v2.1.0: AI Agent Governance and Conventions
This release covers AI agents as governed, first-class repository participants: how to govern them, and how to write conventions for them.
Highlights
- Added the AI Agent Governance guide, covering three agent identity models, permission scoping, PR approval rules, CI triggers with secrets isolation, and traceability, with hosted agent restrictions grounded in the official GitHub documentation
- Added the AGENTS.md template, copyable into team repositories, with setup commands, required verification, boundary rules, commit conventions, and a mapping table to tool-specific instruction files
- This repository now follows its own recommendations: a root AGENTS.md, AI-assisted contribution rules in the contributing guides, and documentation checks that include AGENTS.md
- Expanded Multi-Agent Branch Strategy with executable workflows: comparing experiment branches, integrating the winning solution, handling same-file collisions, and cleaning up losing branches
- Expanded Stacked PR for AI-Generated Changes with native Git stack operations (
--update-refs, rebase --onto, --force-with-lease) and Graphite CLI core commands
- All content above is maintained as Chinese and English pairs
Why This Release
v2.0 set the direction toward AI-native development workflows, but agent governance and collaboration conventions were still missing.
AI agents are already creating branches, opening PRs, and triggering CI. v2.1.0 upgrades them from diff generators to governed participants: maintainers get a governance configuration checklist, teams get a copyable AGENTS.md template, and developers get executable commands for multi-agent work and PR stacks.
Validation
python3 scripts/check-docs.pypython3 scripts/check-links.py --no-externalgit diff --check