executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
pipelines-and-methodsPlan and implement FlashRAG end-to-end RAG pipelines, quick-start demos, method reproductions, active/reasoning/branching/multimodal pipelines, multi-turn prompts, and experiment-runner dry-runs without executing large models by default.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when the task is about choosing or wiring FlashRAG pipelines, adapting quick-start demos, reproducing supported methods, planning multi-turn or multimodal workflows, or dry-checking an experiment configuration before any large model/index execution.
SequentialPipeline or naive_run; see pipeline API and quick-start/multi-turn.python skills/flashrag/sub-skills/pipelines-and-methods/scripts/validate_pipeline_config.py --config CONFIG.yaml --method METHOD --dry-run-plan.test_sample_num, small retrieval_topk, short generation_params, and do_eval=False for smoke tests.