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Found 10,743 Skills
Expert guidance for building production-ready FastAPI applications with modular architecture where each business domain is an independent module with own routes, models, schemas, services, cache, and migrations. Uses UV + pyproject.toml for modern Python dependency management, project name subdirectory for clean workspace organization, structlog (JSON+colored logging), pydantic-settings configuration, auto-discovery module loader, async SQLAlchemy with PostgreSQL, per-module Alembic migrations, Redis/memory cache with module-specific namespaces, central httpx client, OpenTelemetry/Prometheus observability, conversation ID tracking (X-Conversation-ID header+cookie), conditional Keycloak/app-based RBAC authentication, DDD/clean code principles, and automation scripts for rapid module development. Use when user requests FastAPI project setup, modular architecture, independent module development, microservice architecture, async database operations, caching strategies, logging patterns, configuration management, authentication systems, observability implementation, or enterprise Python web services. Supports max 3-4 route nesting depth, cache invalidation patterns, inter-module communication via service layer, and comprehensive error handling workflows.
Docs as QA: audit doc coverage and freshness, validate runbooks, and maintain documentation quality gates for APIs, services, events, and operational workflows. Includes AI-assisted audits, observability patterns, and automated coverage tracking.
Kubernetes operations including deployment, management, troubleshooting, kubectl mastery, and cluster stability. Covers K8s workloads, networking, storage, and debugging pods. Use when user mentions Kubernetes, K8s, kubectl, pods, deployments, services, ingress, ConfigMaps, Secrets, or cluster operations.
This skill should be used when the user asks to create a new skill, build a skill, make a custom skill, develop a CLI skill, or wants to extend the CLI with new capabilities. Automates the entire skill creation workflow from brainstorming to installation.
Provides comprehensive Google Cloud Platform (GCP) guidance including Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE (Google Kubernetes Engine), Cloud Functions, Cloud Run, VPC networking, load balancing, IAM, Cloud Build, infrastructure as code (Terraform, Deployment Manager), security configuration, cost optimization, and multi-region deployment. Produces infrastructure code, deployment scripts, configuration guides, and architecture designs. Use when deploying to Google Cloud, designing GCP infrastructure, migrating to GCP, configuring GCE instances, setting up Cloud Storage, managing Cloud SQL databases, working with BigQuery, deploying to GKE, or when users mention "Google Cloud", "GCP", "Compute Engine", "Cloud Storage", "BigQuery", "GKE", "Cloud Run", "Cloud Functions", "VPC", "Cloud SQL", or "Google Cloud Platform".
This skill should be used when reviewing pull requests, performing comprehensive code review, analyzing code changes before merge, or when the user asks for thorough/ultra-critical code review. Performs EXTREMELY CRITICAL 6-pass analysis identifying runtime failures, code consistency issues, architectural problems, environment compatibility risks, and verification strategies. Posts structured review as GitHub PR comment. Use when user asks to "review PR", "review this code", "review changes", "check this PR", "analyze PR", "post review", or for Phase 3 of devflow. Supports parallel review mode with multiplier (code-review-3, code-review 6X) for consensus-based reviews. This is an ultra-critical reviewer that does not let things slip and desires only perfection.
Typst Academic Paper Assistant (supports Chinese and English papers, conference/journal submissions). Domains: Deep Learning, Time Series, Industrial Control, Computer Science. Trigger Words (any module can be called independently): - "compile", "compile", "typst compile" → Compilation Module - "format", "format check", "lint" → Format Check Module - "grammar", "grammar", "proofread", "polish" → Grammar Analysis Module - "long sentence", "long sentence", "simplify", "decompose" → Complex Sentence Analysis Module - "academic tone", "academic expression", "improve writing" → Academic Expression Module - "logic", "coherence", "logic", "cohesion", "methodology", "methodology" → Logical Cohesion & Methodology Depth Module - "translate", "translate", "Chinese to English" → Translation Module - "bib", "bibliography", "bibliography" → Bibliography Module - "deai", "de-AI", "humanize", "reduce AI traces" → De-AI Editing Module - "title", "title", "title optimization", "create title" → Title Optimization Module - "template", "template", "IEEE", "ACM" → Template Configuration Module
End-to-end workflow for TypeScript db-core modules: discover schema/model inputs, run DB/document/DAO generation, scaffold DB/document converters, and scaffold procedures with capability-aware validation and safe persistence boundaries. Use when the user asks to regenerate db-core artifacts, generate beans/DAOs from schemas, scaffold or update converters, or scaffold procedure CRUD methods. Trigger keywords: db-core, Db beans, DAO, converter, procedure.
Stakeholder-ready summary document for any Intelligems A/B test. Combines verdict, financial impact, segment analysis, and recommendations into a single shareable brief.
Expert partnership marketing guidance for building and scaling partner programs, co-marketing campaigns, and channel ecosystems. Use when developing partner strategy, creating co-marketing content, designing partner tiers, building affiliate programs, positioning in integration marketplaces, enabling channel partners, planning joint webinars, or structuring revenue sharing. Use for technology partnerships, reseller programs, strategic alliances, and partner relationship management.
Expert-level site reliability engineering, SLOs, incident management, and operational excellence
Write detailed Conventional Commit messages using only the active chat conversation as context. Use when the user asks for commit messages based on discussion history, requests module-scoped commit subjects, or explicitly forbids checking git logs, diffs, or code files.