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Found 459 Skills
Loads orchestrate mode — a disciplined delivery loop that enforces BDD specs in specs/, real integration tests (no mocks), PR CI and CodeRabbit babysitting, and mandatory end-user QA via computer-use or CLI dogfooding before anything is considered done. Use when starting any non-trivial implementation task, feature build, or delivery where you want the work driven from spec to proven-shipped state rather than stopping at "tests pass".
Cross-model second opinion from Google Gemini — a different AI reviewing the same changes, with deep Google ecosystem knowledge. Three modes: review (pass/fail gate for Google Ads campaigns, SEO metadata, or code), challenge (adversarial stress-test that tries to break your changes), and consult (open Q&A with Gemini on Google Ads strategy, SEO best practices, or implementation questions). Use when the user says "gemini review", "ask gemini", "gemini challenge", "second opinion from gemini", "consult gemini", "stress test with gemini", "what would gemini say", "cross-model review", or "get another opinion". Voice aliases: "gem", "gemini check". Especially useful for Google Ads changes, SEO metadata updates, campaign structure decisions, keyword strategies, and bid/budget changes — Gemini has native Google ecosystem knowledge that complements Claude's analysis.
Portable Zod schema design and validation guidance. Default to `zod/mini` for new work and preserve established classic `zod` surfaces. Use when Codex needs to create, extend, refactor, or review Zod schemas; choose strict or loose object contracts; model nullability, unions, intersections, recursion, or runtime-validated values; or debug surprising Zod behavior and serialization boundaries.
Proceed with implementation based on the TODO list in Spec.md. Execute review→check→commit after each task is completed.
Use when user asks to leverage claude or claude code to do something (e.g. implement a feature design or review codes, etc). Provides non-interactive automation mode for hands-off task execution without approval prompts.
Consult an advisory council of three AI personas — Cato (skeptic), Ada (optimist), Marcus (pragmatist) — backed by different frontier LLM agents (Gemini, Claude, Codex). Each persona runs as a separate agent process with full repo context and returns independent feedback. Use when the user says "/council", asks for a second opinion, wants feedback on code changes, needs a premortem, wants to pressure-test a decision, or asks "what do you think about this approach?" Claude may also proactively suggest consulting the council before major architectural decisions, risky deploys, or ambiguous trade-offs (but should ask for user approval first).
Detect common code smells and anti-patterns providing feedback on quality issues a senior developer would catch during review. Use when user opens/views code files, asks for code review or quality assessment, mentions code quality/refactoring/improvements, when files contain code smell patterns, or during code review discussions.
Code Style Conventions. Use when writing, editing, or reviewing Python code. This includes conventions such as type hints, Decimal precision, docstrings, module organization, etc. Enforces type hints, Decimal precision, docstrings, and module organization.
Game development expert including DragonRuby, Unity, and game mechanics
Security-related rules for Tauri application development.
Execute a plan file or Beads epic systematically with git setup, task tracking, quality checks, and commit workflow. Use when implementing a plan, working through a spec, following documented steps, or executing a Beads issue ID (e.g., bd-123, gno-45, app-12).
Multi-agent PR and code review workflow for projects using multiple AI assistants (Claude, GitHub Copilot/Codex, Gemini Code Assist). Use when working with pull requests, code reviews, commits, or addressing review feedback. Teaches how to check all feedback sources (conversation, inline, reviews), respond to inline bot comments, create Fix Reports, and coordinate between agents that use different comment formats. Critical for ensuring no feedback is missed from external review bots.