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Found 540 Skills
Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests for "review paper", "survey", "literature review", "综述", "systematic review", or mentions of writing academic reviews on deep learning for medical imaging.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
Analyzes fundamental questions and concepts through philosophical lens using logic, epistemology, metaphysics, and critical analysis frameworks. Provides insights on meaning, truth, knowledge, existence, reasoning, and conceptual clarity. Use when: Conceptual ambiguity, logical arguments, foundational assumptions, meaning questions. Evaluates: Validity, soundness, coherence, assumptions, implications, conceptual clarity.
Use this skill when creating and configuring a PixiJS v8 Application. Covers new Application() + async app.init() options (width, height, background, antialias, resolution, autoDensity, preference, resizeTo, autoStart, sharedTicker, canvas, useBackBuffer, powerPreference, eventFeatures, accessibilityOptions, gcActive, bezierSmoothness, webgl/webgpu/canvasOptions per-renderer overrides), app.stage/renderer/canvas/screen/domContainerRoot access, ResizePlugin, TickerPlugin, CullerPlugin (cullable, cullArea), custom ApplicationPlugin creation via ExtensionType.Application, start/stop lifecycle, and app.destroy() with releaseGlobalResources. Triggers on: Application, app.init, app.stage, app.renderer, app.canvas, app.screen, app.domContainerRoot, ApplicationOptions, ApplicationPlugin, ExtensionType.Application, resizeTo, preference, autoStart, sharedTicker, useBackBuffer, powerPreference, skipExtensionImports, preferWebGLVersion, preserveDrawingBuffer, cullable, CullerPlugin, app.start, app.stop, app.destroy, releaseGlobalResources.
High-dividend stock screen via Longbridge — analyse high-dividend-yield strategies for A-shares / HK / US, filter for sustainable payout (reasonable payout ratio, free-cash-flow coverage), stable dividend history, and evaluate long-term total return potential. Triggers: "高分红", "股息率", "红利股", "高股息", "分红稳定", "现金分红", "股息策略", "红利策略", "高分紅", "股息率", "紅利股", "高股息", "分紅穩定", "現金分紅", "high dividend", "dividend yield", "dividend stock", "income stock", "dividend strategy", "payout ratio", "free cash flow coverage", "dividend growth", "dividend stability".
Agent Script DSL development skill for Salesforce Agentforce. Enables writing deterministic agents in a single .agent file with FSM architecture, instruction resolution, and hybrid reasoning. Covers syntax, debugging, testing, and CLI deployment.
Use to detect and remove cognitive biases from reasoning. Invoke when prediction feels emotional, stuck at 50/50, or when you want to validate forecasting process. Use when user mentions scout mindset, soldier mindset, bias check, reversal test, scope sensitivity, or cognitive distortions.
Knowledge base for designing, reviewing, and linting agentic AI infrastructure. Use when: (1) designing a new agentic system and need to choose patterns, (2) reviewing an existing agentic architecture ADR or design doc for gaps/risks, (3) applying the lint script to an ADR markdown file to get structured findings, (4) looking up a specific agentic pattern (prompt chaining, routing, parallelization, reflection, tool use, planning, multi-agent collaboration, memory management, learning/adaptation, MCP, goal setting, exception handling, HITL, RAG, A2A, resource optimization, reasoning techniques, guardrails, evaluation, prioritization, exploration/discovery). All rules and guidance are grounded in the PDF "Agentic Design Patterns" (482 pages).
Configure Steedos Server via environment variables and YAML settings files. Covers required env vars (MONGO_URL, ROOT_URL, B6_TRANSPORTER, B6_CACHER), steedos-config.yml project settings, default.steedos.settings.yml template with env interpolation, datasources, tenant settings, CFS file storage (local, aliyun, aws, steedosCloud), SSO/OIDC, email, SMS, push notifications, and frontend asset URLs.
Analyze a user's Plannotator plan archive to extract denial patterns, feedback taxonomy, evolution over time, and actionable prompt improvements — then produce a polished HTML dashboard report. Falls back to Claude Code ExitPlanMode denial reasons when Plannotator data is unavailable.
Use this skill before any creative or constructive work (features, components, architecture, behavior changes, or functionality). This skill transforms vague ideas into validated designs through disciplined, incremental reasoning and collaboration.
Build agentic AI with OpenAI Responses API - stateful conversations with preserved reasoning, built-in tools (Code Interpreter, File Search, Web Search), and MCP integration. Prevents 11 documented errors. Use when: building agents with persistent reasoning, using server-side tools, or migrating from Chat Completions/Assistants for better multi-turn performance.