Unit Testing

Produces comprehensive, well-sourced research reports through iterative refinement using Time-Tested Diffusion methodology. Triggers on "deep research", "thorough analysis", "comprehensive report", "investigate", "due diligence", or when multiple sources are needed to answer complex questions.

ALWAYS USE when working with dbt models, SQL transformations, tests, snapshots, or macros. MUST be loaded before editing any .sql files, dbt_project.yml, or profiles.yml. Enforces dbt owns SQL principle - never parse SQL in Python.

CI/CD pipeline best practices including GitHub Actions, testing, and deployment strategies.

Enforce Rust best practices including ownership patterns, error handling, testing, documentation, and code quality standards. Use when working with Rust code or when the user requests Rust-specific guidance. Includes patterns for cargo tooling, performance optimization, and idiomatic Rust conventions.

Set up GitHub Actions workflows for CI/CD with automated testing, linting, and deployment for Python/UV projects. Use when creating CI pipelines, automating tests, or setting up deployment workflows.

Sensitivity analysis frameworks and assumption-testing methods

Use when building professional installers for desktop applications - covers macOS DMG with app bundles, Windows MSI with WiX, Linux DEB packages, GitHub Actions automation, and SLSA attestations

Palantir 本地文档（en/latest）

Test-Driven Development workflow for .NET with xUnit, FluentAssertions, and NSubstitute. Use when implementing features using TDD practices.

Use when building features with TCA (The Composable Architecture), structuring reducers, managing state, handling effects, navigation, or testing TCA features. Covers @Reducer, Store, Effect, TestStore, reducer composition, and TCA patterns.

Use when editing ANY Neovim configuration including init.lua, plugins, keymaps, LSP settings, or theme configuration. Provides file structure guidance and VHS testing workflow.

Validate spec-implementation-test alignment and convergence. Checks spec completeness, implementation conformance, test coverage, and contract consistency. Use after implementation and tests are complete.

Validates compliance with 9 Constitutional Articles and Phase -1 Gates before implementation.Trigger terms: constitution, governance, compliance, validation, constitutional compliance,Phase -1 Gates, simplicity gate, anti-abstraction gate, test-first, library-first,EARS compliance, governance validation, constitutional audit, compliance check, gate validation.Enforces all 9 Constitutional Articles with automated validation:- Article I: Library-First Principle- Article II: CLI Interface Mandate- Article III: Test-First Imperative- Article IV: EARS Requirements Format- Article V: Traceability Mandate- Article VI: Project Memory- Article VII: Simplicity Gate- Article VIII: Anti-Abstraction Gate- Article IX: Integration-First TestingRuns Phase -1 Gates before any implementation begins.Use when: validating project governance, checking constitutional compliance,or enforcing quality gates before implementation.

Maintain approved technology stack including TypeScript/Python languages, React/Tailwind frontend, Node.js/FastAPI backend, PostgreSQL/Redis persistence, and Ansible infrastructure automation with enforced quality gates. Use this skill when selecting technologies, adding dependencies, configuring tooling, or ensuring infrastructure-as-code practices. Applies to package.json, requirements.txt, CI/CD pipelines, Ansible playbooks, linters, formatters, testing frameworks, and all technology choices requiring documented approval and migration strategies.

Guide experienced developers through REFACTOR phase of TDD cycle - improving code quality while maintaining green tests

Writing high-quality unit tests for JavaScript and TypeScript using Jest. Covers test structure (AAA pattern, USE naming), breaking dependencies (stubs, mocks, dependency injection), testing async code (promises, callbacks, timers), avoiding flaky tests, and test-driven development. Use when writing tests, debugging test failures, refactoring tests for maintainability, or questions about Jest, TDD, mocks, stubs, or test best practices.

Python project scaffolding and development with modern tooling. Use when creating new Python projects, setting up virtual environments, configuring dependencies, or working with Flask web applications. Triggers on mentions of Python setup, uv, Flask, pytest, or project initialization.

Create and maintain Roslyn source generators for compile-time code generation. Use when building incremental generators, designing pipelines with ForAttributeWithMetadataName, creating marker attributes, implementing equatable models, testing generators, or debugging generator performance issues.

Systematic methodology for debugging bugs, test failures, and unexpected behavior.Use when encountering any technical issue before proposing fixes. Covers root causeinvestigation, pattern analysis, hypothesis testing, and fix implementation.Use ESPECIALLY when under time pressure, "just one quick fix" seems obvious, oryou've already tried multiple fixes. NOT for exploratory code reading.

Comprehensive pre-production repository audit for preparing repos for public release. Use when the user wants to perform a "final sweep", "production check", "pre-release audit", or prepare a repository to be made public. Audits metadata files across all project types (Fabric mods, Node/npm, Go, Python, etc.) for correct username/organization, checks README links, and identifies leftover development artifacts like planning docs, test scripts, and temporary files. Interactive cleanup with user confirmation.