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Found 1,650 Skills
Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.4 review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.
Add LangWatch tracing and observability to your code. Use for both onboarding (instrument an entire codebase) and targeted operations (add tracing to a specific function or module). Supports Python and TypeScript with all major frameworks.
Read and analyze arXiv papers by fetching LaTeX source, listing sections, or extracting abstracts. Use when the user mentions arXiv, research papers, preprints, paper IDs like 2301.xxxxx, or wants to read academic publications.
Cost-conscious Claude Code mode. Reduces output tokens 40-70% and overall costs 30-60% by enforcing concise responses, smart model routing, and efficient workflow patterns. Keeps full technical accuracy. Activate with /cost-mode or "enable cost mode". Auto-triggers on mentions of budget, cost, tokens, or spending.
Causal digital twin for marketing simulation — predict campaign ROI, run counterfactual KOL swaps, and audit causal graphs before spending a dollar.
GANG validator skill. You are a validator, performing rule-based verification to check if the worker's handoff meets the val standards and issuing a verdict.
Generate and curate evaluation datasets — structured generation via dimensions-tuples-NL, quick from description, expansion from existing data, plus dataset maintenance through deduplication, rebalancing, and gap-filling. Use when creating eval data, expanding test coverage, or cleaning datasets. Do NOT use when sufficient real production data exists (use analyze-trace-failures instead). Do NOT use for evaluator creation (use build-evaluator).
Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
Semantic security scanner for OpenClaw skills. Detects prompt injection, data exfiltration, and hidden instructions that traditional code scanners miss. Use when user asks to scan skills, check skill safety, or run a security audit.
AI Agent long-term memory system with cross-session, cross-project persistence. Triggers: - /remember - Store memories - /recall - Search memories - /forget - Delete/archive memories - /memory-status - Check status - When needing to persist important conversation insights - When sharing user preferences across projects
Query decomposition for multi-concept retrieval. Use when handling complex queries spanning multiple topics, implementing multi-hop retrieval, or improving coverage for compound questions.
VCR.py HTTP recording for Python tests. Use when testing Python code making HTTP requests, recording API responses for replay, or creating deterministic tests for external services.