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Found 1,266 Skills
Expert knowledge for Azure Functions development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building HTTP/queue/event-triggered Functions, Durable orchestrations, containerized Functions, CI/CD, or Dapr/OpenAI integrations, and other Azure Functions related development tasks. Not for Azure App Service (use azure-app-service), Azure Logic Apps (use azure-logic-apps), Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service).
Produce programmable videos with Remotion using scene planning, asset orchestration, and validation gates for automated, brand-consistent video content.
6sense platform help — Signalverse Intent Data, Predictive Analytics (6AI Scoring), Sales Intelligence (Sales Copilot), AI Email Agents (Conversational Email), Advertising & Audience Activation, Orchestration Workflows, Segments, Company Identification API, People/Company Enrichment API, Company Discovery, Campaign Analytics. Use when asking 'how do I set up 6sense', '6sense intent data', '6sense predictive scoring', '6sense AI email agents', '6sense advertising', '6sense segments', '6sense API', '6sense Sales Intelligence', '6sense vs Demandbase'. Do NOT use for intent strategy across tools (use /sales-intent), lead scoring strategy across tools (use /sales-lead-score), enrichment strategy across tools (use /sales-enrich), B2B advertising strategy across tools (use /sales-b2b-advertising), or cadence/sequence strategy across tools (use /sales-cadence).
Iterative code refinement through plan → code → evaluate → refine cycles. Runs lint checks (ruff), tests (pytest), and structured self-evaluation each cycle, then diagnoses failures and refines. Decomposes complex tasks into sequential phases, iterates up to 3 times per phase (10 total). Use when: the main agent delegates a code task with 'MODE: MORE_EFFORT', the user selects 'More Effort' code generation mode, or the task explicitly requests iterative refinement for higher code quality. Do NOT use for single-pass code generation (Lite mode), experiment pipeline orchestration (use experiment-pipeline), or diagnosing a specific experiment failure (use experiment-craft).
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.
Scaffold and maintain a reusable research → design → plan → orchestrate → act folder for any non-trivial work — software features, marketing campaigns, org changes. Drops a domain-agnostic spine (00-README · 01-plan · 02/03 research · 04-discussion newest-first · 05-tracking · 09-orchestration · artifact/board.html plan-board) plus stateless action-skills that augment the docs in place without clobbering hand-written prose. Composes ikenga-artifact-builder, huashu-design, frontend-design, ikenga-pkg-builder when present; degrades gracefully when not. Profile-driven: `software` (rich default, code work), `general` (lean, non-code — campaigns, org changes), and `content` (editorial/marketing with key art). TRIGGER when the user asks to start a real plan for non-trivial work ("plan a feature," "scaffold a plan folder," "set up groundwork for…"), references an existing plans/ folder by groundwork structure, or runs any of these actions: groundwork init / research / design / review / clarify / orchestrate / refresh-board / refresh-living-spec / status. DO NOT TRIGGER for one-off code changes, single-document writeups, ADRs, or content that fits in a single markdown file — those don't need a multi-doc plan folder. If the user just wants a single artifact (dashboard, mockup), route to ikenga-artifact-builder instead.
Design and implement Internal Developer Platforms (IDPs) with self-service capabilities, golden paths, and developer experience optimization. Covers platform strategy, IDP architecture (Backstage, Port), infrastructure orchestration (Crossplane), GitOps (Argo CD), and adoption patterns. Use when building developer platforms, improving DevEx, or establishing platform teams.
Automatically discover data pipeline and ETL skills when working with ETL, data pipelines, streaming, batch processing, data validation, or pipeline orchestration. Activates for data development tasks.
Use when building networks that grow, prune, or adapt topology during training. Routes to continual learning, gradient isolation, modular composition, and lifecycle orchestration skills.
Explore-lane experimental execution skill for deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with results summarized in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, or implicit experimentation.
Interact with KWeaver Knowledge Network and Decision Agent — build knowledge networks, query Schema/instances, semantic search, execute Action, Agent CRUD and conversation, Trace data analysis. Interact with Dataflow document processes — list processes, trigger runs, query run history, view step logs. Interact with Skill management module — register Skill, search in market, progressive reading, download and installation. Interact with Toolbox / Tool — create toolbox, upload OpenAPI tools, publish, start and stop. Interact with Vega observability platform — query Catalog/resources/connector types, health inspection. This skill is automatically activated when users mention intents such as "knowledge network", "knowledge graph", "query object type", "execute Action", "what Agents are there", "create Agent", "converse with Agent", "list all Agent templates", "list Agents I created", "list Agents in private space", "dataflow", "data flow", "process orchestration", "process run records", "process logs", "trigger dataflow", "view dataflow run history", "Skill", "skill package", "register Skill", "install Skill", "read SKILL.md", "toolbox", "toolbox", "upload tool", "register tool", "OpenAPI tool", "enable tool", "publish toolbox", "data source", "data view", "atomic view", "Catalog", "Vega", "health check", "inspection", "trace", "evidence chain", "data flow tracking", "data source", "how data is obtained", etc.
Use when managing Alibaba Cloud Intelligent Cloud Editing (ICE) media workflows via OpenAPI/SDK, including media processing jobs, template/workflow orchestration, editing and production pipelines, and job status troubleshooting.