Use when the user wants a dashboard of all phases or to run more than one phase in parallel. Shows phase status with recommended next actions, runs discuss inline, and dispatches plan and execute as background agents.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Designed for power users who want to parallelize work across phases from one terminal: discuss a phase while another plans or executes in the background.
Creates/Updates:
.planning/STATE.md, .planning/ROADMAP.md, phase directories for status.After: User exits when done managing, or all phases complete and milestone lifecycle is suggested. </objective>
<execution_context> @$HOME/.claude/get-shit-done/workflows/manager.md @$HOME/.claude/get-shit-done/references/ui-brand.md </execution_context>
<context> No arguments required. Requires an active milestone with ROADMAP.md and STATE.md.Project context, phase list, dependencies, and recommendations are resolved inside the workflow using gsd-tools.cjs init manager. No upfront context loading needed.
</context>
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Train and optimize AI agents using Microsoft's Agent Lightning framework with reinforcement learning. Use when setting up agent training, instrumenting agents with tracing, configuring LightningStore, implementing reward functions, or optimizing prompts with RL/APO algorithms.
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Post-run self-evaluation system that scores agent output on correctness, clarity, actionability, and conciseness. Use after /team runs, skill executions, or when explicitly asked to evaluate output quality.
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Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awareness. Triggers: marketing video, ad video, promo video, commercial, brand video, product video, explainer video, ad creative, video ad, facebook ad video, youtube ad, instagram ad, tiktok ad, promotional video, launch video
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Use when building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model output.
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Your AI research and engineering brain trust. 59 named personas across 8 cells covering frontier labs, applied product, model architecture, reasoning/RL/agents, alignment and interpretability, theory and science of DL, multimodal and…
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Use when designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL. Covers resources, HTTP semantics, pagination, error handling, and pitfalls.
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