Results for “protocol-statistics”

Use when selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.

Apply Optionals, Protocols, Extensions, and Type Safety patterns in Swift. Use when working with Swift Optionals, Protocols, Extensions, or type-safe APIs.

rate(http_requests_total[5m])

Use to define handoff standards for support transfers and to measure whether context survives the handoff — cold vs warm, required fields, and re-ask rate after transfer. Trigger for "transfer protocol", "warm handoff", "customers repeat themselves after transfer", "ping-pong between teams", "what should agents include when transferring", handoff quality, or re-ask rate after escalation.

session-stats

Deploys anomaly detection for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications.

Curation-Bench Protocol (skill-grounded)

Provides production-grade FastAPI development patterns including project structure, Pydantic v2 schemas, dependency injection, async handlers, authentication, authorization, transactional service layers, and testing with httpx and pytest.

Structured logging strategy — levels, correlation IDs, context propagation, PII avoidance. Use when designing a logging approach, reviewing log statements, setting up log aggregation (ELK, Loki, CloudWatch), adding correlation IDs to a distributed system, or deciding what to log and what to keep out.

Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API.

OpenTelemetry observability patterns: traces, metrics, logs, context propagation, OTLP export, Collector pipelines, and troubleshooting

Rep Operating Standards — Canonical (Heath-set 2026-06-07)

用于查询优化、模式设计、索引和安全性的PostgreSQL数据库模式。基于Supabase最佳实践。

Proactive self-monitoring of infrastructure, services, and health. Tracks disk/memory/load, service health, cron job status, recent errors. Auto-fixes safe issues. Triggers on: health check, heartbeat, monitor status, service status, infrastructure check.

Batch Signal Isolation with Recipe-Driven Processing