.claude/skills/hook-updater/SKILL.md
Research-backed hook refresh workflow for updating existing hooks with TDD checkpoints and settings.json registration validation.
npx skillsauth add oimiragieo/agent-studio hook-updaterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill to refresh an existing hook safely: research current best practices, compare against current implementation, generate a TDD patch backlog, apply updates, and verify ecosystem integration including settings.json registration.
Never update a hook blindly. Every refresh must be evidence-backed, TDD-gated, and integration-validated.
.claude/hooks/CLAUDE.md for hook conventions.claude/rules/hooks.md for hook rulesSkill({ skill: 'research-synthesis' }) if external research neededEdit tool — never rewrite the entire file.claude/settings.json for correct eventspnpm lint:fix && pnpm formatMemoryRecord if significanttools
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
tools
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
data-ai
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
development
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.