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Found 6,581 Skills
Expert-level AI implementation, deployment, LLM integration, and production AI systems
This skill should be used when the user asks to "팀 구성해줘", "team assemble", "전문가 팀으로 해줘", "팀으로 해줘", "swarm", "병렬로 전문가 팀", or wants to decompose a complex task into specialist roles executed via TeamCreate. Also triggers when user describes a task clearly benefiting from parallel expert execution.
STUB — installed at ~/openclaw/skills/skill-creator/SKILL.md
This skill should be used when the user asks to "execute this blueprint", "run the plan", "execute the plan", "start building from the plan", "implement the blueprint", "implement the plan", "continue the plan", "resume execution", or "execute 01_milestone_name.md".
Task-based multi-agent coordination (includes Issue Remediation Loop)
Guide for creating effective skills for Apollo Solutions and Field teams. Use this skill when: (1) users want to create a new skill for this repository, (2) users want to update an existing skill, (3) users ask about skill structure or best practices, (4) users need help writing SKILL.md files.
Use when a task fails, an approach does not work, when encountering errors during implementation, or when tempted to say "I cannot do this" - ensures retry with at least 3 genuinely different approaches before escalating
Invoke this skill when the user says "use btca"
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
Search Korean scholarship announcements across official KOSAF, university, foundation, company, and public-sector sources, extract amount and eligibility, and filter results by school, income band, student level, and organization type. Users may invoke it with the phrase 장학금 검색 및 조회.
Comprehensive map and workflows for the API domain. Triggers when users ask to 'design an API', 'secure the APIs', 'update endpoints', 'view the API ecosystem', or want to see all available API orchestration skills.
Audit experiment integrity before claiming results. Uses cross-model review (GPT-5.4) to check for fake ground truth, score normalization fraud, phantom results, and insufficient scope. Use when user says "审计实验", "check experiment integrity", "audit results", "实验诚实度", or after experiments complete before writing claims.