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Found 156 Skills
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Control Room template for managing Hermes agents from one VPS agent to specialist teams and orchestrated workflows
Unified test-fix pipeline combining test generation (session, context, analysis, task gen) with iterative test-cycle execution (adaptive strategy, progressive testing, CLI fallback). Triggers on "workflow:test-fix-gen", "workflow:test-cycle-execute", "test fix workflow".
Discourse 패턴으로 다관점 리뷰를 수행한다. Tech Spec 리뷰와 에픽 통합 코드 리뷰를 모두 처리하며, 쟁점 해소 프로토콜에 따라 합의/미합의를 분리한다.
Launch multiple sub-agents in parallel to execute tasks across files or targets with intelligent model selection and quality-focused prompting
Execute a task with sub-agent implementation and LLM-as-a-judge verification with automatic retry loop
Resolve all pending CLI todos using parallel processing, compound on lessons learned, then clean up completed todos.
Route tasks to optimal agents using learned patterns, model recommendations, and confidence scoring
Design and build multi-agent harness architectures for long-running AI application development. GAN-inspired Generator-Evaluator pattern, Sprint Contract negotiation, context management, quality criteria calibration. Based on Anthropic Engineering patterns. Use when: "build a harness", "multi-agent architecture", "agent orchestration", "generator-evaluator", "long-running app", "harness design", "agent pipeline", "quality evaluation loop", "sprint contract", "build app with agents", "Claude Agent SDK architecture", or when building complex full-stack apps that need planning → generation → evaluation cycles. Also use when discussing context degradation, self-evaluation bias, or assumption testing in AI workflows.
Orchestrates infrastructure cost estimation with tier-based or custom TPS sizing. Offers pre-configured tiers (Starter/Growth/Business/Enterprise) or custom TPS input. Skill discovers components, asks shared/dedicated for EACH, selects environment(s), reads actual Helm chart configs, then dispatches agent for accurate calculations.
Controlled plan execution with human review checkpoints - loads plan, executes in batches, pauses for feedback. Supports one-go (autonomous) or batch modes.
Orchestrate parallel paper processing. Split paper into sections and run any eligible Skill (polish, translation, de-ai) across sections via subagents. 团队协作模式：将论文拆分为章节并行处理。