Skills worth trusting.
Agent skills from Anthropic, OpenAI, skills.sh, ClawHub, SkillsMP and other reputable sources. Savant assesses them for security risks and evaluates model-generated test cases using independent scoring. Workspaces import any skill into their own repositories through a reviewed pull request. Every listing on each hub is enumerated; packages are fetched, scanned and evaluated most-popular first as daily capacity allows.
company-watch
Watches a company or topic on podcasts and YouTube: what was said lately (shows, counts, momentum, quotes), then an Arcmira monitor to keep following it.
scientific-visualization
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.
block-inventory
Use this when the page-import pipeline needs to survey the block palette available from a local AEM Edge Delivery Services project and the Block Collection to inform content modeling decisions. Scans local block folders, searches the Block Collection for common blocks, resolves each block's purpose, and returns a consolidated block inventory annotated with per-block purpose and availability. Do not invoke directly — called by page-import as a pipeline step.
sponsor-research
Sponsor and ad-read research on podcasts and YouTube: who sponsors a show, or which shows a brand sponsors, how often, since when. Uses arcmira.
find-quotes
Finds exact spoken quotes and clip-ready moments on podcasts and YouTube: verbatim words, speaker, date, a timestamped link, clip start and end. Uses arcmira.
compare-shows
Compares two podcasts or YouTube shows side by side: size, latest episode, what each talks about, what both cover, and shared sponsors. Uses arcmira.
storage-analyzer
macOS / Windows 只读存储分析助手（自动识别系统）。扫描整机磁盘占用，找出 占空间大户，把每一项分成 🟢可自动清理 / 🟡需人工判断 / 🔴谨慎清理 三级并给出 可执行处置方案，生成排版精美、可折叠、命令可一键复制的交互式 HTML 报告，并可 起本地服务在网页上一键删除（移废纸篓/直接删）。扫描全程只读。务必在以下场景 使用：用户说"存储分析""磁盘满了""C盘/硬盘满了""空间不够""清理空间" "清理磁盘""占空间""哪些东西占地方""帮我看看存储""看一下电脑存储/空间" "存储空间""电脑空间不够""内存满了/不够/不足""看下内存/存储"（中文口语里 "内存"常指存储空间）"storage analysis""disk cleanup""清缓存""磁盘清理"； 或用户抱怨电脑没空间、想知道什么东西吃硬盘、想要清理建议时。注意：若用户明确 指运行内存/RAM（如"哪个进程吃内存""内存占用高"想看活动监视器），那是 RAM 不是存储，不属于本 skill。
microsoft-sharepoint
Microsoft Sharepoint integration. Manage Sites. Use when the user wants to interact with Microsoft Sharepoint data.
platform-strategy
Help users design and execute platform business strategies. Use when someone is building a marketplace, creating an ecosystem, deciding on API strategy, thinking about multi-sided network effects, or building developer platforms.
content-driven-development
Use this when making any AEM Edge Delivery Services (EDS, Franklin, Helix) code change — new blocks, block modifications, CSS styling, bug fixes, core functionality (scripts.js, styles, delayed.js), or any JavaScript/CSS work that needs validation. Covers the Content Driven Development process — identifying or creating real test content before writing code, designing an author-friendly content model, and validating against that content throughout development. Do not use for documentation-only changes or configuration changes that do not affect authoring.
coaching-pms
Help users develop and coach product managers. Use when someone is managing PMs, creating development plans, running performance reviews, or trying to level up their PM team's capabilities.
cross-functional-collaboration
Help users work effectively across functions. Use when someone is navigating PM-engineering relationships, resolving cross-team conflicts, building product trios, or improving handoffs between design, engineering, and product.
platform-infrastructure
Help users build and scale internal platforms and technical infrastructure. Use when someone is deciding whether to build vs buy tooling, designing developer platforms, creating shared services, or managing technical debt at scale.
building-sales-team
Help users build and scale their sales organization. Use when someone is hiring their first salespeople, deciding when to bring on sales leadership, structuring sales compensation, or transitioning from founder-led sales.
managing-timelines
Help users set and hit realistic deadlines. Use when someone is planning project timelines, struggling to hit deadlines, dealing with timeline pressure from stakeholders, or trying to improve estimation accuracy.
scoping-cutting
Help users scope projects and cut features effectively. Use when someone is defining an MVP, dealing with scope creep, trying to ship faster, or needs to make tradeoffs about what to build.
playwright-scraper
Playwright web scraping: dynamic content, auth flows, pagination, data extraction, screenshots
content-modeling
Use this when you are building new AEM Edge Delivery Services blocks or changing the initial structure that authors work with in an existing block. Covers designing content models that are easy for authors to use.
analyze-and-plan
Use this when you need to define acceptance criteria, write requirements, scope work, or create a definition of done for AEM Edge Delivery Services (EDS) tasks such as new blocks, variants, behavior modifications, CSS-only changes, or bug fixes. Covers analyzing development requirements, producing task breakdowns, identifying edge cases, and documenting the analysis.
evaluating-candidates
Help users make better hiring decisions. Use when someone is evaluating job candidates, making hiring decisions, conducting reference checks, reviewing work samples or take-homes, calibrating their hiring bar, or deciding between finalists.
tao-run-on-brev
Run a TAO training/evaluation/inference container on an NVIDIA Brev GPU instance. Instance provisioning (create/search/stop/delete/login) is delegated to the official brev-cli agent skill or the Brev MCP server; this skill covers only the TAO-specific part — running the container over `brev exec` via the four-verb docker contract. Trigger phrases include "run on Brev", "Brev GPU instance", "TAO on Brev", "submit job to Brev".
organizational-design
Help users design effective organizational structures. Use when someone is thinking about team structure, deciding between functional vs. divisional models, planning a reorg, or figuring out how to structure product teams.
code-simplifier
Code simplification skill for improving clarity, consistency, and maintainability while preserving exact behavior. Use when simplifying code, reducing complexity, cleaning up recent changes, applying refactoring patterns, or improving readability. Triggers on tasks involving code cleanup, simplification, refactoring, or readability improvements.
tao-run-deft-aoi
Run the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models: baseline evaluate, RCA, Cosmos AnomalyGen / AMP synthetic defects, k-NN mining, retraining, and deployment gating against a customer-defined primary metric and optional constraints. Use only when the request identifies an AOI / automated-optical-inspection, PCB-defect, VisualChangeNet, or ChangeNet workflow. Supports air-gapped/offline runs with pre-staged assets. Never infer AOI from generic iterative-improvement language. Do not use for CLIP / SigLIP image retrieval, attribute-labelled image data, standalone TAO training, one-off inference, generic anomaly generation, or RCA-only analysis.
tao-train-visual-changenet
Visual ChangeNet for binary image classification and segmentation in AOI defect detection. Use when training, evaluating, exporting, or running inference for PCB defect detection or visual inspection, comparing image pairs for PASS/NO_PASS classification, or producing change-segmentation masks. Trigger phrases include "train Visual ChangeNet", "ChangeNet classify", "ChangeNet segment", "AOI defect detection", "PCB inspection model".
tao-train-mask-auto-label
MAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".
shipping-products
Help users ship products faster and with higher quality. Use when someone is planning a launch, struggling to release features, dealing with shipping velocity issues, or trying to establish better release practices.
release-management
Manage music releases using RELEASE.md documents stored in releases/{release-slug}/ within an artist workspace. Triggers when the user mentions an artist's album, EP, single, or project — or asks about release planning, DSP pitches, metadata, marketing, press materials, physical production, or tour coordination. First infer which artist and release the user means, then find or create the RELEASE.md. Use this skill to create, update, or pull data from release documents, and to generate deliverables like DSP pitches, press one-sheets, and production specs.
aws-solution-architect
Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, and cost optimization.
generate-import-html
Use this when the page-import pipeline needs to produce structured HTML from authoring analysis for AEM Edge Delivery Services. Covers building section structure, applying block tables, handling metadata, and managing the images folder. Do not invoke directly — called by page-import as a pipeline step.
energy-management
Help users manage their energy for sustained performance. Use when someone is feeling burned out, trying to find their zone of genius, scheduling for productivity, or identifying what drains vs energizes them.
tao-mine-aoi-images
Runs the DEFT embed-then-mine workflow for VCN AOI iterations — embeds the gap-analysis target parquet, embeds a source pool, and mines nearest-neighbour source images for downstream augmentation. Use as the immediate next step after `tao-route-visual-changenet-samples` when expanding a real-image augmentation queue from the mining subset.
firecrawl-alexandria
Find a direct path to structured data through ready-made workflows, data APIs, and indexes. Follow the search skill to discover and inspect tools, then the scrape skill to execute them.
tao-train-deformable-detr
Deformable DETR for 2D object detection. Uses deformable attention for efficient multi-scale feature processing, lighter than DINO with competitive accuracy. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Deformable-DETR model. Trigger phrases include "train deformable-detr", "Deformable DETR object detection", "lightweight DETR detector".
tilegym-monkey-patch-kernels-to-transformers
Integrate TileGym kernels into Hugging Face `transformers` models by replacing the library's submodule(s) and certain class(es)' implementations, and patching certain class(es)' init/forward/load weight methods prior to instantiating models. Used when the user requires integrating TileGym kernels into `transformers` models.
agent-integration
Integrate a raw customer agent repo with Veris end to end. Installs or verifies veris-cli, logs in, creates or reuses a Veris environment, analyzes the repo, generates or updates `.veris/veris.yaml`, `.veris/Dockerfile.sandbox`, `.veris/.dockerignore`, configures runtime env vars, and can finish with `veris env push`. Use when a repo has no Veris setup yet, or when an existing `.veris/` integration is stale and needs to be refreshed.
testrail
Sync tests with TestRail. Use when user mentions "testrail", "test management", "test cases", "test run", "sync test cases", "push results to testrail", or "import from testrail".
tao-train-oneformer
OneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".
tao-train-sparse4d
Sparse4D for multi-camera temporal 3D object detection and tracking. Uses sparse queries with deformable attention across camera views and time for end-to-end 3D perception, with an instance bank for temporal tracking. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Sparse4D model. Trigger phrases include "train Sparse4D", "multi-camera 3D detection", "temporal 3D tracker", "sparse query 3D perception".
having-difficult-conversations
Help users navigate tough feedback, performance conversations, and conflict. Use when someone needs to give hard feedback, have a performance conversation, fire someone, address conflict with a colleague, or deliver disappointing news like a denied promotion.
mod-any-game
Mod a PC game the user owns, taking an idea to working in the real game and recorded. It covers new items, weapons, enemies, bosses, units, civilizations, mechanics, art, sound, VR and cross-game mashups. Use when the user wants to mod, extend, hack on, reverse engineer or mash up a game ("add a nuke to Terraria", "make a new civ for Age of Empires", "put Minecraft inside X", "can I mod this game?"). It covers recon (engine, loaders, anti-cheat), choosing the route, a safe lab, a first vertical slice, fal-generated assets, in-game verification and a showcase clip.
kotlin-multiplatform
Platform abstraction decision-making for Amethyst KMP project. Guides when to abstract vs keep platform-specific, source set placement (commonMain, jvmAndroid, platform-specific), expect/actual patterns. Covers primary targets (Android, JVM/Desktop, iOS — all mature) with web/wasm as possible future targets. Integrates with gradle-expert for dependency issues. Triggers on: abstraction decisions ("should I share this?"), source set placement questions, expect/actual creation, build.gradle.kts work, incorrect placement detection, KMP dependency suggestions.
writing-job-descriptions
Help users write effective job descriptions. Use when someone is creating a job posting, defining a new role, preparing to hire, or trying to attract the right candidates for an open position.
tilegym-improve-cutile-kernel-perf
Iteratively optimize cuTile kernel performance through systematic profiling, bottleneck analysis, IR comparison, and targeted tuning. Covers tile sizes, occupancy, autotune configs, TMA, latency hints, persistent scheduling, num_ctas, flush_to_zero, and IR-level debugging. Use when asked to "optimize cutile kernel", "improve kernel perf", "tune cutile performance", "make kernel faster", or iteratively benchmark and refine a cuTile GPU kernel in the TileGym project.
managing-tech-debt
Help users manage technical debt strategically. Use when someone is dealing with legacy code, planning refactoring work, deciding between rewrites vs. incremental fixes, trying to get buy-in for tech debt reduction, or balancing new features with maintenance.
reverse-engineering
Read how a game actually works so a mod can hook it. Decompile .NET/Mono (ILSpy), IL2CPP (Cpp2IL, Il2CppDumper), Java (Vineflower) and native code (Ghidra, IDA, via MCP servers); dump data and asset formats; reverse-engineer a binary file format and prove it with a round trip; read live memory (Cheat Engine, Frida, x64dbg); find render passes (RenderDoc). Use when a mod needs game internals, e.g. "how does the boss AI work", "find the damage function", "what format is this .sld/.pak/.dat", "where is the player position in memory".
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
evaluating-new-technology
Help users evaluate emerging technologies. Use when someone is assessing new tools, making build vs buy decisions, evaluating AI vendors, or deciding on technical architecture.