20 NVIDIA NeMo Data Designer alternatives
NVIDIA NeMo Data Designer: NVIDIA's official skill for building synthetic datasets with NeMo Data Designer — describe the data you want and the agent writes a declarative generation pipeline, column by column. 20 agent skills do similar work, most sharing Evaluation, Python and Data, ranked by how much they have in common with NVIDIA NeMo Data Designer.
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by NVIDIA
Diagnoses wrong gradients in differentiable NVIDIA Warp programs by measuring first — comparing autodiff against finite differences on a shrunk reproduction before proposing any fix.
Also: Evaluation, NVIDIA, Python
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by Hugging Face
Read-only recipes for the Hugging Face Dataset Viewer API — resolve splits, paginate rows, run text search and row filters, and pull parquet URLs and column statistics.
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by NVIDIA
Trains, distils, quantises, evaluates, exports and runs inference for RT-DETR real-time object detection in NVIDIA TAO, routing training through AutoML hyperparameter search by default.
Also: Fine-tuning, NVIDIA
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by Hugging Face
Train bi-encoders, rerankers, SPLADE sparse encoders and ColBERT multi-vector models with the loss, evaluator and template each type actually needs.
Also: Fine-tuning, Python
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by Hugging Face
Fine-tune object detection, image classification and SAM/SAM2 segmentation models on Hugging Face Jobs cloud GPUs, with dataset validation before you spend GPU minutes.
Also: Fine-tuning, Python
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by Hugging Face
Fine-tune language and vision models with TRL or Unsloth — supervised, preference, and reinforcement training methods.
Also: Fine-tuning, Python
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by Agnost AI
Walks a coding agent through wiring Agnost AI conversation analytics into a Python or TypeScript app — inspecting existing OpenTelemetry first and only adding an SDK when the traces are not usable.
Also: Evaluation, Python
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by Anthropic
Anthropic's guide for building high-quality MCP servers end to end — research, tool design, implementation in TypeScript or Python, testing, and a 10-question evaluation suite.
Also: Evaluation, Python
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by NVIDIA
GPU-accelerated Mean-CVaR and Mean-Variance portfolio construction with NVIDIA cuOpt: scenario generation, variance-capped SOCP allocations, efficient frontiers, backtests and rebalancing.
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by NVIDIA
Turns a plain-language weather question into a working Earth2Studio inference script — picks the AI forecast model, a compatible data source, an IO backend, and the step count.
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by DuckDB
Run SQL — or a plain-English question — against DuckDB databases, CSV, Parquet, JSON and Excel files, with schema inspection and error recovery built in.
Also: Data
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by Senzing
Drives the Senzing MCP server through the real entity-resolution jobs: map a messy CSV to Senzing's format, scaffold SDK code in five languages, decode error codes, migrate V3 to V4.
Also: Data
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by Tinybird
Tinybird's own datafile and SQL rules for coding agents — datasources, pipes, endpoints, materialized views, deduplication and query optimisation.
Also: Data
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by Google
Google's official BigQuery skill — datasets, tables, jobs and SQL from the bq CLI, plus the reference set for IAM, Terraform, change history and continuous queries.
Also: Data
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by Tencent
Tencent's skill-evolution harness: it rewrites a whole skill folder — SKILL.md, scripts and references together — and lands every decision as a real Git issue, PR and wiki entry you can review.
Also: Evaluation
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by AMD
AMD's official skill for benchmarking vLLM/SGLang inference and driving GPU kernel optimization with Magpie and TraceLens trace analysis.
Also: Evaluation
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by SerpApi
A protocol for measuring whether agents can discover and use your tool without being told about it — WITH/WITHOUT trials, binary scoring, and lift as the only metric. The subject under test is your docs, not the model.
Also: Evaluation
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by Anthropic
Anthropic's official skill that appends 2-3 targeted follow-up questions to a substantive answer, prompting the reader to check facts, probe assumptions and spot missing context.
Also: Evaluation
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by Addy Osmani
Sends every non-trivial decision to a fresh-context adversarial reviewer before it stands — for production, security-sensitive or irreversible work.
Also: Evaluation
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by Anthropic
Create, edit, and optimize Agent Skills — scaffold new skills, refine existing ones, run evals, and tune descriptions for reliable triggering.
Also: Evaluation
