Use this skill when you need to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data.

Apply Google Style documentation standards to Python, Go, and Terraform code. Use when writing or reviewing code that needs docstrings/comments, when asked to "document this code", "add docstrings", "follow Google Style", or when improving code documentation quality. Supports Python docstrings, Go comments, and Terraform variable/output descriptions. Enforces consistent, professional documentation standards.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Generate comprehensive, professional project documentation structures including README, ARCHITECTURE, USER_GUIDE, DEVELOPER_GUIDE, and CONTRIBUTING files. Use when the user requests project documentation creation, asks to "document a project", needs standard documentation files, or wants to set up docs for a new repository. Adapts to Python/Go projects and OpenSource/internal contexts.

Documentation-first development methodology. The goal is AI-ready documentation - when docs are clear enough, code generation becomes automatic. Triggers on "Build", "Create", "Implement", "Document", or "Spec out". Version 3.5 adds Phase 2.5 Adversarial Review and renames internal verification to Spec Gate (structural completeness). Clarity Gate is now a separate standalone tool for epistemic quality.

All changes for the release (dependency updates, bug fixes, etc.) should already be merged to `main`.

[APP从启动到显示流程](https://www.jianshu.com/p/08855d69c0bf)

Tailwind CSS v4 performance optimization and best practices guidelines (formerly tailwindcss-v4-style). This skill should be used when writing, reviewing, or refactoring Tailwind CSS v4 code to ensure optimal build performance, minimal CSS output, and correct usage of v4 features. Triggers on tasks involving Tailwind configuration, @theme directive, utility classes, responsive design, dark mode, container queries, or CSS generation optimization.

Executes production deployment workflow by promoting validated staging builds to production with semantic versioning, health checks, and release tagging. Use when running /ship-prod command, deploying to production after staging validation, or promoting staging builds to production environment.

Provides standard operating procedures for the /specify phase including feature classification (HAS_UI, IS_IMPROVEMENT, HAS_METRICS, HAS_DEPLOYMENT_IMPACT), research depth determination, clarification strategy (max 3, informed guesses for defaults), and roadmap integration. Use when executing /specify command, classifying features, generating structured specs, or determining research depth for planning phase. (project)

Detect and warn about breaking API/schema changes before implementation. Auto-trigger when modifying API routes, database schemas, or public interfaces. Validates changes against api-strategy.md versioning rules. Suggests migration paths for breaking changes. Prevents removing endpoints, changing request/response formats, dropping database columns, modifying function signatures without deprecation.

Create optimized prompts for Claude-to-Claude pipelines with research, planning, and execution stages. Use when building prompts that produce outputs for other prompts to consume, or when running multi-stage workflows (research -> plan -> implement).

Completes feature/epic workflows after deployment with comprehensive walkthrough generation for epics (v5.0+), roadmap updates, artifact archival, documentation, and branch cleanup. Use after /ship-prod, /deploy-prod, or /build-local completes, or when user asks to finalize. (project)

Executes implementation tasks using Test-Driven Development, prevents code duplication through anti-duplication checks, and maintains quality through continuous testing. Use when implementing features from tasks.md, during the /implement phase, or when the user requests TDD-based implementation. (project)

Detect and prevent hallucinated technical decisions during feature work. Auto-trigger when suggesting technologies, frameworks, APIs, database schemas, or external services. Validates all tech decisions against docs/project/tech-stack.md (single source of truth). Blocks suggestions that violate documented architecture. Requires evidence/citation for all technical choices. Prevents wrong tech stack, duplicate entities, fake APIs, incompatible versions.

Before implementing new code (endpoints, components, services, models), search the codebase for existing patterns to reuse. Prevent code duplication by finding and suggesting similar implementations. Auto-trigger when user asks to create, implement, add, or build new functionality.

Enforce atomic task status updates through task-tracker commands only. Prevent manual edits to NOTES.md and tasks.md that break synchronization. Auto-trigger when detecting Edit/Write attempts to task files, task completion mentions, or status update discussions. Auto-convert manual edit attempts to equivalent task-tracker commands. Validate task-tracker usage and auto-fix common mistakes.

Validates production readiness through performance benchmarking, accessibility audits, security reviews, and code quality checks. Use after implementation phase completes, before deployment, or when conducting quality gates for features. (project)

Insert schedule rows into the local database (schedules) from a JSON array. Use when bulk-loading schedule entries with prompt_name, input_value, and scheduled_date via scripts/add_schedules.py.

Insert or read behavior log rows in the local database (behavior_logs). Use when recording a good/bad behavior entry, attaching a Pavlok API response JSON, adding a coach comment, or fetching recent logs via scripts/behavior_log.py.