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Found 1,667 Skills
· Write, review, or architect CI/CD pipelines -- GitHub Actions, GitLab CI, Forgejo. Covers pipeline security, SHA pinning, SBOM, and runner configuration. Triggers: 'ci/cd', 'pipeline', 'github actions', 'gitlab ci', 'forgejo', '.github/workflows', 'runner', 'sha pinning'.
NetHunt CRM integration. Manage Leads, Persons, Organizations, Deals, Pipelines, Activities and more. Use when the user wants to interact with NetHunt CRM data.
Spydra integration. Manage Organizations, Pipelines, Users, Goals, Filters. Use when the user wants to interact with Spydra data.
Convert PDF presentations to HTML slide templates using a visual reproduction approach. Pipeline: PDF → slide screenshots → Claude writes HTML matching each screenshot. Use when the user wants to convert a PDF to HTML slide templates, reproduce a presentation as HTML, or create reusable templates from existing decks. Triggers: 'pdf to html', 'convert pdf to template', 'reproduce this deck as html', 'create template from pdf'.
Full content production pipeline from blank page to publish-ready piece. Covers competitive research, content briefs, drafting, SEO optimization, readability scoring, editorial quality gates, and internal linking. Use when writing blog posts, articles, guides, or long-form content end-to-end, or when user mentions write a post, draft an article, create content, content pipeline, editorial workflow, content operations, content calendar management, repurposing, or content at scale.
Reference skill for Zoom AI Services Scribe. Use after routing to a transcription workflow when handling uploaded or stored media, Build-platform JWT auth, fast mode transcription, batch jobs, or transcript pipeline design.
Spec-driven development pipeline with 6 phases: Explore, Requirements, Design, Task Plan, Implementation, Review. Enforces human approval gates between phases. Use when user wants structured feature development, spec-first approach, or says "I want to add feature X", "new feature", "implement", "build". Keywords: spec, requirements, design document, TDD plan, task plan, implementation, code review, pipeline, approval gates, WHEN/SHALL.
Generates structured literature survey reports from collected papers using a multi-stage pipeline: outline generation (query-type adaptive) → draft survey → section-by-section expansion → summary section refinement → final assembly. Produces survey-grade output with taxonomy-based method analysis, LaTeX formalizations, comparative tables, and dense citations. Use when: user wants a literature review, research survey, field overview, or systematic synthesis of multiple papers. Do NOT use for finding/searching papers (use paper-navigator), generating research ideas (use research-ideation), or writing a paper's Related Work section (use paper-writing).
Use this skill whenever writing, reviewing, debugging, or refactoring TypeScript code that uses the Effect-TS library. Trigger when you see imports from `effect`, `effect/*`, or any `@effect/*` scoped package (schema, platform, sql, opentelemetry, cli, cluster, rpc, vitest). Trigger on Effect-specific constructs: Effect.gen generators, Schema.Struct/Schema.Class definitions, Layer/Context.Tag/Service patterns, Effect.pipe pipelines, Data.TaggedError/Data.Class error types, Ref/Queue/PubSub/Deferred concurrency primitives, Match module, Config providers, Scope/Exit/Cause/Runtime patterns, or any code using Effect's typed error channel (E parameter). Also trigger when the user asks about Effect patterns, migration from Promises/fp-ts/neverthrow to Effect, or how to structure an Effect application. Covers the full ecosystem: core Effect type, Schema validation, error management, concurrency (fibers, queues, semaphores, pools), streams/sinks, services and layers (DI), resource management, scheduling, observability, platform APIs, and AI integration. Do NOT trigger for React's useEffect, Redux side effects, or general English usage of "effect" unless the context clearly involves the Effect-TS library.
Implement text summarization using extractive and abstractive approaches. Use this skill when the user needs to condense long documents, build an automatic summarization pipeline, or compare summarization strategies — even if they say 'summarize this document', 'TLDR', or 'key points extraction'.
Analyze Huawei Ascend NPU profiling data to discover hidden performance anomalies and produce a detailed model architecture report reverse-engineered from profiling. Trigger on Ascend profiling traces, NPU bottlenecks, device idle gaps, host-device issues, kernel_details.csv / trace_view.json / op_summary / communication.json. Also trigger on "profiling", "step time", "device bubble", "underfeed", "host bound", "device bound", "AICPU", "wait anchor", "kernel gap", "Ascend performance", "model architecture", "layer structure", "forward pass", "model structure". Runs anomaly discovery (bubble detection, wait-anchor, AICPU exposure) alongside model architecture analysis (layer classification, per-layer sub-structure, communication pipeline). Outputs a separate Markdown architecture report alongside anomaly analysis.
Complete toolkit for Huawei Ascend NPU model conversion and end-to-end inference adaptation. Workflow 1 auto-discovers input shapes and parameters from user source code. Workflow 2 exports PyTorch models to ONNX. Workflow 3 converts ONNX to .om via ATC with multi-CANN version support. Workflow 4 adapts the user's full inference pipeline (preprocessing + model + postprocessing) to run end-to-end on NPU. Workflow 5 verifies precision between ONNX and OM outputs. Workflow 6 generates a reproducible README. Supports any standard PyTorch/ONNX model. Use when converting, testing, or deploying models on Ascend AI processors.