skills/phase-data-analyze/SKILL.md
Phase guidance for the neuroflow /data-analyze command. Loaded automatically when /data-analyze is invoked to orient agent behavior, relevant skills, and workflow hints for the data-analyze phase.
npx skillsauth add stanislavjiricek/neuroflow phase-data-analyzeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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The data-analyze phase applies statistical and computational methods to preprocessed data to test the research hypothesis.
.neuroflow/ideation/ for the research question and .neuroflow/data-preprocess/ for the preprocessing report before choosing methodsanalysis-plan.md first; do not write analysis code before the plan is acceptedneuroflow:neuroflow-core — read first; defines the command lifecycle and .neuroflow/ write rulesneuroflow:bids — invoke when querying dataset structure with pybids, loading subject/session/task metadata from participants.tsv and events.tsv, or writing analysis outputs to BIDS derivativesoutput_path (scripts/analysis/, results/, figures/), not inside .neuroflow/analysis-plan.md to .neuroflow/data-analyze/ before running any scripts.neuroflow/reasoning/data-analyze.json/neuroflow:data-analyze — 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).