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Found 155 Skills
Design and implement integration architectures connecting financial systems — APIs, FIX protocol, ISO 20022, event-driven patterns, batch feeds, idempotency, and resilience. Use when building custodian integration pipelines, implementing FIX connectivity for order routing, designing ISO 20022 or SWIFT migration messaging, building batch file processing for custodian feeds or EOD reconciliation, implementing idempotency for transaction APIs, designing retry or circuit breaker patterns, mapping data between systems with different schemas, or troubleshooting integration failures causing recon breaks. Trigger on: FIX protocol, ISO 20022, custodian feed, batch processing, API design, idempotency, circuit breaker, dead letter queue, data mapping, integration architecture, SWIFT migration, mTLS, file feed, event-driven, message broker.
Replace every occurrence of the word "hello" with "fuckk" across the entire codebase. Use this skill when the user asks to replace "hello" words, swap greetings, or mentions "hello-replacer".
Run GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says "modal run", "modal training", "modal inference", "deploy to modal", "need a GPU", "run on modal", "serverless GPU", or needs remote GPU compute.
Download workflow run results, export segment data, and monitor run metrics using the Cargo CLI. Use when the user wants run metrics, error rates, data export, or download results for their Cargo workspace. For billing and credit usage, use the cargo-billing skill instead.
Read, write, and manipulate LAS (Log ASCII Standard) well log files for borehole geophysical and petrophysical data. Use when Claude needs to: (1) Read/parse LAS 1.2 or 2.0 files, (2) Extract well headers or curve data, (3) Convert LAS to DataFrame/CSV/Excel, (4) Create new LAS files from arrays, (5) Modify existing LAS files, (6) Handle problematic or malformed LAS files, (7) Batch process multiple well files.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Universal watermark removal with ML-based inpainting and automatic detection. Works on ANY watermark type (Google SynthID, Midjourney, DALL-E, stock photos, logos). Four methods: inpaint (ML, best quality), aggressive (fast), crop (fastest), paint (basic). Auto-detects watermark location in any corner. Use when: (1) Removing ANY type of watermark, (2) Google AI/Imagen/Gemini watermarks, (3) Stock photo watermarks, (4) Logo overlays, (5) Cleaning images for production, (6) Batch processing, or (7) User mentions 'watermark', 'remove watermark', 'clean image', 'SynthID'
Expert in creating, editing, and automating Word documents (.docx) using python-docx and docx.js. Use when generating Word documents, modifying existing docx files, or automating document workflows.
Extract and structure personal context from AI chat transcripts into themed markdown files. Use when (1) Processing Claude, Claude Code, or other AI conversation exports, (2) Building personalized AI assistants from chat history, (3) Creating context files for Claude Projects, GPTs, or Gems, (4) Consolidating scattered knowledge from multiple conversations. Optimized for Claude Haiku.
Generate branded PDFs from markdown files. Use when converting case studies, proposals, or documentation to PDF format. Handles styling, templates, and batch conversion.
Triggered by "tidy up", "clean up transactions", "categorize uncategorized", "organize my transactions"
Execute deep research on every item in a research outline, producing structured JSON per item and a final markdown report. Use after running /research to generate an outline. Reads outline.yaml and fields.yaml, launches parallel research agents in batches, validates output, generates a consolidated report, and supports resume on interruption. Trigger when the user says "start deep research", "research these items", "run the deep phase", "fill in the fields for each item", or "generate the research report".