Sources and update policy

Use this page when you want to check a setup detail, adapt an example, or prepare a session for colleagues. It collects the official documentation behind the agent setup guide and notes what each source helps explain.

Source review date: September 5, 2026. We retrieved the relevant pages to check modes, tool access, paths, configuration fields, instruction discovery, and documented capabilities. The examples use those formats with tasks and file paths from this repository.

A feature described in documentation still needs a hands-on check in the client you plan to use. We distinguish those two kinds of evidence throughout the guide. Installation and sign-in links lead to the provider’s current instructions because account and operating-system requirements can change.

Shared concepts

Source Used for
Agent Skills specification Skill structure, required metadata, and optional resources
Model Context Protocol introduction Connecting clients to external tools and context
MCP server concepts Distinguishing tools, resources, and prompts
Building effective agents A foundational explanation of tool use and feedback; originally published in 2024
Context engineering Context retrieval, conversation compaction, and notes for longer tasks

Codex

Source Used for
CLI setup Installation, sign-in, and launching in a project
Desktop quickstart Selecting the coding experience in the desktop app
CLI commands Planning, permissions, model selection, and inspecting connected tools
Desktop commands Planning in the desktop interface
Configuration basics Shared .codex/config.toml, personal configuration, trust, and precedence
Advanced configuration Project configuration limits, relative paths, and personal state
Configuration reference Supported model-provider fields and API compatibility
Permissions Beta permission profiles and their incompatibility with mixed sandbox settings
AGENTS.md discovery Project hierarchy, personal instructions, and overrides
Skills Project/user locations and explicit or implicit use
Subagents and custom agents TOML definitions, inherited settings, and delegation
Approvals and security Sandbox, approvals, external tools, and hosted execution
Plugin packaging Distributing reusable workflows and connections

Claude Code

Source Used for
Quickstart Installation, authentication, and first session
Permission modes Entering Plan, exploration tools, plan approval, and implementation access
Settings Project and personal configuration locations
Model configuration Session model choice, saved defaults, aliases, and planning/execution routing
LLM gateways Provider connections and supported model scope
Tools reference File reading, editing, shell execution, and other tools
Project memory CLAUDE.md locations, imports, context inspection, and enforcement limits
Skills Discovery paths and invocation
Subagents Markdown definitions and restricted reviewer tools
Hooks reference Lifecycle events and their limits

GitHub Copilot

Source Used for
CLI quickstart Current CLI setup
CLI command reference CLI planning and permission commands
CLI configuration directories Current project and personal settings files
VS Code session targets and roles Local Ask/Plan/Agent roles, execution locations, and handoffs
VS Code planning Reviewing a plan and starting implementation
VS Code tools Enabling tools and inspecting their results
VS Code approvals Tool approval controls and their relationship to sandboxing
VS Code language models Model selection, external providers, and tool-calling support
Changing the Copilot model Session model selection across clients
Customization cheat sheet Instructions and feature support in different clients
Adding agent skills Supported locations, skill selection, and package review
About custom agents Agent profiles and project scope
Custom agent configuration Front matter, tool aliases, and differences between clients

Cursor

Source Used for
Quickstart Current setup
Ask mode Orientation and code explanation
Plan mode Discussing a proposal and starting a build
Agent Editing, command execution, and reviewing changes
Run Modes Approval settings for local execution and differences from cloud operation
Available models Selecting a model and checking availability
API keys Personal provider keys and feature limitations
Rules AGENTS.md and .mdc rule discovery
Skills Shared/native skill paths and remote availability
Subagents Reviewer format, inherited model, and restricted writes
Cloud Agents Hosted environments and review artifacts

Gemini CLI

Source Used for
Getting started Installation and authentication options
Configuration reference Project and personal settings locations
Settings dialog Inspecting the configuration during the lesson
Model selection Manual and automatic model choice and subagent differences
Authentication Access through Google sign-in, Gemini API keys, or Vertex AI
Plan Mode Interactive planning, allowed tools, model routing, and headless differences
Planning tools Plan approval and the transition to implementation
Policy engine Rules for allowing, denying, or asking about tool use
Sandboxing Isolation of tool execution
GEMINI.md context Imports, custom filenames, and context inspection
Skills Shared/native locations, activation, and management commands
Subagents Agent files, tool restrictions, and invocation
Behavioral evaluations Distinguishing agent-workflow checks from ordinary code tests

University policy and lab data

These sources support lab data and university policy. We reviewed the public guidance; the detailed Sensitive Data Guide service listings require U-M sign-in and were not inspected. Check those listings for the exact service and data type before a real study task.

Source Used for
AI and U-M data Service agreements, permitted data use, and where to ask for help
Data classification examples PHI, identifiable records, and context-dependent sensitivity
Claude Code via U-M GPT Toolkit Eligibility, university setup, and the explicit ePHI exclusion
ITS AI FAQ Eligibility details that need checking against the service page and Toolkit portal
Secure coding at U-M Human review and risk in logs, dependencies, and deployment
AI in human research Research use, study documentation, and IRB amendment scope
Appropriate AI use University responsibilities, review, and acknowledgment of AI assistance
Incident reporting Prompt reporting and unit-specific support routes

Maintaining these pages

A short rehearsal is useful before teaching a session or publishing a release. Focus on the clients you will actually demonstrate:

  1. Reopen the pages for installation, mode selection, discovery paths, configuration examples, permissions, and feature availability. A working link is only part of the check; make sure its content still supports the instructions.
  2. Try orientation, a plan-to-implementation handoff, skill discovery, and one small review in each client you intend to show. Record the version, model, selected modes and permissions, whether you used an editor, CLI, or hosted service, the operating system, and the result. These details will help a colleague troubleshoot a different outcome.
  3. Update the review date for the material you actually checked. If a feature is unavailable or its documentation no longer supports an example, explain the limitation and remove the unsupported instructions.
  4. Keep the exercise’s agreed behavior the same while updating client setup files. After changing filenames or navigation, recheck the examples and links.

The agent workflow discussion brings these documented features together and suggests ways to explore them in this repository. The sources establish what the tools describe as available. Claims about productivity, model rankings, scientific validity, or how much human review a task needs would require additional evidence.