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zorost/AI-Engineering-Lab

SkillsMP a collecté 14 skills depuis zorost/AI-Engineering-Lab. Ouvrez un skill pour examiner sa source et ses détails.

Dernière activité source enregistrée
Catalogue SkillsMP mis à jour
skills collectés
14
Étoiles GitHub
204
Forks GitHub
170

Skills dans ce dépôt

classification en attente

Affichage de 14 skills collectés sur 14.

métier
non classé
description

Wrap an agent loop with step limits, cost caps, human approval gates, and a full trace. Use whenever building or reviewing any tool-calling agent before it touches real systems.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Move an agent from laptop demo to operated system, tracing, cost dashboard, scheduled runs, alerting, and rollback. Use when an agent is about to run unattended or serve real users.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Review AI-generated code or text before accepting it, spec diff, verifier run, secret scan, and the AI smell list. Use before merging any agent-produced change.

Langue du texte source : anglais

mis à jour
métier
non classé
description

The pre-deployment gate for managed AI platforms (Azure AI Foundry, Google Vertex AI, AWS Bedrock), evals packed, budget set, guardrails on, owner named. Use before any cloud deployment.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Audit the seven claimants on an LLM call's context window, set a working ceiling, and cut in the right order. Use when prompts grow, agents drift, or token bills surprise you.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Read 50 real failures by hand, cluster them into classes, fix the largest class, and extend the golden set. Use whenever an AI system's score stalls or its failures are 'mysterious'.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Build the golden set and the automated scorer before touching the prompt, model, or pipeline. Use whenever an AI output's quality will need to be measured, extraction, RAG, agents, classification.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Decide whether fine-tuning is justified versus prompting or RAG, and gate the training dataset before any LoRA/SFT/DPO run. Use when someone says 'let's fine-tune'.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Compute the VRAM/RAM budget and pick a model size and quantization before downloading anything. Use when choosing local models, planning GPU hardware, or hitting out-of-memory errors.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Design and build an MCP server whose tools are narrow, typed, idempotent, and documented. Use when exposing any system to AI agents via the Model Context Protocol.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Improve a prompt as a versioned artifact with a score, change one variable at a time, keep the diff, read the failures. Use whenever editing prompts that must stay measurably good.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Verify a RAG pipeline end-to-end, chunking, embeddings, retrieval quality, reranking, grounded answers with citations. Use when building or debugging retrieval-augmented generation.

Langue du texte source : anglais

mis à jour
métier
non classé
description

Write the one-page spec for an AI feature, user, golden set, metric, gate, refused tradeoffs, before any code or prompt work. Use when starting any AI feature, agent, or pipeline.

Langue du texte source : anglais

mis à jour
métier
non classé
description

How to pick, run, and amend Zorost agent skills. Use at the start of any task when this catalog is installed, or when a skill seems not to fit.

Langue du texte source : anglais

mis à jour
Affichage de 14 skills collectés sur 14.