GitHub
ai-model-registry
Centralized management of machine learning models throughout their lifecycle, including versioning, metadata, and production deployment.
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Lifestyle AI Skills
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GitHub
tech-stack-selection
Systematic approach to choosing technologies, frameworks, and tools based on requirements, team capabilities, and long-term sustainability.
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GitHub
llm-token-optimization
See the main LLM Cost Optimization skill for comprehensive coverage of token economics and optimization strategies.
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GitHub
architecture-decision-records-adr
Documenting significant architectural decisions with context, consequences, and rationale for future reference.
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GitHub
where-to-find-what
A quick lookup guide for navigating a repository: where to find endpoints, business logic, models, tests, configs, docs, scripts, plus search patterns and commands
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GitHub
roadmap-planning
Comprehensive guide to creating, communicating, and maintaining technical and product roadmaps for strategic alignment and stakeholder communication
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GitHub
communication-templates
Pre-written message templates for incident communication across different channels and severity levels.
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GitHub
schema-drift-detection
Detecting and managing schema changes that can break data pipelines and downstream consumers.
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GitHub
pricing-and-usage-meters
See the main Usage-Based Pricing skill for comprehensive coverage of metering and billing implementation.
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GitHub
llm-security-red-teaming
Comprehensive guide to securing LLM applications including prompt injection prevention, jailbreak detection, guardrails, and red teaming methodologies
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GitHub
user-interviews
Comprehensive guide to conducting effective user interviews for problem discovery, solution validation, and continuous learning
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GitHub
tool-permission-model
Comprehensive guide to implementing permission systems for AI agent tools including RBAC, approval workflows, and security policies
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GitHub
repository-automation-scripts
Automated scripts for common repository tasks including setup, cleanup, dependency updates, and maintenance.
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GitHub
llm-function-calling
Implementing function calling (tool use) with LLMs for structured outputs and external integrations.
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GitHub
backfill-and-reconciliation-playbook
Playbook สำหรับ backfill historical data และ reconcile inconsistencies ระหว่าง data sources
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GitHub
sla-slo-and-slis
Comprehensive guide to Service Level Agreements, Objectives, and Indicators for measuring and maintaining system reliability
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GitHub
cost-observability-and-monitoring
Techniques for gaining visibility into cloud spending, attributing costs to business units, and detecting financial anomalies.
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GitHub
model-serving-inference
Comprehensive guide to deploying and serving LLM models including optimization, batching, caching, and production infrastructure
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GitHub
access-audit-and-reviews
Comprehensive guide to access audits, periodic reviews, anomaly detection, and segregation of duties for compliance and security.
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GitHub
retention-and-archival
Policy และ automation สำหรับ data retention, archival และ deletion ตาม compliance requirements
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GitHub
prompting-patterns
Comprehensive guide to effective prompt engineering patterns including few-shot, chain-of-thought, ReAct, and advanced prompting techniques
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GitHub
pii-detection
Comprehensive guide to detecting Personally Identifiable Information (PII) across systems, databases, and logs using regex patterns, NER models, and automated scanning tools.
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GitHub
retrieval-playbook-for-ai
กลยุทธ์การ retrieve context ให้ AI อย่างมีประสิทธิภาพ - เลือกอะไร ไม่เลือกอะไร และจัดลำดับอย่างไร
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GitHub
api-versioning-strategies
Comprehensive guide to API versioning approaches for maintaining backward compatibility.
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