This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

Provides guidance for fine-tuning LLMs using the Tinker cloud training API from Thinking Machines Lab. Use when running supervised fine-tuning, reinforcement learning (GRPO/PPO), or LoRA training on cloud GPUs via Tinker's managed infrastructure instead of local compute.

Fast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.

Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

Retrieve ClinGen gene-disease validity assertions for a public gene or disease, and review source-linked public evidence and literature for one supported GRCh38 germline nuclear SNV or simple indel through Folklore Clinical Variant Interpretation MCP. Use when a scientific agent must branch deterministically on resolved, ambiguous, not-found, invalid, unsupported, or unavailable variant outcomes; chain a resolved public variant into related literature or publication details; or preserve evidence provenance without accepting patient, phenotype, family, segregation, or private case data.

Download updated expected app size files from Azure DevOps CI artifacts for the current branch. Use when app size tests fail in CI and the user wants to update the expected files locally. Trigger on "update app size", "download expected files", "fix app size test", or "update expected app size files".

Manage stacked branches and pull requests with the gh-stack GitHub CLI extension. Use when the user wants to create, push, rebase, sync, navigate, or view stacks of dependent PRs. Triggers on tasks involving stacked diffs, dependent pull requests, branch chains, or incremental code review workflows.

Investigate and triage CI failures for dotnet/macios from Azure DevOps build URLs. Use this skill whenever the user shares a DevOps build link, asks about CI failures, wants to understand why a build failed, or asks to investigate test failures on any platform (iOS, tvOS, macOS, Mac Catalyst). Also use when the user says things like "CI is red", "tests are failing", "build broke", or "what happened in CI".

Reference for writing a Workflow tool script (script API and gotchas, pipeline-vs-barrier rules, quality patterns, worked examples). Load before authoring a script for a workflow the user already opted into; it does not itself authorize running one.

Create and manage shared memory — git-tracked repositories hosted on Letta Cloud that are attached to one or more agents and projected into their filesystems. Use when the user wants to share memory or files across agents, store context outside your own MemFS, attach or detach shared memory, or inspect its file history.

Generate images from text prompts (and optionally edit/remix input images). Use when the user asks to create, generate, draw, render, or edit an image, illustration, logo, icon, diagram, or photo.

Captures reviewable before-and-after visual proof from the real Letta Code Ink TUI. Use when a Letta Code PR changes interactive CLI rendering or behavior and needs terminal screenshots or GIFs in its PR body.

Open or file a GitHub issue, bug report, feature request, docs issue, or chore. Add evidence to an existing issue. Run gh issue create or gh issue comment.

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", and whenever they complain about over-engineering, bloat, boilerplate, or unnecessary dependencies.

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", and whenever they complain about over-engineering, bloat, boilerplate, or unnecessary dependencies.

Generate idiomatic Typst (.typ) code, edit and troubleshoot Typst documents and projects, and answer Typst syntax/reference questions. Use when working with .typ files or when the user explicitly asks for Typst document creation, editing, debugging, compilation, formatting, template work, or package usage.

Write effective prompts for Jimeng Seedance 2.0 multimodal AI video generation. Use when users want to create video prompts using text, images, videos, and audio inputs with the @ reference system. Covers camera movements, effects replication, video extension, editing, music beat-matching, e-commerce ads, short dramas, and educational content.

Systematically discover synthesis opportunities across the Obsidian wiki — pairs or clusters of concepts that co-occur frequently across pages but have no synthesis page connecting them. Creates new synthesis/ pages that draw explicit cross-cutting conclusions. Use when the user says "synthesize my wiki", "find connections", "what concepts keep coming up together", "/wiki-synthesize", or after a large ingest when the vault has grown significantly.

Scan the Obsidian wiki for page-level identity collisions — different pages covering the same concept under different names (e.g. "RSC" vs "React Server Components") — and merge them. Use this skill when the user says "dedup my wiki", "find duplicate pages", "merge duplicates", "identity resolution", "consolidate my wiki", "I have duplicate pages", or "my wiki has two pages for the same thing". Distinct from wiki-lint (which checks structure) and cross-linker (which adds links) — this skill makes destructive page-level merges and requires careful confirmation.