Rewrite user's original prompt by integrating their critique of the agent's failed response.
Deconstruct LLM "neuroslop" — machine clichés, puffery, weasel-wording, Markdown abuse, rhythmic monotony. Use when user asks to humanize, dehumanize-AI, очистить от нейрослопа, депорезать, redact AI-generated copy, edit a draft from ChatGPT/Claude/Gemini, or refine corporate/PR/wiki text that "sounds AI".
Discover and merge useful features from sibling forks into the user's fork. Invoke only on explicit user request via /fork-merge with a fork URL.
Git workflow patterns — branching, committing, rebasing, conflict resolution. Use when working with git operations.
Relentlessly interview user to stress-test a plan/design.
Generate conversation handoff document for the next agent session.
Generate a comprehensive CLAUDE.md for the current repository — first runs Anthropic's /init for a baseline, then restructures with an extended standardized template (sections, security flows, anti-patterns, data models, CI/CD, common issues). Use when a repo has no CLAUDE.md or you want to enrich an existing one with extended structure.
Practical playbook for maximizing prompt cache hit rate and minimizing token spend on LLM/agentic systems (Anthropic, OpenAI, Google Gemini, self-hosted vLLM). Covers prompt structure rules, multi-turn cache breakpoint placement, tool definition stability, dynamic content handling, TTL choice, multi-tenant isolation, and known anti-patterns.