Create and validate lab output YAML files with standardized frontmatter.
npx skills add https://github.com/hammer/labs --skill add-output
Please help me install this Agent Skill. Skill: add-output Source: https://github.com/hammer/labs/tree/main/.agents/skills/add-output Command: npx skills add https://github.com/hammer/labs --skill add-output
Add new research outputs to a lab's data directory in a consistent, auditable format.
Create a new output YAML under data/outputs with the required frontmatter and descriptive body.
High-intent search queries and answers about installing and using this skill.
Adding new lab outputs to YAML requires standardized frontmatter with name and description fields, plus a descriptive body. This ensures consistent metadata and traceability for models, papers, datasets, and libraries.
Standard YAML frontmatter for research data management requires name and description fields to validate an entry. Optional component metadata can also be included for scripts, references, and assets to support lifecycle updates.
Validating required fields in a YAML output entry involves applying guardrails to ensure proper frontmatter presence. You must confirm that both name and description fields are populated before including the content body.
You can include optional component metadata for scripts, references, and assets in your YAML outputs. This supports lifecycle management for future updates, variants, and linking to related outputs in your lab catalog.
Automating the addition of models and datasets to a lab directory uses a guided workflow to create entries under data/outputs. This enforces standardized YAML frontmatter and descriptive body for auditable data management.
No specific dependencies are required to manage YAML frontmatter for lab outputs. The validation process operates independently to enforce required fields and proper frontmatter presence for your data entries.
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