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
cli-and-operationsGuides agents using Axolotl CLI commands, launcher flags, agent-docs, config-schema, install checks, merge LoRA, inference, vLLM serving, evaluation, fetch, and quantize operations.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when the task is about an axolotl command, CLI flags, command construction, agent-docs, config-schema, install checks, fetching examples, preprocessing runs, training launchers, inference, evaluation, LoRA merge, sharded FSDP merge, vLLM serving, cloud invocation, or post-training quantization.
agent-docs/config-schema usage.axolotl on PATH, and axolotl --help without starting training or loading a model.command not found, import errors, or a failing help/schema command.axolotl agent-docs --list, axolotl agent-docs <topic>, and axolotl config-schema --field <name> for installed-package truth before guessing config keys.-- separator, and launcher-specific args after --.axolotl preprocess config.yml --debug before long training when dataset formatting, chat_template, labels, packing, or tokenization is uncertain.This sub-skill owns Axolotl CLI entry points, safe command construction, install/entry-point checks, operational sequencing, fetch, agent-docs, config-schema, cloud flags, inference/evaluation/merge/vLLM/quantize command routes, and common CLI failures. Route detailed config fields and dataset shapes to data-and-configs, method recipes to SFT/pretraining or RL/preference sub-skills, model/adapters to model-loading-and-adapters, and distributed/performance backend tuning to distributed-and-performance.