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3,534 results
- Sequence LoadAnthropicOfficialFind leads matching criteria and bulk-add them to an Apollo outreach sequence. Handles enrichment, contact creation, deduplication, and enrollment in one flow.
- Signature RequestAnthropicOfficialPrepare and route a document for e-signature — run a pre-signature checklist, configure signing order, and send for execution. Use when a contract is finalized and ready to sign, when verifying entity names, exhibits, and signature blocks before sending, or when setting up an envelope with sequential or parallel signers.
- Slack MessagingAnthropicOfficialGuidance for composing well-formatted, effective Slack messages using mrkdwn syntax
- Slack SearchAnthropicOfficialGuidance for effectively searching Slack to find messages, files, channels, and people
- Stakeholder MapAnthropicOfficialMap the people in a deal or account - roles, influence, sentiment, who's missing, and your best access path to the people you haven't reached. Use when the user asks "who are the players at [account]", "who's my way in", "am I single-threaded on [deal]", "map the stakeholders", or "who else should I be talking to".
- StandupAnthropicOfficialGenerate a standup update from recent activity. Use when preparing for daily standup, summarizing yesterday's commits and PRs and ticket moves, formatting work into yesterday/today/blockers, or structuring a few rough notes into a shareable update.
- Synthesize ResearchAnthropicOfficialSynthesize user research from interviews, surveys, and feedback into structured insights. Use when you have a pile of interview notes, survey responses, or support tickets to make sense of, need to extract themes and rank findings by frequency and impact, or want to turn raw feedback into roadmap recommendations.
- User Research SynthesisAnthropicOfficialSynthesize qualitative and quantitative user research into structured insights and opportunity areas. Use when analyzing interview notes, survey responses, support tickets, or behavioral data to identify themes, build personas, or prioritize opportunities.
- Jupyter NotebookOpenAIOfficialUse when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.
- Migrate Ai Sdk V6 To V7VercelOfficialMigrate applications from AI SDK 6.x to AI SDK 7.0. Use when upgrading Vercel AI SDK packages, fixing v7 migration errors, or when the user mentions AI SDK v6, v7, upgrade, migration, breaking changes, system to instructions, fullStream, telemetry, tool context, or finalStep.
- Gke Ai Troubleshooting Node Unresponsive TimeoutGoogleOfficialDiagnose and mitigate GKE TPU or GPU nodes stuck in NotReady / NodeStatusUnknown ("Kubelet stopped posting node status") due to host kernel panics, hardware lockups, or disabled node auto-repair. Use when nodes stop heartbeating beyond the node auto-repair threshold and pods remain stuck in Terminating. Don't use for healthy nodes, pod-only application crashes, or routine GKE upgrades.
- Gke Ai Troubleshooting Tpu Reservation StockoutGoogleOfficialDiagnose and resolve cluster-wide GKE TPU node pool creation or scale-up failures caused by Compute Engine reservation stockouts (GCE_STOCKOUT, ZONE_RESOURCE_POOL_EXHAUSTED) when existing unhealthy or NotReady TPU node pools in the cluster have node auto-repair disabled and hold reserved TPU capacity.
- Gke CostGoogleOfficialOptimizes GKE costs, rightsizes workloads, and configures Spot VMs and CUDs. Use when optimizing GKE costs, rightsizing GKE workloads, or configuring GKE Spot VMs. Don't use for general compute class provisioning or GPU Selection (use gke-compute-classes instead).
- Gke Node NotreadyGoogleOfficialDiagnoses GKE nodes reporting NotReady or Unknown status by inspecting node conditions, events, kubelet/containerd logs, and node metrics, then proposing safe remediations. Use when nodes show NotReady, when the kubelet stops posting node status, or when workloads are evicted or stuck Pending due to node health.
- Gke ScalingGoogleOfficialConfigures GKE autoscaling, including HPA, VPA, and Node Auto-Provisioning (NAP). Use when configuring GKE autoscaling, setting up GKE HPA, setting up GKE VPA, or configuring GKE NAP. Don't use for configuring static cluster sizes or setting node-level machine styles directly (use gke-compute-classes instead).
- Gke Workload ScalingGoogleOfficialManages scaling for GKE workloads using HPA and VPA. Use when configuring Horizontal Pod Autoscaler (HPA), configuring Vertical Pod Autoscaler (VPA), or applying best practices for GKE workload autoscaling. Do not use for cluster-level autoscaling (Cluster Autoscaler), static cluster sizing, or configuring node-level machine styles directly.
- DirectivesVercelOfficialPre-built custom directives for json-render — formatting, math, string manipulation, and i18n. Use when working with @json-render/directives, defining custom directives with defineDirective, or adding $format, $math, $concat, $count, $truncate, $pluralize, $join, or $t to specs.
- JotaiVercelOfficialJotai adapter for json-render's StateStore interface. Use when integrating json-render with Jotai for state management via @json-render/jotai.
- NextVercelOfficialNext.js renderer for json-render that turns JSON specs into full Next.js applications with routes, layouts, SSR, and metadata. Use when working with @json-render/next, building Next.js apps from JSON specs, or creating AI-generated multi-page applications.
- ReduxVercelOfficialRedux adapter for json-render's StateStore interface. Use when integrating json-render with Redux or Redux Toolkit for state management via @json-render/redux.
- XstateVercelOfficialXState Store adapter for json-render's StateStore interface. Use when integrating json-render with @xstate/store for state management via @json-render/xstate.
- ZustandVercelOfficialZustand adapter for json-render's StateStore interface. Use when integrating json-render with Zustand for state management via @json-render/zustand.
- Hf MemHugging FaceOfficialHugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub
- Huggingface Local ModelsHugging FaceOfficialUse to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.