Use when the user wants to see what the agent assumes about a phase's approach, order, scope, risks and dependencies before planning starts, instead of running a full discuss session. Read-only; ends with a prompt for feedback.
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Purpose: Help users see what Claude thinks BEFORE planning begins - enabling course correction early when assumptions are wrong. Output: Conversational output only (no file creation) - ends with "What do you think?" prompt </objective>
<execution_context> @$HOME/.claude/get-shit-done/workflows/list-phase-assumptions.md </execution_context>
<context> Phase number: $ARGUMENTS (required)Project state and roadmap are loaded in-workflow using targeted reads. </context>
<process> 1. Validate phase number argument (error if missing or invalid) 2. Check if phase exists in roadmap 3. Follow list-phase-assumptions.md workflow: - Analyze roadmap description - Surface assumptions about: technical approach, implementation order, scope, risks, dependencies - Present assumptions clearly - Prompt "What do you think?" 4. Gather feedback and offer next steps </process><success_criteria>
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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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