493 skills · sorted by relevance
Create realistic metal surfaces in Three.js by combining structured reflections, studio lighting, scratches, fingerprints, and beveled edges. Includes polished, brushed, and aged finishes for objects such as tools, rings, and metal product parts.
Add underwater sunbeams to a Three.js scene, with rippling light patterns, a shimmering surface viewed from below, and matching illumination on fish. The beams shift against objects as the camera moves, giving the water depth.
Build a Three.js object viewer with a gentle camera lean on hover and a click-to-inspect mode. Visitors can rotate and zoom the object, then return it to its original position using mouse, touch, or keyboard controls.
Connect an AI agent to BNB Chain through MCP, a protocol for accessing external tools. Configure the server, inspect balances and transactions, transfer tokens, interact with contracts, register agents, and manage Greenfield storage.
Apply the System.Text.Json APIs introduced in .NET 11 to produce PascalCase JSON names and retrieve typed serialization metadata, the information used to convert objects. Create runnable examples and check metadata availability without exception-based probing.
Configure dependency injection in .NET MAUI, a way to supply objects with the services they need. Covers service registration, instance lifetimes, page and ViewModel constructors, Shell navigation, platform implementations, and test substitutions.
Investigate unsafe deserialization, where restoring objects from untrusted data can trigger code execution. The skill covers Java, PHP, Python, .NET, Ruby, and related patterns, with detection clues and callback-based checks for confirming execution.
Process astronomical data in Python with Astropy. This skill covers celestial coordinate, unit, and time conversions; reading and editing FITS astronomy files; matching object catalogs; and calculating cosmic distances using cosmological models.
Analyze relationships between people, objects, or papers as networks in Python. Use NetworkX to find shortest paths, identify important nodes and communities, visualize connections, exchange graph data, and generate sample networks for testing.
Turns a repeatable workflow from a conversation, skill, spreadsheet, or Claude/ChatGPT project into an Agent-Native app. It creates populated screens with controls that hand tasks to an in-app agent and return results to the relevant objects.
Create custom tools that an AI agent can call in Unity Editor by adding C# files to the project. Includes implementation examples and guidance for structured results, running Unity operations on the main thread, and handling lengthy operations or recompilation.
Create HTML design artifacts, including interface mockups, interactive prototypes, and slide decks, then preview and verify them. The skill also guides importing design references and building reusable design systems with shared styles and components.
Coordinate Lark and Feishu work from Codex by routing requests to the appropriate skills and CLI commands. Resolve linked objects, choose user or bot access, and guide reading or updates to documents, spreadsheets, events, and tasks.
Collect GitHub activity and local git history as evidence for investigations, then save, filter, and share it as JSON. The skill also supports recovering deleted content from archives and checking stored evidence against its original sources.
Analyze relationships between people, objects, or places using Python networks. Build connection diagrams, find shortest paths, identify important nodes and closely connected groups, visualize network structure, and save the resulting data and measurements.
Helps process astronomical data in Python by converting coordinates, units, and time scales, working with FITS observation files, matching object catalogs, and calculating distances using cosmological models.
Assess whether a DOCA application needs low-level communication controls beyond its higher-level APIs. For those cases, guide queue configuration, libibverbs migration, and error diagnosis using installed headers, version checks, and device capability queries.
Configure DOCA GPI so CUDA kernels can initiate RDMA, direct remote memory access, without host CPU mediation. The skill guides channel setup, memory attachment, GPU handle handoff, library selection, and diagnosis of GPI errors.
Write and debug nvMolKit Python code for processing large molecule batches on GPUs. Covers molecular fingerprints, compact representations of molecular features, plus similarity calculations, 3D conformer generation, optimization, clustering, and molecular searches using RDKit objects.
Implements dependency injection in Golang using uber-go/dig — reflection-based container, Provide/Invoke, dig.In/dig.Out parameter and result objects, named values, value groups, optional dependencies, scopes, and Decorate. Apply when using or adopting uber-go/dig, when the codebase imports `go.uber.org/dig`, or when wiring an application graph at startup. For higher-level lifecycle and modules, see `samber/cc-skills-golang@golang-uber-fx` skill.
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Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks. Triggers: "image analysis", "computer vision", "OCR", "object detection", "ImageAnalysisClient", "image caption".
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Profile or debug CPU usage and memory allocation in deployed Cloudflare Workers and Durable Objects. Then use this information to optimize your code.
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Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.
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Perform differential expression analysis using DESeq2 in R/Bioconductor. Use for analyzing RNA-seq count data, creating DESeqDataSet objects, running the DESeq workflow, and extracting results with log fold change shrinkage. Use when performing DE analysis with DESeq2.
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