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Plan how an AI application should use Hindsight memory. Identify useful information to retain, define user-scoping tags and memory bank settings, and specify how retrieved facts and synthesized knowledge should reach the model.
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Retrieve relevant Hindsight memories before planning or answering a request. Searches the agent’s own and shared memory stores, plus other relevant stores when needed, to bring past decisions, user preferences, and project context into the task.
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Record task handoffs between Bots in shared Hindsight memory, including progress, remaining work, sources, and caveats. Other Bots can retrieve the record later, continue unfinished work, and report the outcome back through shared memory.
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Create a specialized Claude Code subagent with Hindsight long-term memory. Start with an empty agent or import prepared documents, then equip it with knowledge pages and memory search to reuse information across sessions.
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Answer questions about past decisions, usual practices, and changes over time by reasoning across Hindsight memories. When information spans multiple memory banks, combine the answers and identify their sources, while acknowledging gaps or contradictions.
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Recognize classic candlestick patterns using pandas, a Python library for tabular data. Combine bullish and bearish pattern scores into long, short, or stand-aside signals, with adjustable thresholds for candle bodies and shadows.
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Develop and deploy Cloudflare Workers, manage related storage and services, and troubleshoot configuration with Wrangler. The skill checks official documentation and configuration definitions before preparing commands, with guidance for local development, environments, secrets, and logs.
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Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.
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This skill should be used when working with reinforcement learning tasks including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procgen, etc.). Use this skill for implementing PPO training, creating PufferEnv environments, optimizing RL performance, or developing policies with CNNs/LSTMs.
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Your long-term knowledge pages. Read them at session start. Create new pages when you learn something worth remembering across sessions. Pages auto-update from your conversations via Hindsight.
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Turn a raster logo (PNG/JPG/WebP/screenshot) into a clean minimal SVG with edge smoothness as the primary hard gate and IoU optimized as high as reasonably possible without a fixed global threshold, then into a choreographed logo animation delivered as standalone JS-rendered HTML, applying Disney's 12 animation principles. Use when asked to animate a logo, build a logo reveal / splash screen / brand intro, convert a logo image into animated SVG or HTML, add motion to a vectorized mark, or create loading/idle/hover motion for a brand mark. v2: also handles self-crossing draw-on choreography (split-fill, exact easing subdivision, tip glint), closed variable-width ribbon fitting, and quantitative motion QA (easing probe, ink-delta continuity sweep).
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Turn a raster logo (PNG/JPG/WebP/screenshot) into a clean minimal SVG with edge smoothness as the primary hard gate and IoU optimized as high as reasonably possible without a fixed global threshold, then into a choreographed logo animation delivered as standalone JS-rendered HTML, applying Disney's 12 animation principles. Use when asked to animate a logo, build a logo reveal / splash screen / brand intro, convert a logo image into animated SVG or HTML, add motion to a vectorized mark, or create loading/idle/hover motion for a brand mark. v2: also handles self-crossing draw-on choreography (split-fill, exact easing subdivision, tip glint), closed variable-width ribbon fitting, and quantitative motion QA (easing probe, ink-delta continuity sweep).
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Use when editing an existing image on Scenario through MCP with a tool model, not a new generation: upscale or enhance to 2x, 4K, 8K, super resolution, 3D LUT color grade, color correction, posterize, solarize, vignette, film grain, blur, sharpen, glow, chromatic aberration, oilify, cubism, crystallize, dodge and burn, tint, desaturate, expand or uncrop, reframe an aspect ratio, resize to exact pixels, slice tiles, contact sheet, split into layers, remove a background or watermark, vectorize.
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Use when building a visual identity or brand kit with Scenario: a logo, wordmark, or icon as editable SVG, a color palette and typography spec, logo variants (mono, reversed, favicon), and brand applications like social templates, avatars, banners, or merchandise mockups. Also for a rebrand or refreshing an existing mark. Keywords: brandkit, brand kit, visual identity, logo, monogram, wordmark, SVG, vectorize, color palette, typography, brand guidelines, brand board, launch kit.
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High-performance vectorized backtesting with parameter optimization, portfolio simulation, and rich performance metrics
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Python framework for single- and multi-objective optimization with evolutionary algorithms. Define vectorized objectives and constraints; solve with NSGA-II, NSGA-III, MOEA/D, GAs, or differential evolution. Analyze Pareto fronts, visualize trade-offs, customize operators and callbacks. For engineering design, hyperparameter search, and conflicting objectives. Alternatives: scipy.optimize (single-objective, gradient), platypus, jMetalPy (Java).
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Route BERTopic topic modeling, embedding, vectorizer, labeling, visualization, and serialization workflows.
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Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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Fallback reference for Cloudflare products that have no dedicated skill here — Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Prefer the focused skill when one fits: agents-sdk for the Agents SDK, durable-objects for Durable Objects, workers-best-practices for reviewing or authoring Worker code, wrangler for CLI commands, sandbox-sdk for sandboxed execution. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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You are an expert in Cloudflare Workers AI, the serverless AI inference platform running on Cloudflare's global network. You help developers run LLMs, embedding models, image generation, speech-to-text, and translation models at the edge with zero cold starts, pay-per-use pricing, and integration with Workers, Pages, and Vectorize — enabling AI features without managing GPU infrastructure.
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Convert raster images (photos, paintings, illustrations, line art) into SVG vector reproductions. Use when the user uploads an image and asks to reproduce, vectorize, trace, or convert it to SVG. Also use when asked to decompose an image into shapes, create an SVG version of a picture, or faithfully reproduce artwork as vector graphics. Handles graphic/line-art inputs (Kandinsky, architectural drawings, ink work) via a compositional pipeline that extracts lines as SVG strokes. Do NOT use for creating original SVG illustrations from text descriptions — only for converting existing raster images.
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Portrait Mode for SVGs — foveated vectorization with 4-zone selective detail. Combines vision annotations, MediaPipe segmentation/landmarks, and optional saliency. Like phone portrait mode, but vectorized. Use when vectorizing a portrait or photo where subject detail should outrank background detail.
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Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task.
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Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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