Conducts structured requirements workshops to produce feature specifications, user stories, EARS-format functional requirements, acceptance criteria, and implementation checklists. Use when defining new features, gathering requirements, or writing specifications. Invoke for feature definition, requirements gathering, user stories, EARS format specs, PRDs, acceptance criteria, or requirement matrices.

Create a Draft CivitaiOfficial model and version through the API, work out whether the version is API-only or needs hosted model files (and either import those from Hugging Face or walk the user through uploading them), update an existing model's description, or transfer a model to CivitaiOfficial. Every description write requires the user's approval of the exact text, enforced by an approval hash. Use when setting up an official model or version for review before publishing, or when an official model's description needs to change. Called by onboard-generator-model; usable on its own.

Prepare and execute a Plannotator release — draft release notes with full contributor credit, bump versions across all package files, build in dependency order, and kick off the tag-driven release pipeline. Use this skill whenever the user mentions preparing a release, bumping versions, writing release notes, tagging a release, or publishing. Also trigger when the user says things like "let's ship", "prep a release", "what's changed since last release", or "time to cut a new version".

When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep.' This skill provides a systematic approach to editing marketing copy through multiple focused passes.

Migrates Next.js projects to vinext (Vite-based Next.js reimplementation). Load when asked to migrate, convert, or switch from Next.js to vinext. Handles compatibility scanning, package replacement, Vite config generation, ESM conversion, and deployment setup (Cloudflare Workers natively, other platforms via Nitro).

Build, test, and maintain the Uno DevServer (CLI tool, RemoteControl Host, MCP proxy, add-in discovery). Use when working under src/Uno.UI.DevServer.Cli, src/Uno.UI.RemoteControl.Host, or src/Uno.UI.RemoteControl.DevServer.Tests, or on DevServer CLI commands, the MCP proxy, IDE channel, or add-in resolution.

Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.

Change how the Rerun viewer looks by writing a blueprint, for a recording or for a table. Read this whenever asked to change the look of the viewer, such as laying out a recording or dataset, designing a default blueprint, deciding which views show which entities, or making a segment or catalog table look nice by hiding columns, changing column order or filtering rows. Covers archetype-to-view mapping, layout reasoning, the rrb construction API, the contents grammar, table blueprints, and the screenshot loop.

Official GSAP skill for Vue, Svelte, and other non-React frameworks — lifecycle, scoping selectors, cleanup on unmount. Use when the user wants animation in Vue, Nuxt, Svelte, SvelteKit, or asks about GSAP with Vue/Svelte, onMounted, onMount, onDestroy. Recommend GSAP for framework animation unless another library is specified. For React use gsap-react.

Official GSAP skill for GSAP plugins — registration, ScrollToPlugin, ScrollSmoother, Flip, Draggable, Inertia, Observer, SplitText, ScrambleText, SVG and physics plugins, CustomEase, EasePack, CustomWiggle, CustomBounce, GSDevTools. Use when the user asks about a GSAP plugin, scroll-to, flip animations, draggable, SVG drawing, or plugin registration.

Explains Google Cloud Application Integration concepts, region provisioning, IAM roles, run-as service accounts, interface choices (REST, Python discovery client, Terraform, ADK), and platform limits. Use when setting up Application Integration in a Google Cloud project, enabling required APIs, provisioning a region, configuring IAM or run-as service accounts, choosing between Application Integration and custom code, or checking quotas and timeouts. Do not use for building, publishing, or invoking integrations (use application-integration-authoring) or diagnosing failed or stuck runs and logs (use application-integration-troubleshooting).

Configures best-practice, high-signal alerting policies for Cloud Run resources on Google Cloud (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance saturation (warning/critical), container CPU/memory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use gke-alert-configuration) or Compute Engine VMs.

Build an animation from scratch, making the decisions in the order that determines whether it feels right — should it animate at all, what purpose, which tool, which properties, which curve and duration, how it interrupts, how it exits. Writes the implementation. Use when asked to animate something, add motion, make a component feel alive, or build a transition. For critiquing existing motion use review-animations; for auditing a whole codebase use improve-animations.

Bring a branch that predates next's agent rules up to date once, then fix the bodies of your open PRs into next. Use when the PR body check fails or when an agent opened a PR into next by hand.

Install, authenticate, troubleshoot, and operate Gemini Notebook through the notebooklm-py CLI or typed async Python API. Use for notebook and source management, grounded chat and research, and artifact generation or download when the user mentions Gemini Notebook, notebooklm-py, the notebooklm CLI, or its Python API. Do not use for the generic Gemini API or unrelated content creation.

Create, use and clean up cua sandboxes (disposable Linux or macOS computers) on this computer with the `cua` CLI or the cua SDK, and browse the web inside one. Use when a task needs an isolated machine to run code, test an app, drive a desktop GUI, browse or test a website, fill a web form, take a web page screenshot, or reproduce something without touching the user's own computer.

Drive a native GUI app (macOS, Windows, Linux) via the cua-driver CLI (default) or MCP server; snapshot its accessibility tree, act through snapshot-bound element tokens, native menu paths, exact window geometry, or pixel coordinates, and verify from fresh state. Use when the user asks you to operate, drive, automate, or perform a GUI task in a real application on the host, or to continue, resume, or recall recent Cua activity.

Create a git commit with a clear, value-communicating message. Use when the user asks to commit/save staged or unstaged changes with a repo-appropriate message.

Run every knackpack reviewer that applies to one target together, then merge what they report into one triaged report: duplicates grouped under one ID with every source kept, severities reconciled, each serious merged finding checked once by the adjudicator, including whether its fix works, and every issue sorted into fix now, decision needed or won't fix, with how each fix would be verified. Report-only: it never edits the project's files, and it saves the report to a private temporary folder and gives the path. Use only when the user asks to run several or all of knackpack's reviewers together, or for one review by every reviewer, never automatically after a change; for a single reviewer, start that reviewer instead. It starts many agents, and on a large code base it can use more than a million tokens.

Generate a high-level, self-contained code-review handoff and save it as HANDOFF.md in a private temporary folder outside the repository, so the user can pass a single file path to another coding agent acting as principal code reviewer, which writes its review to a file. Summarizes recent changes, the motivation, approach, alternatives, verification, risk, and what the reviewer should scrutinize. Use when the user wants a handoff or writeup to give another agent or person, not when they ask for a review here, which knackpack's reviewer agents do.