Research

Papers and tutorials on KAN learnable activation networks

Run NLP and CV model inference via Hugging Face free-tier API

Search and discover ML models, datasets, and Spaces on Hugging Face

Conference papers on graph neural networks and graph learning

Search PubMed and bioRxiv, summarise papers with LLM, build citation graphs, and generate literature review sections.

Medication photo to personalised PGx dosage card via Claude vision — snap a pill, get genotype-informed guidance

Autonomous deep-research loop: iterative investigation, externalized state, convergence detection, fresh context per pass.

Monitors running spatial experiments. Checks output files, log files, and process status. Categorizes results as OK, STALLED, FAILED, or COMPLETE. Fires alerts by appending to output/PROJ_NOTES.md. Run every 15 minutes during Stage 3 of research-pipeline.

Validates a manuscript against target journal requirements before submission. Checks word count, section structure, figure/table count, reference format, and geo-specific reporting standards. Writes a PASS/FAIL checklist report to output/reports/.

Guideline-driven spatial analysis skill. Given a research question and data context, provides decision frameworks for selecting appropriate spatial methods, diagnostics, and interpretation strategies. Adapts to available data, spatial units, and analytical objectives — Claude Code determines the optimal workflow. Use when user says "spatial analysis", "analyze spatial data", "run spatial regression", "check for clustering", "map this", or needs to go from a research question to a complete spa...

Full paper writing pipeline. Orchestrates paper-plan → paper-figure-generate → paper-draft → paper-review-loop → paper-covert to go from upstream research artifacts to a polished, submission-ready manuscript package (Markdown → LaTeX → PDF + DOCX). Use when user says \"write paper pipeline\", \"paper writing\", or wants the complete paper generation workflow.

Reviews the manuscript produced by `paper-draft` (in `output/manuscript/`) as a demanding IJGIS / ISPRS JPRS reviewer-editor, cross-checks it against `output/PAPER_PLAN.md` and its evidence artifacts, then revises it into a stronger draft. Produces a reviewed manuscript, a revised manuscript, a structured review report, a prioritized issue log, a revision log, claim-risk notes, journal-fit notes, and next-loop priorities. Supports full, section-scoped, and mode-scoped review (structural / arg...

Produces a detailed, venue-aware paper outline from all available upstream artifacts (RESEARCH_PLAN, lit review, idea report, refined proposal, experiment plan/results, narrative report). Creates section-by-section plan with word budgets, claim-evidence matrix, figure/table plan, and citation scaffolding. Uses journal templates from templates/ for venue-specific formatting.

Transforms output/PAPER_PLAN.md into a journal-quality Markdown manuscript draft for GIScience, GeoAI, spatial data science, and remote sensing venues (IJGIS, ISPRS JPRS, RSE, TGIS, AAG Annals). Consults referenced literature, experiment, figure, and claim artifacts; supports full drafts, partial drafts, and skeleton drafts depending on readiness. Never fabricates results, metrics, or citations — produces a claim-to-evidence map and coverage-gap report alongside the manuscript.

Converts the final Markdown manuscript from `paper-draft` / `paper-review-loop` into a submission package for the target venue — modular LaTeX (one file per section), compiled PDF, and Word `.docx`. Venue is read from `output/PAPER_PLAN.md` (or argument) and routed through a small YAML profile. Does not rewrite prose, score, or invent citations.

Validates that a research idea is genuinely novel vs. existing literature. Searches ArXiv, Semantic Scholar, and WebSearch for near-duplicate work. Produces a novelty verdict and evidence. Run on each idea from idea-discovery-pipeline before investing in experiments.

Retrieves papers from local folder or ArXiv and Semantic Scholar using domain-aware keyword expansion, builds synthesis matrix, identifies gaps. Calls tools/arxiv_fetch.py and tools/semantic_scholar_fetch.py. Writes to output/paper-cache/ and output/LIT_REVIEW_REPORT.md.

Get a deep critical review of research idea from GPT via Codex MCP. Use when user says "review my idea", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.

The full pipeline for idea generation. It generates 8-12 novel research ideas from literature gaps and evaluates each on novelty, feasibility, and domain fit. Orchestrates lit-review → generate-idea → novelty-check → idea-review → experiment-design-pipeline to go from a broad research direction to a validated, pilot-tested idea with a refined proposal and experiment plan. Produces output/IDEA_REPORT.md plus refinement and experiment artifacts.

Consolidates literature review, idea discovery, refined proposal, experiment plan, experiment results, and automated review into a single NARRATIVE_REPORT.md that is rich enough to drive the downstream paper-writing-pipeline (paper-plan → paper-figure-generate → paper-draft → paper-review-loop → paper-convert).

Generate and rank research ideas given a broad direction. Use when user input "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.

Turn a refined GIScience / remote sensing / spatial data science proposal into a detailed, claim-driven experiment roadmap. Use after `refine-research`, or when the user asks for a detailed experiment plan, ablation matrix, spatial evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and contribution.

Discover, evaluate, and download publicly available datasets from the internet. Infers data needs from a research question or task, selects authoritative sources, downloads reproducibly, validates file integrity, and documents provenance. Pauses for user input when authentication, API keys, or major tradeoffs require a decision. Use when user says "download data", "get data", "find a dataset", "I need boundary files", "download census data", or needs any external dataset for analysis.

Orchestrates a comprehensive research effort across multiple design systems/component libraries