unifi-mcp-server / rules
Cursor rule294 starsChanged 18 days agoApache-2.0View on GitHub
Development workflow and commit practices
We split this workflow.mdc into the rules it gives an agent
9 rules. About 0 are common, 5 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
Create feature branch: git checkout -b feature/your-feature
- Distinctive: line 14
Read CLAUDE.md and AGENTS.md for project-specific AI assistant guidelines
- Distinctive: line 18
Write tests first (TDD approach)
- Very specific: line 20
Run tests frequently: pytest -v
- Very specific: line 26
Run full test suite: pytest --cov=src --cov-report=term-missing
- Distinctive: line 27
Ensure coverage ≥80%: Check coverage report
- Very specific: line 30
Run pre-commit hooks: pre-commit run --all-files
- Distinctive: line 31
Update documentation if needed
- Distinctive: line 57
Before submitting a PR, verify:
≈ “Common” is an estimate: at least 1 in 5 of the 6,350 Cursor rule files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
--- description: Development workflow and commit practices globs: ["**/*.py", "**/*.md"] alwaysApply: false --- # Development Workflow ## Before Starting Work 1. Pull latest changes: `git pull origin main` 2. Create feature branch: `git checkout -b feature/your-feature` 3. Review existing patterns in similar files 4. Read `CLAUDE.md` and `AGENTS.md` for project-specific AI assistant guidelines ## During Development 1. Write tests first (TDD approach) 2. Implement feature following patterns above 3. Run tests frequently: `pytest -v` 4. Check types: `mypy src/` 5. Format code: `black src/ tests/` and `isort src/ tests/` ## Before Committing 1. Run full test suite: `pytest --cov=src --cov-report=term-missing` 2. Ensure coverage ≥80%: Check coverage report 3. Run linter: `ruff check src/ tests/ --fix` 4. Type check: `mypy src/` 5. Run pre-commit hooks: `pre-commit run --all-files` 6. Update documentation if needed ## Commit Message Format Follow Conventional Commits: ``` <type>: <short summary> <optional body> ``` Types: `feat`, `fix`, `docs`, `test`, `refactor`, `style`, `chore` Examples: ``` feat: add DPI statistics tool for bandwidth analysis fix: correct device restart timeout handling docs: update API.md with WiFi management tools test: add integration tests for port forwarding refactor: simplify client blocking logic ``` ## Code Quality Checklist Before submitting a PR, verify: - [ ] All tests pass (`pytest`) - [ ] Code coverage ≥80% (`pytest --cov`) - [ ] Type checking passes (`mypy src/`) - [ ] Linting passes (`ruff check src/ tests/`) - [ ] Code formatted (`black`, `isort`) - [ ] Security checks pass (`bandit -r src/`) - [ ] Pre-commit hooks pass - [ ] Documentation updated (docstrings, API.md) - [ ] CHANGELOG.md updated for user-facing changes - [ ] No hardcoded secrets or API keys - [ ] Audit logging added for mutating operations
Where files are headingNew Cursor rule files have more rules about planning and tracking tasks, and fewer about code style.
Of the Cursor rule files we read, the 3,978 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository52 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .agents/skills/fastmcp/CLAUDE.mdCLAUDE.md
- CLAUDE.mdCLAUDE.md
- .claude/skills/fastmcp/CLAUDE.mdCLAUDE.md
- .cursor/rules/common-mistakes.mdcCursor rule
- .cursor/rules/core-principles.mdcCursor rule
- .cursor/rules/environment-setup.mdcCursor rule
- .cursor/rules/mcp-tools.mdcCursor rule
- .cursor/rules/project-context.mdcCursor rule
- .cursor/rules/README.mdCursor rule
- .cursor/rules/unifi-api.mdcCursor rule
- FastMCP DevelopmentSkill
- mcp-builderSkill
- source-command-build-dockerSkill
- source-command-check-depsSkill
- source-command-cleanSkill
- source-command-docsSkill
- source-command-formatSkill
- source-command-lintSkill
- source-command-prSkill
- source-command-securitySkill
- source-command-setupSkill
- source-command-testSkill
- source-command-unifi-api-docs-update-2Skill
- source-command-unifi-api-docs-updateSkill
- source-command-unifi-mcp-add-toolSkill
- source-command-unifi-mcp-release-prepSkill
- source-command-unifi-mcp-test-coverageSkill
- source-command-unifi-mcp-update-docsSkill
- unifi-cloud-fleet-toolsSkill
- unifi-mcp-tool-builderSkill
- unifi-network-config-toolsSkill
- unifi-protect-toolsSkill
- unifi-security-toolsSkill
- FastMCP DevelopmentSkill
- mcp-builderSkill
- unifi-cloud-fleet-toolsSkill
- unifi-mcp-tool-builderSkill
- unifi-network-config-toolsSkill
- unifi-protect-toolsSkill
- unifi-security-toolsSkill
- unifiSkill
- unifi-channel-planningSkill
- unifi-cloud-fleet-toolsSkill
- unifi-devicesSkill
- unifi-mcp-tool-builderSkill
- unifi-network-config-toolsSkill
- unifi-networkSkill
- unifi-protect-toolsSkill
- unifi-securitySkill
- unifi-security-toolsSkill
- unifi-systemSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

