Loading...
Loading...
Found 5,856 Skills
Activate this skill when any task fails two or more times, when you are about to give up or say 'I cannot', when shifting responsibility to the user (e.g., 'you should manually...', 'please check...', 'you may need to...'), blaming the environment without verification (e.g., 'might be a permissions issue', 'could be a network problem'), making any excuse to stop trying, spinning in circles (repeatedly tweaking the same code/parameters without new information — busywork), fixing only the surface issue without checking for related problems, skipping verification after a fix and claiming 'done', providing suggestions instead of actual code/commands, saying 'this is beyond scope' or 'this requires manual intervention', encountering permission/network/auth errors and stopping instead of trying alternatives, or displaying any passive behavior (waiting for user instructions instead of proactively investigating). It also triggers on user frustration phrases in any language: '你怎么又失败了', '为什么还不行', '换个方法', '你再试试', '不要放弃', '继续', '加油', 'why does this still not work', 'try harder', 'you keep failing', 'stop giving up', 'try again', 'don't give up', 'keep going', 'figure it out'. This applies to ALL task types: debugging, implementation, configuration, deployment, research, DevOps, infrastructure, API integration, data processing. Do NOT activate it for first-attempt failures or when a known fix is already in progress.
Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
Local-first, security-first control center for OpenClaw agents — visibility dashboard with readonly defaults, token attribution, collaboration tracing, and safe write operations.
Simplify and refine recently modified code for clarity and consistency. Use after writing code to improve readability without changing functionality.
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
This skill should be used when the user asks about 'account balance', 'how much USDT do I have', 'my funding account', 'show my positions', 'open positions', 'position P&L', 'unrealized PnL', 'closed positions', 'position history', 'realized PnL', 'account bills', 'transaction history', 'trading fees', 'fee tier', 'account config', 'max order size', 'how much can I buy', 'withdrawable amount', 'transfer funds', 'move USDT to trading account', or 'switch position mode'. Requires API credentials. Do NOT use for market prices (use okx-cex-market), placing/cancelling orders (use okx-cex-trade), or grid/DCA bots (use okx-cex-bot).
Cloud-based quantum chemistry platform with Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2). Use when tasks involve quantum chemistry calculations, molecular property prediction, DFT or semiempirical methods, neural network potentials (AIMNet2), protein-ligand binding predictions, or automated computational chemistry pipelines. Provides cloud compute resources with no local setup required.
Official Opentrons Protocol API for OT-2 and Flex robots. Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features. Best for production Opentrons protocols, official API compatibility. For multi-vendor automation or broader equipment control use pylabrobot.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
Build headless data tables with TanStack Table v8. Server-side pagination, filtering, sorting, and virtualization for Cloudflare Workers + D1. Prevents 12 documented errors. Use when building tables with large datasets, coordinating with TanStack Query, or fixing state management, performance, or React 19+ compatibility issues.