Use this skill when designing, generating an MVP blueprint for, auditing, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, permissions, system prompts, planning, goals, context…
Ultra-compressed communication mode. Cuts output tokens 65% (measured) by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens"…
Use when performing any file-changing development task in a repository, including code, tests, documentation, configuration, schemas, generated artifacts, implementation, fixes, refactors, finishing, or verification.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use when starting work in a project repository that has no agent harness or an incomplete one (no root AGENTS.md canon, no .harness/ directory, no gates, no harness.lock), when a SessionStart hook reports a missing or outdated harness, or when the owner asks to set a project up for agent-driven development. Detect…
Use when finishing project-scoped work that changed project state or produced a completed audit, diagnosis, investigation, or decision, including tasks with or without a tracker.
Use when phrasing or structuring any task for Claude Code — a vague or underspecified request that needs shaping, the user asks "как сформулировать" / "how should I ask for X", starting an unfamiliar kind of work (onboarding a repo, incident, migration, release, spec, review), writing prompts for subagents/workflows…
Use when writing an implementation plan for a multi-step coding task before execution: bite-sized tasks, exact paths, complete code, verification steps per task.