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Found 2,764 Skills
Verify and build the required environment for Triton operator development on the Ascend platform, including configurations of dependencies such as CANN, Python/torch/torch_npu/triton-ascend and PATH environment variables. This is used when users need to configure the Triton operator development environment, check the installation of CANN/torch/triton-ascend, or verify whether the environment is available.
Accepts Triton operator implementations, automatically invokes Torch small operator implementations (CPU or NPU) for precision comparison, and generates precision reports. It is used when users need to verify the correctness and precision of Triton operator implementations, compare precision with PyTorch implementations, and generate standardized precision reports.
Verify documentation coverage and generate missing docs interactively
Abstract - Email Verification API integration. Manage data, records, and automate workflows. Use when the user wants to interact with Abstract - Email Verification API data.
Preview and verify imported content in local AEM Edge Delivery Services dev server. Validates rendering, compares with original page, and troubleshoots common issues.
Grow a component package into a high-quality, sourceable reusable design in Zener. Use when translating a datasheet, application note, or eval design into circuitry that should live with the component package itself — including checking for existing reusable packages first, extracting evidence, choosing sourceable passives, documenting the design in the `.zen` docstring, and validating with `pcb build`.
Run a pre-submission citation and reference audit for LaTeX academic papers. Use this skill whenever the user wants to verify that BibTeX entries are correct, every citation key in TeX resolves, every figure/table/equation/section reference is valid, DOI/arXiv/OpenReview/proceedings metadata matches the cited work, citation claims are supported by the cited paper, or a paper is ready for submission with clean references.
[Hyper] Test Codex/agent skills for intended triggering and behavior with realistic positive, negative, boundary, and edge-case scenarios. Use when validating a skill folder, SKILL.md, rules/references/scripts/assets, trigger precision, workflow correctness, or regression coverage before shipping skill changes.
Use when the user asks to generate API tests, create integration test suites, test REST endpoints, or build contract tests.
Researches any project idea against live data from GitHub and Dev.to to surface what already exists, how mature the space is, and where the real opportunity lives. Use when a developer describes something they want to build and wants to know if it's been done before. Triggers on phrases like "validate my idea", "has this been built", "is this already a thing", "what exists for X", "should I build this", "is this idea original", "check if my project exists", "what are the alternatives to what I want to build", "is the market saturated for X", or any request to research the competitive landscape before starting a project.
Automated pipeline for retraining ML models with new construction data. Monitor model drift, trigger retraining, and validate model performance.
Read a ***plain project — its `.plain` files, `test_scripts/`, `config.yaml`(s), and `resources/` — and determine every command-line tool, runtime, package manager, and external service the project needs on the host machine. Probe the host for each one, then emit a `PASS` / `FAIL` report listing what's installed (with versions), what's missing, and concrete OS-specific install commands for the gaps. Run this any time someone is about to render, test, or onboard onto a ***plain project for the first time.