Loading...
Loading...
Found 6,309 Skills
Use when helping Zaid Ul Hassan search, score, tailor resumes for, prepare, submit, or track backend and backend-heavy full-stack job applications, especially LinkedIn, company-site, recruiter DM, cover-letter, DOCX/PDF resume, and application-packet workflows.
AI-powered command-line assistant for developers that provides code review, debugging, test generation, and development workflows directly in the terminal
Build and run durable background coding agents with workflow orchestration, isolated sandboxes, and GitHub integration on Vercel.
Code commit, PR creation, merge, and issue closure workflow via GitHub CLI (gh). Triggers after a goal (GitHub Issue) implementation is complete — commit code, push branch, create PR, merge, then close the issue. Use when the user says "提交代码", "commit and merge", "创建PR", "合入", "关闭issue", "ship-it", or when a goal implementation is done and code needs to be shipped.
Codex-native Academic Research Skills suite for deep research, academic paper writing, manuscript review, full research-to-paper pipelines, and experiment planning or validation. Use when the user asks for deep research, literature review, systematic review, meta-analysis, research question refinement, academic paper drafting, paper revision, citation or integrity checks, reviewer simulation, peer review, editorial decision letters, research-to-paper workflows, experiment execution planning, statistical interpretation, or human study protocol support. Also use for Claude-style ARS command aliases such as /ars-plan, ars-plan, /ars-outline, /ars-abstract, /ars-lit-review, /ars-citation-check, /ars-disclosure, /ars-format-convert, /ars-revision-coach, /ars-revision, and /ars-full. This skill vendors ARS role prompts, references, templates, and shared handoff schemas under ars/.
A collection of Agent Skills for the Stitch MCP server: generate high-fidelity UI screens, create multi-page websites from a single prompt, produce DESIGN.md documentation, enhance vague UI prompts, convert designs to React/shadcn-ui components, and generate walkthrough videos via Remotion. Use when the user needs AI-assisted UI design generation, prompt refinement, or screen-to-code workflows. Triggers on: stitch, stitch-design, stitch-loop, enhance-prompt, react-components, remotion, shadcn-ui, screen generation, ui generation.
Build and operate multi-agent workflows with OpenAI Agents SDK (Python): define agents/tools/handoffs, add guardrails, run conversations, and debug orchestration behavior. Use when users ask for agent orchestration with OpenAI-native patterns, handoff routing, or production-ready agent loops.
Search named IDA entities by pattern. Use when asked to find functions, labels, types, or members by name, or to seed xref/decompiler workflows from a name lookup.
MoveIt2 SRDF generation, validation, and planning-semantics workflow. Use when creating, editing, regenerating, inspecting, or validating `.srdf` files, `gen_srdf()` sources, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-linked planning semantics, or SRDF handoff to CAD Explorer review. Use the URDF skill for robot structure, the SDF skill for simulator descriptions, and the render skill for rendering, Explorer links, and optional MoveIt2 controls.
Apply CUDA Graphs to PyTorch workloads — API selection (torch.compile, PyTorch make_graphed_callables, TE make_graphed_callables, MCore CudaGraphManager, FullCudaGraphWrapper, manual torch.cuda.graph), code compatibility, capture workflows, dynamic pattern handling, and troubleshooting. Triggers: CUDA graph, torch.cuda.graph, make_graphed_callables, reduce-overhead, graph capture, graph replay, kernel launch overhead, CudaGraphManager, FullCudaGraphWrapper, full-iteration graph, stream capture.
Bump a pinned dependency (TransformerEngine, Megatron-LM, NRX, etc.), regenerate the lockfile, open a PR, and drive it to green by attaching a watchdog to the "CICD NeMo" workflow and quarantining failing functional tests as flaky until the run is green.
ONLY for OpenAI Triton (@triton.jit) kernel development. NEVER use for CUDA C++ kernels, TileIR, or profiling tools (ncu, nsys). The user's request must involve Triton explicitly. Covers Triton-specific patterns: fused elementwise, reductions (softmax, LayerNorm, RMSNorm), tiled GEMM with triton.autotune, and flash attention. Workflow: design, write, verify (with fast-path for explicit requests).