🎯Skills1
🔌Plugins7
Project lifecycle toolkit: initialization, cross-agent user-instruction setup, tiered model routing, epic/sprint workflow, PR review, onboarding, planning, debugging, engineering loop, agent fan-out, CI/CD, Docker, security, and document processing
Neuroscience data standards and experiment design: BIDS conversion/validation, HED annotation, and PsychoPy experiment scaffolding
Academic manuscript toolkit: literature review (multi-phase citation-traceable + single-pass thematic), peer review, writing, journal-specific formatting for submission, and humanizer pass to remove AI-writing tells
Grant proposal toolkit: NIH/NSF writing with mechanism-specific templates, structured review with scoring criteria, and figure quality assurance
Presentation builder: create interactive Reveal.js presentations from JSON with Mermaid diagrams, LaTeX math, code highlighting, and animated reveals
Academic literature search, citation management, PDF retrieval, identifier conversion, and BibTeX export
Publication-quality figures plugin. Seven skills + one QA agent: scientific-figure (svgutils composer with font validation; Inkscape/cairosvg export); transparent-icons (flat scientific icons via Codex CLI or OpenAI Images API); svg-figure (schematic authoring with consistency guidelines); svg-primitives (mm-precise SVG builder in Python: auto-fit boxes, tangent-correct arrows on straight/cubic/orthogonal routes, multi-waypoint paths, brackets/annotations/groups, layered z-order); ai-full-figure (AI substrate + programmatic label/arrow/scale-bar overlay); plot-styling (library decision tree + SciencePlots recipes for Nature/IEEE/Science/Cell/PNAS/APS); figure-qa agent (type-dispatching QA across SVG/raster/plot-script with strict programmatic-vs-VLM separation).