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Found 1,665 Skills
Specialist in self-healing data pipelines — uses air-gapped local SLMs and semantic clustering to automatically detect, classify, and fix data anomalies at scale. Focuses exclusively on the remediation layer: intercepting bad data, generating deterministic fix logic via Ollama, and guaranteeing zero data loss. Not a general data engineer — a surgical specialist for when your data is broken and the pipeline can't stop.
Signal-based outbound specialist who designs multi-channel prospecting sequences, defines ICPs, and builds pipeline through research-driven personalization — not volume.
Builds data infrastructure — ETL/ELT pipelines, data warehousing, stream processing, data quality, orchestration (Airflow/Dagster), and analytics engineering (dbt). Use when the user asks to build data pipelines, set up ETL/ELT workflows, design a data warehouse, configure stream processing, or implement analytics engineering with dbt, Airflow, or Dagster.
Apply PyGraphistry graph ML/AI workflows such as UMAP, DBSCAN, embedding-based anomaly analysis, and fit/transform pipelines on nodes or edges. Use for feature-driven exploration, clustering, anomaly triage, and graph-AI notebook workflows.
Shotstack integration. Manage Deals, Persons, Organizations, Leads, Projects, Pipelines and more. Use when the user wants to interact with Shotstack data.
Agiled integration. Manage Organizations, Leads, Pipelines, Users, Goals, Filters. Use when the user wants to interact with Agiled data.
Linear project-management CLI for the terminal. Manage issues, projects, cycles, teams, initiatives, roadmaps, and customer records via the Linear GraphQL API with offline-capable SQLite sync. Use when the user asks about their Linear issues, wants today's queue, sprint velocity, team workload, bottlenecks, duplicate / stale / orphaned issues, release pipelines, or wants to create, update, or search Linear items from the terminal. Offline search and analytics work without an API round-trip after a one-time sync.
Use when the user asks to design RAG pipelines, optimize retrieval strategies, choose embedding models, implement vector search, or build knowledge retrieval systems.
Design an end-to-end MotherDuck pipeline. Use when choosing raw, staging, and analytics boundaries, bulk ingestion paths, transformation sequencing, publication targets, or whether DuckLake is actually required.
Spatial data gridding and interpolation with a machine-learning style API. Process geographic and Cartesian point data onto regular grids. Use when Claude needs to: (1) Grid scattered spatial data onto regular grids, (2) Interpolate point data using splines, linear, or cubic methods, (3) Process geographic coordinates with projections, (4) Reduce large datasets using block averaging, (5) Remove polynomial trends from spatial data, (6) Cross-validate gridding parameters, (7) Create processing pipelines with Chain, (8) Grid vector data like GPS velocities.
End-to-end conference talk pipeline: paper → slide outline → Beamer + PPTX → per-page polish → assurance checks (claim / citation / anonymity) → final export and report. Default-good for academic conference talks (NeurIPS / ICML / ICLR / VALSE / 投稿 talks). Trigger phrases: "做 talk", "做 PPT 全流程", "talk pipeline", "end-to-end slides", "做演讲", "conference talk full workflow". Use when the user wants the complete talk artifact, not just a slide deck.
Produces a one-page cross-functional business snapshot for SMB owners — cash position (QuickBooks), sales trend (PayPal/Square), pipeline movement (HubSpot), this week's commitments (Calendar), urgent watch-list items (Gmail/Slack), and the single most important thing needing attention today. Proactively tries every available connector and gracefully scopes to whatever is connected — one connector gives a partial pulse; the full stack gives the full picture. Trigger when the user asks how the business is doing, wants a snapshot, a weekly summary, a Monday brief, or says anything like "what am I missing" or "catch me up on the business."