WeChat Mini Program AI Collaboration Rules Generator (AGENTS.md)
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About this skill
Problem This Skill Addresses
When AI assists with WeChat Mini Program development, the failure mode is often not missing syntax, but uncontrolled behavior: refactoring unrelated modules, embedding secrets in code, running irreversible actions without confirmation, or missing reference updates after renames. In mini program projects, the risk grows with subpackages, Canvas, locked templates, and multiple feature boards.
How It Works
The skill turns collaboration rules into a generated and inspectable project file:
- Renders an
AGENTS.mdat the project root for AI to read at the start of each session. - Encodes baseline rules for safety, stability, communication, minimal changes, and reference synchronization, with high-priority restrictions on payments, deletion,
.env, and Git commits. - Adds stronger constraints for subpackages and Canvas work, such as naming isolation, core template locking, Canvas sizing, and draw-order rules.
- Supports
--checkto scan for hard-coded secrets or.envfiles in version control. - Uses
--self-testto re-read the generated rules and verify required principles are present.
Boundaries and Notes
This skill provides a general collaboration baseline, not project-specific MVP scope, API inventories, or business documentation indexes. The default tech stack assumptions cover WeChat Mini Program, FastAPI, and a database; change the stack-specific section when migrating. Human review and delivery acceptance remain necessary.
Use Cases
- Set up a new WeChat Mini Program repository by generating an `AGENTS.md` that tells AI to follow safety and minimal-change rules.
- Review a subpackage refactor by checking naming isolation so AI does not touch variables or functions from another board.
- Run a pre-delivery check for hard-coded secrets, exposed tokens, or `.env` files committed to version control.
- Guide Canvas template work with A4 sizing, draw-order, font-fallback, and export constraints before asking AI to implement.
Best For
- Tech leads owning WeChat Mini Program projects who want AI safety and change-control rules stored in the repository.
- Front-end engineers working on subpackage tool modules who need to avoid cross-board naming collisions and accidental edits.
- Front-end developers maintaining Canvas homework templates who need A4 sizing, draw order, and font-fallback constraints.
- Engineering managers approving AI-assisted delivery who want pre-delivery checks for secrets, `.env` files, and Git commit risks.
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