Individual skill
dataset-curation
Prepare, format, and validate datasets for supervised fine-tuning and preference training. Use when converting raw data into training format, applying chat templates, configuring sequence packing, generating synthetic training data, or writing a dataset card before a run.
plugins/llm-finetuning/skills/dataset-curation/SKILL.md
Source commit 4bde3168b43c0655c4d00ea2726e631719908a6d
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- Yes
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- Yes
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
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Repository context
- Repository stars (not skill ratings)
- 42,378
- Repository last updated
- Nov 9, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- anthropic Repository topic
- agent-skills Repository topic
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- mcp Repository topic
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SKILL.mdcore · 7,991 bytesSKILL.mdcore · 7,991 bytesSKILL.mdcore · 7,991 bytesSKILL.mdcore · 7,991 bytesreferences/formats-and-templates.mddoc · 6,509 bytesreferences/synthetic-data.mddoc · 12,834 bytes
Read excerpt
# Dataset Curation
This skill assumes `finetuning-method-selection`
already routed here — the next step is preparing
data, not choosing a method. What follows: format
selection by target method, the template/packing
mechanics behind the most common silent training
failures, rules for mixing in synthetic data
without collapse, and the dataset card that closes
out Phase 2 before a run starts.
**Input:** raw examples (demonstrations, preference
judgments, or task prompts) plus a routing decision
from `finetuning-method-selection`.