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Found 6,494 Skills
Expert in using ktx, the executable context layer for data and analytics agents that enables accurate querying through MCP with skills, memory and a semantic layer
Use truffler to find similar or pre-existing JavaScript/TypeScript symbols before implementing new code, especially helpers, utilities, parsers, formatters, scanners, fuzzy matchers, and other reusable functions. Agents should use this skill whenever they are about to add or refactor functionality in a JS/TS repository and need to avoid duplicating existing code, even if the user does not explicitly mention deduplication.
Inspect an existing memory corpus (wiki substrate) and align it to this repo's Obsidian-friendly note-graph conventions. Use this when the user wants to import, normalize, retrofit, or clean up existing memory, notes folder, vault, docs tree, or mixed markdown knowledge base. In monorepos, also use it to align relevant AGENTS.md and CLAUDE.md files. Excludes goals/ from normalization. Not for routine wiki maintenance; use /loam::linting-memory for that.
Correct or update existing wiki content when newer evidence shows the wiki is wrong, stale, incomplete, or contradicted. Use this when the agent discovers the wiki says X but we now know Y, when code or real-world changes invalidate a wiki claim, or when the user asks to fix or amend the wiki. Not for adding new sources, routine learnings capture, structural normalization, or health checks; use /loam::adding-to-memory, /loam::learning-from-session, /loam::normalizing-memory, or /loam::linting-memory.
Author and review GitHub Actions workflow YAML safely so syntactically-valid YAML can't ship a workflow that GitHub Actions refuses to run. USE FOR: editing, adding, or reviewing any file under .github/workflows/, writing run-name/name/if/env/run values that contain ${{ }} expressions, diagnosing a run that fails with 'This run likely failed because of a workflow file issue' and no jobs starting, deciding when a workflow scalar must be quoted, validating workflows with actionlint. DO NOT USE FOR: authoring application YAML unrelated to GitHub Actions, Azure Pipelines, GitLab CI, or non-workflow YAML. SCOPE: this skill covers *syntactic/structural* correctness of workflow YAML (quoting, parsing, actionlint); for *semantic and functional* workflow design (what a workflow should do, agentic-workflow behavior), see .github/agents/agentic-workflows.agent.md — the two are complementary. INVOKES: actionlint (downloaded pinned binary) plus git/grep for inspection.
Use when streaming durable workflow updates to a UI in real time — live order status pages that animate as steps complete, AI agent token streaming from a function to the browser, log tailing for long-running jobs, or human-in-the-loop approval flows that publish a prompt and wait for a user reply. Covers Inngest v4 native realtime: defining typed channels, publishing from inside step.run, minting subscription tokens via server actions, and consuming the stream from React/Next.js client components.
Deploy a production self-hosted n8n end-to-end to a fresh Linux VM over SSH, using Docker Compose behind a Caddy reverse proxy with automatic HTTPS. Use whenever the user wants to self-host, install, set up, provision, or deploy n8n on their own server/VPS/box (Hetzner, DigitalOcean, AWS EC2, bare metal, etc.) — in either single/regular mode or queue mode with workers — or to update, back up, restore, or harden such an instance. This is for SELF-HOSTED n8n (Docker), not n8n Cloud and not building workflows. The skill makes the agent ask single-vs-queue first, collect the domain/SSH/timezone inputs, generate fresh secrets on the box, and bring the stack up with TLS. Trigger on "deploy n8n", "self-host n8n", "install n8n on my server", "n8n docker compose", "n8n queue mode / workers / scaling", "n8n reverse proxy / SSL", or "back up / update my n8n".
Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.
Answer questions about the Paseo product and app, including setup, configuration, connectivity, providers, workspaces, updates, logs, and troubleshooting. Use when a user inside Paseo asks how Paseo works, how to configure it, or why something is broken; use the paseo skill instead to operate agents and workspaces through MCP or the CLI.
Before showing the founder any substantive GTM deliverable (positioning, value prop, homepage, launch post, pricing, sales script, the brief or roadmap), stress-test it against the standard as an independent critic, because the agent that wrote it is the worst judge of whether it is good. Use as a gate right before presenting work, or when the founder asks whether something is actually strong.
Sweep current cross-platform hotspots and surface emerging keywords from the latest crawl batch. Use when the user asks 今日热点 / 今天有什么热点 / 今天热搜 / 各平台热搜 / 看一下当前热搜 / 现在在火什么 / 全网热点 / 全网在聊什么 / what's trending / what's trending now / multi-platform trend sweep / hotspot snapshot, or wants a quick snapshot of zhihu / weibo / douyin / bilibili / toutiao / baidu / thepaper / ifeng / tieba / cls-hot / wallstreetcn-hot at once via the trendradar MCP. Combines latest news with both preset-keyword extraction and emergent auto-extraction so the agent can flag 全网共振 (cross-platform resonance) and 新冒头 (newly emerging) terms in a single pass.
Convert W&B Table artifacts into non-destructive EvalTable previews with scan-first planning, typed input/output/score columns, bounded batches, verification, and safe removal. Use when a coding agent needs to create, inspect, compare, verify, or remove W&B EvalTable previews.