Research roadmap for a legal issue — statutes to check, case law areas to investigate, regulatory frameworks, Westlaw search terms. Leads and frameworks, NOT authoritative citations; students verify and develop everything. Use when a student asks where to start researching, wants a research roadmap for an issue, or needs gaps identified in existing research.

Prep for a cold-call — predict the professor's likely questions and drill them Socratically, flagging where you're shaky so you know what to re-read before class. Use when the user says "prep for class tomorrow", "cold call [case]", "what might [professor] ask on", or points at assigned reading.

Run the PinchTab stealth-score sweep against 15 bot-detection / fingerprint sites (sannysoft, rebrowser, deviceandbrowserinfo, iphey, whoer, browserscan, pixelscan, fingerprint-scan, incolumitas, fvision, amiunique, browserleaks, creepjs, coveryourtracks, fingerprint-demo). Starts a Docker PinchTab container per browser (chrome / cloak / both), spawns a blind agent that drives PinchTab through plain-English per-site playbooks, captures structured metrics, prints a side-by-side comparison highlighting divergent metrics, and appends to history.jsonl for cross-session tracking. Use when asked to 'run stealth score', 'compare cloak vs chrome detection', 'measure stealth', or '/pinchtab-stealth-score'.

AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.

Ensure a usable SageMaker execution role exists before deploying or training. Use this skill whenever about to create a SageMaker endpoint, model, training job, or any resource that requires an execution role. Use it especially when the user has not provided a role ARN explicitly, when scripts are about to call `iam:CreateRole`, or when an AccessDenied error mentions an IAM action. Never blindly call `iam:CreateRole` — always check for existing roles first. This skill prevents the most common SageMaker deployment failure: trying to create IAM resources from an SSO principal that has no IAM write permissions.

Kubernetes network security audit skill powered by Kubeshark MCP. Use this skill whenever the user wants to audit a cluster for security threats, detect compromised workloads, find malicious traffic patterns, hunt for indicators of compromise (IOCs), check for data exfiltration, identify C2 (command and control) communication, detect cryptomining, find lateral movement, discover credential theft attempts, assess network security posture, or perform threat hunting in Kubernetes. Also trigger when the user mentions security audit, threat detection, compromise assessment, vulnerability scan, "is my cluster compromised", "find malicious traffic", "check for threats", DNS exfiltration, DNS tunneling, port scanning, IMDS access, reverse shell, crypto miner, MITRE ATT&CK, IOC detection, anomaly detection, suspicious traffic, rogue workloads, unauthorized access, or any request to evaluate cluster security through network traffic analysis.

OllyGarden's opinionated, optimization-first OpenTelemetry Collector configuration for a Kubernetes node agent (DaemonSet). Use when authoring or reviewing a node-level/agent collector config for logs, metrics, and traces on Kubernetes, or when the user wants to reduce telemetry volume, cost, cardinality, or noise at collection time. Triggers on "collector daemonset config", "node agent collector", "otel collector on kubernetes", "reduce telemetry cost in the collector", "tune kubeletstats/hostmetrics/filelog", "drop noisy spans/logs/metrics in the collector".

Use when the user wants the dsh agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, skill/memory consolidation, or says things like 'make my agent better the more I use it', 'review my past sessions', 'learn my preferences', 'consolidate what you learned', 'run the sleep cycle', or wants to schedule background self-optimization. Drives the skillopt_sleep engine through the skillopt_* tools: harvest past sessions -> mine recurring tasks -> replay via a selected backend -> consolidate validated skills behind a held-out gate.

Implementation details for EF Core test infrastructure. Use when changing test fixtures, SQL baseline assertions, test helpers, the test class hierarchy, or when adding new tests.

CLI tool for creating, managing, and exporting AI-generated presentations via the Banana Slides API. Use when the user asks to: (1) generate a PPT/presentation/slides from an idea, outline, or description, (2) export a project to PPTX, PDF, or images, (3) batch-generate multiple presentations, (4) manage projects, pages, materials, or templates programmatically, (5) renovate/redesign an existing PPT or PDF, (6) edit slide images with natural language.

飞书云空间（云盘/云存储）：管理 Drive 文件和文件夹，包含上传/下载、创建文件夹、复制/移动/删除、查看元数据、查询权限设置、评论/权限/订阅、标题、版本、飞书文档密级标签（secure labels）和本地文件导入。用户需要整理云盘目录、处理云空间资源 URL/token、判断链接类型/真实 token/标题，或导入 Word/Markdown/Excel/CSV/PPTX/.base 为 docx/sheet/bitable/slides 时使用；doubao.com 云空间 URL/token 也按资源路径和 token 路由，不回退 WebFetch。不负责：文档内容编辑（走 lark-doc）、表格/Base 表内数据操作（走 lark-sheets/lark-base）、知识空间节点/成员管理（走 lark-wiki）、原生 Markdown 文件读写/patch/diff（走 lark-markdown）。

Create or update a Flet release announcement blog post from changelog notes, matching existing /blog style. Use when asked to draft, plan, or revise posts like "Flet X.Y.Z release announcement" with major feature sections, screenshots, code samples, upgrade instructions (pip and uv/pyproject.toml), and a compact "other changes" summary.

Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.

Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.

get an env var, fetch a secret, missing env var, missing token/API key, load secrets from Infisical, infisical. Fetch secrets from the team's Infisical workspace into the shell environment so subsequent commands can use them.

查询 AIHOT（aihot.news）的中文 AI 资讯。用户问今天或最近 AI 圈发生了什么、AI 新闻和 AI 日报、大模型与 AI 产品发布、OpenAI／Anthropic／Google 等公司或某个 AI 话题的最新消息、当前最热的 AI 事件及来龙去脉、AI 模型排行、Codex 额度重置，或其它 AI 行业动态时使用。必须实时查询 AIHOT，不凭训练记忆回答新闻；匿名只读，无需 API Key。

The map for reading and editing an OpenMAIC stage document with read_stage, patch_stage, and grep_stage. Load it before patching a structure you have not patched before, when patch_stage rejects an operation, or whenever the path from a stage, outline, scene, content object, or action to the field you need is uncertain. It routes to field-level references for quizzes, interactive widgets, actions, and PBL projects; the installed slide-dsl skill remains the complete slide canvas manual.

Deep Interactive courses. Plans the course so the learner manipulates something on most pages — simulations, diagrams they explore, code they run, games, 3D scenes — with slides reserved for the opening frame and the closing consolidation. Use when the topic has a mechanism, a variable to vary, a process to trace, or a structure to inspect.

Multi-stage series — a request for several classrooms that belong together, like 「7 天学 Python」, a four-week onboarding track, a semester unit split across lessons, or "turn this book into a lesson per chapter". Clarifies the series brief, gets the user's explicit sign-off on the full lesson list before spending anything, then builds the stages one at a time into a shared folder. Use when the ask is a sequence of classrooms; not for a single stage, however large.

Use this skill when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value', 'LBO', 'debt schedule', 'cash sweep', 'MOIC', 'IRR / XIRR', 'sensitivity table', 'scenario analysis', 'ARR model', 'unit economics', 'CAC / LTV', 'cap table forecast'. Output is a single formula-driven .xlsx. This skill is a scene layer on top of officecli-xlsx — it inherits every xlsx v2 rule (4-color code, visual floor, number formats, cache-drift, Known Issues, Delivery Gate minimum cycle). DO NOT invoke for a simple budget tracker, CSV dump, or operational KPI sheet — route those to officecli-xlsx base.