Cloud Tasks, Secret Manager, Artifact Registry, Cloud Storage, IAM, and cost-aware architecture for production Python services.
原文の言語: 英語
Intercom integration patterns — webhook event handling, Conversations API, Contacts API, custom inbox channels, operator bot flows, and multi-tenant workspace management.
原文の言語: 英語
Kubernetes production patterns — Deployments, Services, Ingress, ConfigMaps, Secrets, RBAC, HPA, health probes, resource limits, and Helm chart structure for containerized Python/Node services.
原文の言語: 英語
LLM observability with Langfuse — tracing LLM calls, spans, prompt versioning, cost tracking, evaluation datasets, and multi-tenant trace isolation in FastAPI/Python applications.
原文の言語: 英語
LLM engineering patterns — prompt design, structured outputs with instructor, tool use, context management, model selection/routing, cost optimization, streaming, retry logic, and observability.
原文の言語: 英語
MCP (Model Context Protocol) server patterns — FastMCP server design, tool/resource/prompt definitions, authentication, testing, and deployment.
原文の言語: 英語
Multi-tenant SaaS patterns — tenant isolation strategies, row-level security, tenant-aware SQLAlchemy models, RBAC, subdomain routing, and Alembic migrations for shared schema.
原文の言語: 英語
RAG architecture patterns — document ingestion, chunking strategies, embedding models, vector stores, hybrid retrieval, re-ranking, advanced techniques (HyDE, multi-query), and evaluation with RAGAS.
原文の言語: 英語
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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/aleonsa/claude-config.README を読み込めませんでした。リポジトリの Skill 一覧は下で引き続き確認できます。