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Found 6,256 Skills
Automates npm release workflows using changesets. Creates a changeset (default patch), fixes lint/test/typecheck/format issues, commits and pushes, watches CI via the Monitor tool, finds and merges the Version Packages PR opened by changesets/action, and watches the release workflow to completion. Use when the user asks to ship, release, publish, autoship, or cut a release for an npm package.
Low-Code Generation uses AI to produce forms, tables, dashboards, and workflow UIs from natural language descriptions or schema definitions.
Run, watch, debug, and extend OpenClaw QA testing with qa-lab and qa-channel. Use when Codex needs to execute the repo-backed QA suite, inspect live QA artifacts, debug failing scenarios, add new QA scenarios, or explain the OpenClaw QA workflow. Prefer the live OpenAI lane with regular openai/gpt-5.4 in fast mode; do not use gpt-5.4-pro or gpt-5.4-mini unless the user explicitly overrides that policy.
Use when the agent wants to define, list, inspect, or execute GUI macros via the OpenClaw Macro System CLI. Macros are parameterized, CLI-callable workflows — the agent invokes `macro run <name>` and the system handles backend routing (plugin, file transform, accessibility, compiled GUI replay).
This skill should be used when the user asks for a publication-quality scientific figure or table, wants help choosing the right chart for results, needs a paper-ready pubfig or pubtab workflow, wants a figure + companion table for a results section, wants an Excel sheet turned into publication-ready LaTeX, or wants an existing scientific figure/table reviewed and upgraded.
Background knowledge for droid-control workflows -- not invoked directly. Capture ground-truth byte sequences from real terminal emulators.
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.
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.