1.9K skills · sorted by relevance
Configure and troubleshoot automatic node scaling in GKE. Examine logs and workload constraints to explain why nodes fail to grow or shrink, and guide tuning for capacity shortages, zone placement, and sudden traffic increases.
Write Apache Cassandra distributed tests that simulate multiple nodes within one JVM, the Java runtime. The guide covers cluster setup, queries, node restarts, message dropping for failure scenarios, and troubleshooting problems caused by isolated class loading.
Write and troubleshoot n8n expressions, the formulas that pass and transform data between workflow steps. Correct field references, read webhook inputs, format dates and text, and query nested JSON while checking for silently missing results.
Build and review server-side APIs with Node.js, Express, and Next.js. The skill provides patterns for separating responsibilities, reducing database queries, caching results, checking access permissions, and handling background work and errors.
Build and maintain MCP servers that let AI assistants use tools, read data, and access reusable prompts. Covers Node/TypeScript implementation, input validation, transport choices for local or remote clients, and registration or connection troubleshooting.
Guide implementation and debugging of visual Sequence editing in Remotion Studio. It documents how sequence identifiers, node paths, and stack traces behave during hot reload, and suggests how to track expanded UI state.
Build graph neural networks, models that learn from connected nodes, with PyTorch Geometric. Supports node and graph classification, link prediction, custom datasets, and training approaches for large graphs or graphs containing multiple types of nodes and connections.
Trace how a web page generates request signatures and encrypted parameters by inspecting network requests and JavaScript execution. Collect runtime evidence, then use it to reproduce the behavior locally in Node.js.
Build Node.js APIs and backend services with Express/Fastify. The skill guides authentication, database integration, error handling, and operational practices such as logging and health checks, which report whether a service is working.
Retire a FastGPT workflow node while preserving existing workflows. The skill guides changes to templates, execution handlers, and interface references so the node disappears from creation menus but still loads, runs, and displays a replacement notice.
Write and troubleshoot n8n expressions, the formulas that pass and transform data between workflow steps. Covers field references, webhook inputs, dates, strings, and choosing between expressions and Code nodes for data transformations.
Plan and configure security across Google Kubernetes Engine clusters. Review access permissions, enable Secret Manager integration, and configure protections such as Shielded Nodes and Binary Authorization to strengthen the platform supporting your applications.
Guide shell, Python, and Node.js execution on the computer running a connected A0 CLI. It explains session reuse, interactive input, output retrieval, and recovery steps when execution permissions, timeouts, or disconnections interrupt the work.
Write and troubleshoot native Python in n8n Code nodes. Covers data filtering and transformation, migration from older Python code, valid return formats, and restricted execution environments, including cases where errors pass unprocessed input downstream.
Use when the user mentions Higgsfield Canvas, a node-based or node graph workspace, an infinite board/canvas, chaining generations into a pipeline, or wants to wire prompts → images → videos across models on one surface. Covers what Canvas is, the node categories, the seven models that run inside Canvas, the named canvas patterns (Simple Seedance, Extend Video, Image Edit, StoryBoard With Elements, Long Video fan-out), the build-free / generate-paid cost model, reusable templates, assets-as-nodes, and Shared Canvas live collaboration. Also trigger on 'Higgsfield ComfyUI alternative', 'node workflow', or 'connect nodes to build a scene/campaign'.
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Audits Claude Code repositories. Two-phase workflow — Phase 1 sweeps 14 hygiene categories (permissions, hooks, CLAUDE.md bloat, Skills hygiene, process-abstraction, plus structural) and an optional 7-layer leak check. Phase 2 executes [APPROVED] markers from the report file. Use for repo cleanup, pre-distribution sanity, post-feature hygiene, environment audit, process-abstraction discovery. Trigger on "audit my CC repo," "sweep my repository for hygiene," "check this CC environment," "find process abstraction candidates," "review my CLAUDE.md," "clean up my .claude directory," "pre-distribution hygiene check," "find layer leaks in my CC setup." Routes structural findings to rootnode-cc-design REMEDIATE. Composes with rootnode-critic-gate. CC-only — does not scan Claude Projects. Do NOT use for building a Skill (use rootnode-skill-builder), compiling a prompt (use rootnode-prompt-compilation), scoring a single prompt (use rootnode-prompt-validation), or auditing a Project (use rootnode-project-audit).
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Diagnose and fix RFDB data disappearing after compaction, where rfdb-server reports a tiny node count (e.g. "15 nodes") on startup despite manifest_index.json showing hundreds of thousands of nodes and segment files existing on disk. Use when: (1) rfdb-server logs "Default database: N nodes" with N orders of magnitude smaller than recent analysis output, (2) /api/stats returns only the most recent commit's nodes, (3) the issue appears AFTER a compaction event (manifest with l1_node_segments populated and node_segments: []), (4) subsequent commits dropped L1 references. Root cause: ManifestStore::create_manifest() initializes l1_node_segments/l1_edge_segments to Vec::new() instead of cloning from current manifest, so any commit AFTER compaction silently orphans all L1 data even though segment .seg files still exist on disk. Compaction injects L1 fields explicitly after create_manifest, but regular commits do not.
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Fix node query issues in Grafema tests when nodes have numeric IDs instead of human-readable IDs, or when `type` field is undefined. Use when: (1) queryNodes returns nodes with numeric IDs like "52710336597754872375318185843222727675" instead of semantic IDs like "net:request#__network__", (2) node.type is undefined but node.nodeType has a value, (3) metadata is a JSON string instead of parsed object, (4) tests fail with "Cannot read property 'length' of undefined" after queryNodes. Covers RFDBServerBackend vs RFDBClient distinction and async generator handling.
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Fix Node.js CLI tools crashing inside Docker containers when host-installed node_modules require a newer Node version than the container provides. Use when: (1) "SyntaxError: Invalid regular expression flags" with /v flag in string-width or similar packages, (2) node_modules installed on host with Node 20+ but container has Node 18, (3) `npm install` with file: protocol creates symlinks that break inside Docker, (4) pnpm workspace packages become broken symlinks in containers. Covers version detection, Node binary mounting, and npm install strategies for cross-version compatibility.
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Structure server-side applications with practical patterns for Node.js, Express, and Next.js API routes. Covers API design, database queries, caching, authentication, error handling, and background jobs, with examples that separate business rules from data access.
Connect an AI agent to Power Automate through FlowStudio MCP. This skill covers authentication, discovering available tools, reusable Python or Node.js helpers, and extracting useful data from responses too large to display directly.
Diagnose GKE TPU slice creation failures caused by shared nodes. Check slice status, partition labels, and monitoring data to identify conflicting resource groups, then provide resolution steps for the user to apply.
Monitor TPU workloads on GKE using system metrics and PromQL, a metrics query language. Check utilization, memory, node availability, and interruptions to investigate infrastructure issues and calculate average recovery times and intervals between interruptions.
Investigate interruptions affecting GPU and TPU workloads on GKE using maintenance labels, monitoring queries, logs, and node scheduling restrictions. The skill helps determine whether host maintenance caused a disruption and recommends workload protection measures when maintenance is confirmed or expected.