skills/phase-tool-build/SKILL.md
Phase guidance for the neuroflow /tool-build command. Loaded automatically when /tool-build is invoked to orient agent behavior, relevant skills, and workflow hints for the tool-build phase.
npx skillsauth add stanislavjiricek/neuroflow phase-tool-buildInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
The tool-build phase designs and implements lab tools or software pipelines — real-time systems, data acquisition, LSL integrations, or custom analysis pipelines.
tool-spec.md first; get confirmation before implementation beginsneuroflow:neuroflow-core — read first; defines the command lifecycle and .neuroflow/ write rulesneuroflow:pupil-labs-neon-realtime — if the tool involves Pupil Labs Neon hardware, use this skill for device discovery, multi-threaded streaming architecture, and real-time data collectionoutput_path (tools/), not inside .neuroflow/tool-spec.md to .neuroflow/tool-build/ before writing any implementation.neuroflow/reasoning/tool-build.json/neuroflow:tool-build — 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).