datagen-reduce-dataset-snapshots

Reduce Daytona snapshot counts by grouping Dockerfiles into shared environments.

276|37|Updated Dec 5, 2025
One-click install
npx skills add https://github.com/open-thoughts/OpenThoughts-Agent --skill datagen-reduce-dataset-snapshots
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: datagen-reduce-dataset-snapshots
Source: https://github.com/open-thoughts/OpenThoughts-Agent/tree/main/.claude/skills/datagen-reduce-dataset-snapshots
Command: npx skills add https://github.com/open-thoughts/OpenThoughts-Agent --skill datagen-reduce-dataset-snapshots

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Reduce Daytona's unique-environment snapshot counts for Harbor datasets by adjusting patcher environment-build logic to group Dockerfiles and reuse environments where possible.

Core Features & Use Cases

  • Group per-task Dockerfiles into shared environment images to dramatically cut snapshots.
  • Diagnose env-hash driver issues, regenerate + upload, and re-count with a two-tier quality gate (infra smoke + oracle) to validate reductions.
  • Real-world example: SweGym dataset reduction from 906 to 5 snapshots demonstrates the payoff of grouping.

Quick Start

Execute the patcher to group Dockerfiles by shared environments and re-count snapshots locally to confirm the cap is under 10.

Frequently Asked Questions about datagen-reduce-dataset-snapshots

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce Docker environment snapshots in Daytona datasets?

To reduce unique-environment snapshots in Daytona, group per-task Dockerfiles into shared environment images by adjusting patcher environment-build logic to reuse environments where possible.

What causes SnapshotCapExceeded errors in Harbor task datasets?

SnapshotCapExceeded errors occur when Harbor task datasets generate too many unique environments. Diagnosing the env-hash driver and grouping Dockerfiles before regenerating snapshots addresses this cap.

How do I validate dataset quality after reducing snapshots?

Validate snapshot reductions using a two-tier quality gate that runs an infrastructure smoke test followed by oracle validation to ensure the grouping did not hurt dataset quality.

Can I run snapshot reduction locally on Mac with Daytona?

Yes, the snapshot reduction workflow runs deterministically on Mac plus Daytona, requiring you to document thresholds, regenerations, and oracle validation locally to confirm compliance.

How many snapshots can I cut by grouping Dockerfiles?

Grouping Dockerfiles can dramatically cut snapshots; a real-world SweGym dataset example reduced unique environments from 906 snapshots down to just 5.

What is the best way to diagnose env-hash driver issues for dataset snapshots?

Diagnose env-hash driver issues by adjusting the patcher environment-build logic to group Dockerfiles, then regenerate, upload, and re-count snapshots locally to confirm the cap is under 10.