Architecture Decision Agent Skill
Conducts and records a verifiable ingestion architectural decision. Use when a choice alters pipeline boundaries, chunk/index contracts, identity, data, source integration, deployment, or operation with meaningful reversal cost.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/Azure/GPT-RAG --skill architecture-decisionWhat comes with it
1 300 bytes besides the instructionThe instruction itself
1 sections, as written by the authorIngestion architectural decision
- Load the relevant
engineering-principlesreferences. - Define the retrieval or operator outcome, constraints, affected
repositories, and up to five prioritized characteristics with measures.
- Compare at least two viable alternatives and not changing.
- Evaluate document security, data contracts, index compatibility, chunk
quality, throughput, memory, cost, failure recovery, migration, and
reversibility.
- Record the decision under
docs/adr/using
the ADR template.
- Define fitness functions, adoption order, rollback or reindex strategy,
and a review trigger.
Do not turn a tool or Azure service preference into an architectural
requirement. When evidence is missing, record a time-bounded investigation
and its decision criterion rather than guessing.
Other skills for the same job
different authors, same section of the catalogue
Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, workflows resume exactly where they left off. This skill covers the platforms (n8n, Temporal, Inngest) and patterns (sequential, parallel, orchestrator-worker) that turn brittle scripts into production-grade automation. Key insight: The platforms make different tradeoffs. n8n optimizes for accessibility
Automate Cloudinary media management including folder organization, upload presets, asset lookup, transformations, and usage monitoring through natural language commands
You are a workflow automation expert specializing in creating efficient CI/CD pipelines, GitHub Actions workflows, and automated development processes. Design automation that reduces manual work, improves consistency, and accelerates delivery while maintaining quality and security.
Server management principles and decision-making. Process management, monitoring strategy, and scaling decisions. Teaches thinking, not commands.
Create a formal specification for an existing GitHub Actions CI/CD workflow, optimized for AI consumption and workflow maintenance.
Build and operate reproducible genomics workloads on DNAnexus with the dx CLI, dxpy, apps/applets, native workflows, dxCompiler, and Nextflow. Use for DNAnexus data transfers, dxapp.json development, execution monitoring, workflow import, and project automation.
Search across company knowledge bases (Confluence, Jira, internal docs) to find and explain internal concepts, processes, and technical details. When an agent needs to: (1) Find or search for information about systems, terminology, processes, deployment, authentication, infrastructure, architecture, or technical concepts, (2) Search internal documentation, knowledge base, company docs, or our docs, (3) Explain what something is, how it works, or look up information, or (4) Synthesize information from multiple sources. Searches in parallel and provides cited answers.
Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.
How to use it
Take azure/architecture-decision from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.