Loading...
Loading...
Found 6,252 Skills
Read.ai platform help — meeting intelligence with engagement/sentiment analytics, Search Copilot across meetings/email/chat, Ada digital twin, REST API (beta) + MCP Server (`api.read.ai/mcp/`), OAuth auth, webhook automations (`meeting_end` events with HMAC signing), CRM sync to Salesforce/HubSpot, Zapier/n8n workflows, 20+ language transcription. Use when setting up Read.ai webhooks or API integration, connecting Read.ai transcripts to a CRM or data warehouse, configuring Read.ai engagement analytics for a sales team, comparing Read.ai pricing tiers, troubleshooting Read.ai auto-joining meetings without permission, or setting up the Read.ai MCP server with Claude or Cursor. Do NOT use for picking between note-takers (use /sales-note-taker) or reviewing a specific call for coaching (use /sales-call-review).
Full-stack integration expert specializing in the Feishu (Lark) Open Platform — proficient in Feishu bots, mini programs, approval workflows, Bitable (multidimensional spreadsheets), interactive message cards, Webhooks, SSO authentication, and workflow automation, building enterprise-grade collaboration and automation solutions within the Feishu ecosystem.
This skill handles the workflow of chapter screenshots and illustrations during book writing. It applies to: sorting out which screenshots are needed for a chapter, providing step-by-step practical prompts for Claude Code, defining the mapping between screenshot filenames and figure numbers, filling image positions in local Markdown, cleaning up author notes to create reader-facing text, and synchronizing chapters and images to Feishu Docs in the correct positions. This skill should be triggered when users mention terms like "book screenshots", "chapter illustrations", "figure number correspondence", "insert into original text", "upload to Feishu Docs", or "follow the previous workflow".
ClickHouse integration. Manage data, records, and automate workflows. Use when the user wants to interact with ClickHouse data.
Multi-source literature search, citation verification, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (BibTeX, related articles, ID conversion) via MCP tools (PubMed, CrossRef, arXiv). Use when the user needs coordinated multi-step literature workflows beyond a single MCP call.
Internal support skill for agent-browser CLI workflows used by rust-learner, docs-researcher, and crate-researcher. Use only when browser automation is explicitly required.
External verl end-to-end validation workflow for Megatron-Bridge model/provider changes. Covers running a small verl Megatron backend job from a Bridge checkout, choosing LoRA/DDP plus optional save/resume and parallelism variants, setting PYTHONPATH so verl imports the local Bridge tree, and reporting pass/fail evidence.
Use when a codebase, product, workflow, runtime, or organization needs purpose-first whole-machine stewardship: understand what the whole system is trying to produce, then improve the machinery, tooling, feedback loops, operability, and developer flow that let it produce that output.
Builds site selection and cannibalization analysis workflows in CARTO. Triggers when the user mentions site selection, cannibalization, cannibalizing, new store location, where to open, optimal location, facility placement, network impact, overlapping catchments, twin areas, similar locations, look-alike areas, find locations like my best, store overlap, revenue impact of new store, commercial hotspots, demand hotspots, location scoring, location ranking, expand network, new branch, franchise placement, EV charging siting, or wants to evaluate candidate sites, quantify overlap between trade areas, or find areas that resemble top-performing locations.
Use for VSS alert workflows — real-time monitoring, Alert-Bridge subscriptions, Slack notifications, incident queries, camera onboarding. Not for non-alert analytics.
Create a SageMaker endpoint (real-time or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever about to create a SageMaker endpoint, write deployment code that calls `create_endpoint`, or finalize a deployment after the image URI and IAM role are known. Provides deploy.py for real-time endpoints and deploy_async.py for async endpoints (with genuine scale-to-zero support). This is the last step in the SageMaker deployment workflow. Never generate a bare `create_endpoint` call without these defaults — endpoints without autoscaling or alarms are demos, not deployments.
Trigger when: (1) User mentions "manimgl" or "ManimGL" or "3b1b manim", (2) Code contains `from manimlib import *`, (3) User runs `manimgl` CLI commands, (4) Working with InteractiveScene, self.frame, self.embed(), ShowCreation(), or ManimGL-specific patterns. Best practices for ManimGL (Grant Sanderson's 3Blue1Brown version) - OpenGL-based animation engine with interactive development. Covers InteractiveScene, Tex with t2c, camera frame control, interactive mode (-se flag), 3D rendering, and checkpoint_paste() workflow. NOT for Manim Community Edition (which uses `manim` imports and `manim` CLI).