Plan and implement Trieste-based compiler passes and AST transformations for rego-cpp. Use when: adding new compiler passes, modifying AST structure, implementing new Rego language features, debugging pass failures, working with well-formedness definitions, or performing any multi-step implementation that touches the Trieste pass pipeline. Includes the multi-planner approach for complex features.
Build good-looking web interfaces. Use when: - User asks you to build a web app, website, landing page, or HTML page - User asks for a one-off tool, utility, or demo app - User is starting a new frontend project - User wants to improve how something looks - User mentions UI, design, styling, or making something look better This applies to ANY frontend work, not just "design" tasks. Even simple apps benefit from basic design principles.
Bump the rego-cpp version number for a new release. Use when: preparing a release, updating version strings after a tag, or when instructed to bump the version. Updates all version files across the main library and wrapper packages to keep them in sync.
Execute AI-generated code in secure isolated E2B cloud sandboxes (SDK v2). Use for running Python/JavaScript/TypeScript/R/Java/Bash code, managing sandbox lifecycle (create, pause, resume, kill, list, connect), running coding agents (Claude Code, Codex, AMP, OpenCode) in sandboxes, git operations inside sandboxes, code contexts for parallel isolated execution, monitoring metrics (CPU, memory, disk), MCP gateway integration (200+ tools), uploading/downloading files, storage bucket mounting (S3, GCS, R2), streaming command output, SSH/PTY access, custom templates with Build System 2.0, and integrating LLMs with code execution capabilities.
Deploys funnel pages to Cloudflare Pages. Covers Wrangler CLI setup, direct upload, custom domains, and Cloudflare-specific optimizations.
Install and configure ToolUniverse for any use case — MCP server (chat-based), CLI (command line with 9 subcommands), or Python SDK (Coding API with 3 calling patterns). Covers uv/uvx setup, MCP configuration for 12+ AI clients (Cursor, Claude Desktop, Windsurf, VS Code, Codex, Gemini CLI, Trae, Cline, etc.), full CLI reference (tu list/grep/find/info/run/test/status/build/serve), Coding API quickstart, agentic tools, code executor, API key walkthrough, skill installation, and upgrading. Use when user asks how to set up ToolUniverse, which access mode to use (MCP vs CLI vs SDK), configuring MCP servers, using the CLI, troubleshooting installation, upgrading, or mentions installing ToolUniverse or setting up scientific tools. Also triggers for "how do I use ToolUniverse", "what's the best way to access tools", "command line", "tu command", "coding API", "tu build".
使用此技能进行复杂病例的辨证分析。当患者症状复杂、涉及多个脏腑、或需要深度分析时使用。
使用此技能了解中医辨证理论要点，包括八纲辨证、脏腑辨证、复合证型识别等核心知识。
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
Autonomous molecular dynamics simulation pipeline inspired by DynaMate (2026). Designs, executes, and analyzes complete MD workflows for protein and protein-ligand systems. Covers structure retrieval, system preparation, minimization, equilibration, production, and trajectory analysis (RMSD, RMSF, hydrogen bonds, binding free energy). Uses OpenMM as the primary engine with AmberTools for preparation. Self-correcting — detects and fixes common simulation failures. Use when users ask for MD simulations, protein stability analysis, binding free energy calculations, or "跑个分子动力学模拟". Requires OpenMM and optionally AmberTools.
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
De novo protein binder design using PXDesign. Use this skill when designing non-antibody protein binders against a target structure. Covers YAML config creation, CLI invocation, output parsing, and result interpretation. For antibody/nanobody binders, use proteus-ab instead. For structure prediction only, use proteus-fold. For scoring and screening, use proteus-scoring and proteus-screening.
Antibody and nanobody binder design using Proteus-AB (BoltzGen diffusion + Protenix refolding). Covers entity YAML specification, CLI invocation, protocol selection (nanobody-anything / antibody-anything), MSA modes, and output parsing. Use this skill whenever the user needs to design an antibody or nanobody binder against a protein target.
De novo protein binder design using PXDesign. Use this skill when designing non-antibody protein binders against a target structure. Covers YAML config creation, CLI invocation, output parsing, and result interpretation. For antibody/nanobody binders, use boltzgen instead. For structure prediction only, use proteus-fold. For scoring and screening, use by-scoring and by-screening.
Deep academic research for antibody design campaigns — target analysis, literature review, prior art search, epitope identification. Uses an 8-phase pipeline with quality gates and persistent memory. Use this skill whenever researching a protein target, starting a new design campaign, investigating prior art, analyzing epitopes, reviewing literature for design strategy, or when the user mentions target research, literature search, or prior art in the context of protein/antibody design.
Deep academic research for antibody design campaigns — target analysis, literature review, prior art search, epitope identification. Uses an 8-phase pipeline with quality gates and persistent memory. Use this skill whenever researching a protein target, starting a new design campaign, investigating prior art, analyzing epitopes, reviewing literature for design strategy, or when the user mentions target research, literature search, or prior art in the context of protein/antibody design.
Antibody and nanobody binder design using BoltzGen (BoltzGen diffusion + Protenix refolding). Covers entity YAML specification, CLI invocation, protocol selection (nanobody-anything / antibody-anything), MSA modes, and output parsing. Use this skill whenever the user needs to design an antibody or nanobody binder against a protein target.
AI-driven patient-to-trial matching for precision medicine and oncology. Given a patient profile (disease, molecular alterations, stage, prior treatments), discovers and ranks clinical trials from ClinicalTrials.gov using multi-dimensional matching across molecular eligibility, clinical criteria, drug-biomarker alignment, evidence strength, and geographic feasibility. Produces a quantitative Trial Match Score (0-100) per trial with tiered recommendations and a comprehensive markdown report. Use when oncologists, molecular tumor boards, or patients ask about clinical trial options for specific cancer types, biomarker profiles, or post-progression scenarios.
Provide differential diagnosis for patients with suspected rare diseases based on phenotype and genetic data. Matches symptoms to HPO terms, identifies candidate diseases from Orphanet/OMIM, prioritizes genes for testing, interprets variants of uncertain significance. Use when clinician asks about rare disease diagnosis, unexplained phenotypes, or genetic testing interpretation.
