Machine learning

Triage a degraded or suspect service end to end: read SLO status and burn rate, check active alerting rules and ML anomalies, measure throughput, latency, and…

Les LLM écrivent du juridique qui ressemble à du juridique sans en être.

Use Netlify AI Gateway to call OpenAI, Anthropic Claude, Google Gemini, TypeSafe (Jev), or OpenRouter-hosted models (xAI/DeepSeek/Meta/Mistral/Qwen) from…

Suede AI eval design and coverage audit: AI-SPEC, failure-mode rubric with severity scoring, concrete pass/fail eval cases, coverage and infrastructure…

Suede AI code review and A-F ship grade for a diff, PR, branch, or commit range: findings ranked P0-P3 with file:line evidence and a fix path, an A-F grade…

Suede AI competitive-intelligence discipline: evidence-backed profiles of positioning, pricing, messaging, product, proof, reviews, organic search footprint…

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet…

Create a handoff brief for another LLM to implement.

This skill provides reference guidance for citation verification in academic writing.

Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub

Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure.

Opinionated Bayesian modeling workflow with PyMC and ArviZ.

Production-grade Bayesian causal inference with PyMC, CausalPy, and DoWhy.

The protocol behind every investigation skill.

Run competitive research like an intelligence agency: eight collection disciplines (OSINT to MASINT), signal-to-inference chains, and fusion.

Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax…

Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold…

Apple HIG guidance for Apple technology integrations: Siri, Apple Pay, HealthKit, HomeKit, ARKit, machine learning, generative AI, iCloud, Sign in with Apple…

Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or…

Generates BYO custom safety policies for NVIDIA Nemotron content-safety guardrails — Nemotron-Content-Safety-Reasoning-4B (text) and multimodal…

Migrate an application with hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation in five stages: audit the code, wrap the call, move the…

Reference architecture for building a Generative AI (生成AI) workload for financial institutions on AWS, based on the closed-network edition of the AWS Samples…

软件开发工程师与数据科学家在构建RAG系统时，当需处理PDF/Word/Excel等多格式复杂文档，用此技能可自动触发三级解析降级，一键输出高置信度结构化Markdown与元数据，免去繁琐清洗，直接夯实企业知识库数据底座！

将 PDF/PPT/Excel/Word 等多格式文档解析为结构化 Markdown，并输出元数据与解析置信度，作为 RAG 与四色卡片的数据底座。