Team conventions for Python development — credentials, API clients, LLM response parsing, testing patterns, and data pipeline structure. Covers dotenv loading, retry logic, secret validation, and pipeline anti-patterns.
The English summary is being prepared. Showing the original description.
See how to installReview the instructions the agent will receive before you install.
Unified conventions for team Python projects: credential management, API clients, testing discipline, and data pipeline structure. Supplements standard patterns with team-specific rules.
.env filesCredentials:
.env.example.APIs:
Tests:
random_state=42. Target 80%+ coverage. Test behavior, not internals.Pipelines:
Read references/credentials.md, references/api-clients.md, references/testing.md, and references/pipelines.md for full examples and anti-patterns.
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
User asks for design, planning, or approach exploration before implementation. Covers new features, components, refactors, or architecture decisions. Creates design docs and proposes approaches with trade-offs.
The English summary is being prepared. Showing the original description.
Use when starting work in a repository under repositories/ that may lack CI configuration. Detects missing CI workflows (GitHub Actions, GitLab CI, CircleCI) and alerts the user to add one. Skips repos marked as research-only.
The English summary is being prepared. Showing the original description.
Use when the user asks to measure command execution time or optimize a feedback loop. Records explicit measurements and recommends faster alternatives such as unit tests versus integration tests. It is opt-in; it does not run on every command.
The English summary is being prepared. Showing the original description.
Measurement-driven code refactoring — profile before changing, measure after, keep only if metrics improve. Covers complexity reduction, extraction patterns, and bulk refactoring for mechanical changes across many files.
The English summary is being prepared. Showing the original description.
Scan projects for credential leaks, secrets in code, insecure patterns, LLM API key exposure, PII leakage to external AI services, and .env/.gitignore misconfigurations. Especially useful for data and API integrations, regardless of implementation language.
The English summary is being prepared. Showing the original description.
Use when committing or pushing changes and the repository needs a version bump. Analyzes commits using conventional commit prefixes to determine whether the next release is a major, minor, or patch increment. Also use when the user asks about versioning, release planning, or changelog generation.
The English summary is being prepared. Showing the original description.