skills/phase-data-preprocess/SKILL.md
Phase guidance for the neuroflow /data-preprocess command. Loaded automatically when /data-preprocess is invoked to orient agent behavior, relevant skills, and workflow hints for the data-preprocess phase.
npx skillsauth add stanislavjiricek/neuroflow phase-data-preprocessInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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The data-preprocess phase filters, cleans, epochs, and quality-checks raw data to produce analysis-ready datasets.
.neuroflow/data/ inventory first — understand the dataset before choosing methodsneuroflow:neuroflow-core — read first; defines the command lifecycle and .neuroflow/ write rulesneuroflow:bids — invoke when loading BIDS-organized data; covers BIDSLayout querying, mne_bids.read_raw_bids(), sidecar metadata fields, and writing preprocessed derivatives back to BIDSoutput_path (scripts/preprocessing/), not inside .neuroflow/preprocess-config.md to .neuroflow/data-preprocess/ with the full parameter set used.neuroflow/reasoning/data-preprocess.json/neuroflow:data-preprocess — runs this workflow as a slash command.
testing
This skill should be used whenever the user mentions BIDS, Brain Imaging Data Structure, BIDS conversion, BIDS validation, BIDS compliance, organizing neuroimaging data, dataset_description.json, participants.tsv, bids-validator, pybids, MNE-BIDS, or asks how to structure EEG/MEG/fMRI/iEEG/PET/DWI data for sharing or preprocessing. Also invoke when the user asks how to name scan files, what sidecar JSON fields are needed, how to set up derivatives/, or how to run fMRIPrep/MRIQC on their dataset. Invoke proactively during /data, /data-preprocess, and /data-analyze phases whenever the dataset structure is relevant to the task at hand.
tools
Phase guidance for the /meeting command. Covers meeting file structure, recurring templates, attendee resolution from profiles, Google Calendar MCP integration, agenda preparation with project context, and action-item-to-task conversion at all three levels (project, flowie, hive).
data-ai
Worker-critic agentic loop protocol — orchestrator coordinates a worker agent and a critic agent across up to 3 revision cycles to produce a vetted output for any phase.
development
Knowledge base skill — Karpathy-style LLM-maintained wiki at three levels (personal/flowie, project, team/hive). Handles ingest, query, lint, schema, and project-tagging workflows. Invoked by /flowie --wiki-* (personal), /wiki (project), /hive --wiki-* (team).