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Find your next superpower If you are an agent, refer to our llms.txt for full access.Uses Nano Banana 2 for scientific diagram generation and Gemini 3.6 Flash for quality review, regenerating when output falls below a document-specific threshold. Covers neural network architectures, system diagrams, flowcharts, biological pathways, and scientific visualizations.
Builds and maintains a Stockbee-style study of US equities moving at least 20% up or down. Classifies catalysts and setup context, updates forward outcomes, and summarizes recurring patterns, with support for historical backfills and example collections.
Reviews claims, evidence, methods, statistics, reproducibility, ethics, figures, tables, and citations. Supports reporting-guideline selection and revision-response planning for authorized manuscript, protocol, preprint, and proposal reviews.
Maintenance ended on August 7, 2026, and its methodology was incorporated into the private deck-creator skill. The final version remains usable for external users but receives no updates and is scheduled for removal in daymade-docs v2.0.0.
Creates slides for research talks, conferences, seminars, and thesis defenses. Provides presentation structure, design templates, timing guidance, and visual validation.
Handles VSS alert workflows through real-time monitoring and Alert-Bridge subscriptions. Includes Slack notifications, incident queries, and camera onboarding, with scope limited to alert-related analytics.
Installs a visible signal in each reply, such as the user's name and a turn counter, to expose silent context degradation. Runs a recovery protocol when that signal fails or context drift is detected.
Creates a Markdown policy, JSON taxonomy, and drop-in inference prompts for text and multimodal Nemotron content-safety models. Maps rough requirements or existing policies to V2 categories, with custom categories and topic-following rules.
Creates an xUnit integration test project targeting Oracle, including a transaction-rollback base class and seed data manager. Intended for the baseline testing phase; the PostgreSQL test project is subsequently produced by migrating this project.
Use Transformers.js for text, vision, audio, and multimodal inference with pretrained Hugging Face models. Supports browsers and Node.js, Bun, or Deno runtimes using WebGPU and WASM.
Builds alerting with Axiom monitors and notifiers using the v2 public API. Covers notification routing, monitor behavior validation, and ongoing alert configuration maintenance.
Guides selection among alltoall, DeepEP, and HybridEP based on hardware, expert-parallel degree, and optimization stage. Summarizes patterns from DSV3, Qwen3, Qwen3-Next, and VLM bring-up work.
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