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Found 81 Skills
Analyze command history to identify which skills work, which fail, and where to improve.
Quick summary of the last session — commands run, files changed, and what to do next.
Capture a session summary — what was done, what decisions were made, and what to do next.
Use when drafting or revising human-facing prose such as docs, essays, prompts, UI copy, reports, commit messages, PR text, or polished long-form writing. Combines anti-AI-trope editing with clear and concise style rules for stronger, more natural prose.
Generates and analyzes financial models, P&L forecasts, and cash flow projections. Transforms business assumptions into multi-year financial statements.
MAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".
Masked Auto-Encoder (MAE) for self-supervised pretraining and fine-tuning. Masks random patches and reconstructs them to learn visual representations; supports pretrain and finetune stages. Use when training, evaluating, exporting, or running inference for a TAO MAE backbone. Trigger phrases include "pretrain MAE", "self-supervised vision pretraining", "Masked Autoencoder", "Mask Auto-Encoder", "MAE fine-tune".
Expert guidance for architecting and troubleshooting Adobe Workfront Planning (WFP, also called "Maestro"): workspace and record-type design, record connections and hierarchies, formula fields, object and connection limits across Select/Prime/Ultimate tiers, the Planning API (filtering, bulk actions, workspace builds), Fusion, AI Assistant, GenStudio, Canvas Dashboards, views, access/licensing, and request forms. Use this skill whenever the user asks about Workfront Planning or Maestro: designing or building a workspace, connecting record types, fixing a broken formula, hitting or asking to raise a limit (such as the 500 connected-records or 25,000 records-per-type caps), tier and capacity questions, filtering records through the API, choosing an automation surface, or reconciling Adobe's public docs against actual API behavior. Also trigger for "build me a Planning workspace", "why is my formula failing", "what's the max records per type", or "Select vs Prime vs Ultimate limits".
Build a Stockbee-style setup model book from momentum-burst screener candidates, then update 3-day and 5-day forward outcomes with MFE/MAE, stop-hit status, outcome tags, and cohort statistics. Use when the user wants to study Stockbee Momentum Burst examples, track failed candidates, build setup fluency, review A/B setup quality, or convert screener outputs into a learning loop rather than immediate trade signals.
Test native, React Native, hybrid, and Flutter mobile apps with Appium 3.x, Detox, Maestro, and Patrol. Covers device farm setup (BrowserStack, Sauce Labs), gesture simulation, deep link and cold-start testing, push notifications, biometric (Face ID) auth, offline/poor-network simulation, and iOS/Android permission dialog handling. Use when: "mobile test," "Appium," "Detox," "Maestro," "Patrol," "Flutter test," "iOS test," "Android test," "device farm," "deep link," "biometric," "Face ID," "permission dialog," "React Native test." Not for: device/browser matrix strategy in the abstract — use cross-browser-testing; app startup/memory/battery profiling depth — use performance-testing; mobile screenshot diffing — use visual-testing. Related: ci-cd-integration, cross-browser-testing, performance-testing, test-data-management, test-reliability.
Create, manage, and orchestrate AI agents using the AI Maestro CLI. Use when the user asks to "create agent", "list agents", "delete agent", "hibernate agent", "wake agent", "install plugin", "show agent", "restart agent", or any agent lifecycle management task.
Comprehensive threat modeling for multi-agent systems using CSA MAESTRO 7-layer framework and OWASP Multi-Agentic System Threat Modeling Guide v1.0. Systematically analyzes threats across all architectural layers from foundation models to agent ecosystems.