Add new AI models to Kiln's mlmodellist.py and produce a Discord announcement. Use when the user wants to add, integrate, or register a new LLM model (e.g. Claude, GPT, DeepSeek, Gemini, Kimi, Qwen, Grok) into the Kiln model list, mentions adding a model to mlmodellist.py, asks to discover/find new models that are…
Check Kiln's model list for deprecated or sunset models across all providers. Use when the user wants to find deprecated models, check model availability, audit the model list for stale entries, or mentions model deprecation/sunset/end-of-life.
Run the Kiln pre-release smoke test suite plus the standard CI checks (checks.sh), diagnose every prerelease test that broke (and why), and write a clean readable report with recommended actions. Read-only — it never edits code. Use when the user wants to validate a release candidate, run prerelease tests, or asks for…
Use when a workflow consistently revolves around a single chat message or prompt response, especially for quick one-turn interactions, message formatting, or minimal-context chat handling.
Use this skill before any data analysis, transformation, or modeling. Always inspect and validate the data before drawing conclusions or writing transformations.
Use this skill when implementing any endpoint, form handler, CLI tool, or function that accepts external input. Validate and sanitize all untrusted data before processing — never assume input is safe.
Use this skill when writing shell scripts, Python automation, or any unattended batch job. Ensure failures are detected, logged, and handled — never silently ignored.
Add a new step under src/nemotron/steps/ / / — manifest (step.toml), runner glue, configs, and per-step README.md. Use when extending the catalog so /nemotron-customize can route to it.
Reference desk for Nemotron 3 Nano / Llama-Nemotron Nano 3 — architecture, training data, recipes, evaluation, quantization, deployment. Use when the user asks facts about the model rather than building a pipeline.
Use when reviewing a proposed REST or GraphQL API change before merge — checks contract clarity, backwards compatibility, errors, pagination, auth, and naming.
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.
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.
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.
This skill should be used when users want to fine-tune language models or perform reinforcement learning (SFT, DPO, GRPO, ORPO, KTO, SimPO) using the highly optimized Unsloth library. Covers environment setup, LoRA patching, VRAM optimization, vision/multimodal fine-tuning, TTS, embedding training, and…
Query NCBI ClinVar for variant clinical significance. Search by gene/condition/CLNSIG, interpret pathogenicity, use E-utilities or FTP; annotate VCFs. Use project tools in src.tools.database.ncbi.
Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.
Distills a completed user workflow or interaction into a reusable VenusFactory agent skill. Use when the user says "make this a skill", "create a skill from what we just did", "package this workflow" or similar. Adapts the workflow into the VenusFactory tools wiring + SKILL.md pattern. Do not use for creating skills…
Use when the user wants to estimate GPU memory (VRAM) requirements for a training configuration, check if a model will fit on their GPUs, or plan GPU allocation for training.
Guides users through LLM post-training with Training Hub, including installation, algorithm selection (SFT, OSFT, LoRA), hyperparameter tuning, troubleshooting OOM errors, interpreting loss curves, and leveraging backend-specific features. Use when the user is working with traininghub, fine-tuning language models…
Release process, CI/CD workflow rules, sccache/S3 caching strategy, version numbering, and changelog conventions for eullm. Use when working on .github/workflows/.yml, cutting a release, tagging EuLLM-v, editing CHANGELOG.md, or debugging CI cache/build-time issues.