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orq-ai/orq

v2.5.1MIT

Agent skills for building, deploying, evaluating, and monitoring LLM pipelines on the orq.ai platform.

orq-generate-synthetic-dataset

Generate and curate evaluation datasets — structured generation via dimensions-tuples-NL, quick from description, expansion from existing data, plus dataset maintenance through deduplication, rebalancing, and gap-filling. Use when creating eval data, expanding test coverage, or cleaning datasets. Do NOT use when sufficient real production data exists (use orq-analyze-trace-failures instead). Do NOT use for evaluator creation (use orq-build-evaluator).

Read SKILL.md at the source

Pinned to revision 9634e1d956e4, so it is the text this page describes rather than whatever the author pushed since.

Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

  • Bash(curl:*)
  • Read
  • Write
  • Edit
  • Grep
  • Glob
  • WebFetch
  • Task
  • AskUserQuestion
  • mcp__orq-workspace__search_entities
  • mcp__orq-workspace__list_models
  • mcp__orq-workspace__list_datapoints
  • mcp__orq-workspace__get_llm_eval
  • mcp__orq-workspace__get_python_eval
  • mcp__orq-workspace__create_dataset
  • mcp__orq-workspace__create_datapoints
  • mcp__orq-workspace__update_datapoint

Files

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