LLM Mart Basic
@llm-mart · Joined Jun 2026
Cross-cutting reference manager for medical manuscripts. Single entry point for citation-key validation, journal-CSL pandoc rendering, manuscript ↔ DOCX cross-reference QC, marker conversion (``[N]`` ↔ ``[@key]``), and native Zotero CWYW field-code injection. Replaces the inline
Turn a folder of research PDFs into an Obsidian knowledge vault — consistently formatted literature notes with frontmatter, PDF embed links, and cross-referenced atomic concept notes. Use whenever the user wants PDFs converted to Obsidian notes, a batch of papers summarized into
Literature search and citation management for medical research. Searches PubMed, Semantic Scholar, and bioRxiv/medRxiv with verified citations. Anti-hallucination — every reference verified via API before inclusion. Generates BibTeX entries.
Audit-only verification of manuscript references against PubMed and CrossRef. Detects fabricated or mismatched citations and writes qc/reference_audit.json. Does not modify references/ or refs.bib.
Interactive sample size calculator for medical research. Decision-tree guided test selection, reproducible R/Python code, effect size interpretation, and IRB-ready justification text. Supports diagnostic accuracy, agreement, proportions, continuous outcomes, survival, ANOVA, logi
Interactive data profiling and cleaning assistant for medical research. Three-stage workflow (profile, flag, code-generate) with user approval gates at each step. Handles missing values, outliers, duplicates, and type mismatches in CSV/Excel clinical data. Does NOT auto-clean — a
Literature-grounded variable operationalization for observational research. Turns a data dictionary + research question into a citation-backed table of exposure/outcome/covariate definitions, cutoffs, and DB variable mappings. Prevents ad-hoc phenotype definitions that invite rev
De-identify clinical research data before LLM-assisted analysis. Standalone Python CLI detects PHI via regex + heuristics with 10 country locale packs (kr, us, jp, cn, de, uk, fr, ca, au, in). Interactive terminal review. No LLM touches raw data — the script runs locally without
Design and validity review for studies that benchmark one or more AI systems against a human-expert panel as the reference. Covers the evaluation question and arm definition, decoupled multi-dimensional rubrics with anchors, planted calibration probes, reviewer-panel construction
Study design and validity review for radiology and medical AI research. Identifies analysis unit, cohort logic, leakage risks, comparator design, validation strategy, and reporting guideline fit before drafting or submission.
Generate a citable data dictionary / codebook from a tabular dataset (CSV/TSV/Excel/Parquet/Stata/SAS). Profiles every variable — role, type, units placeholder, level frequencies, range/quantiles, missingness — and emits codebook.md + codebook.json. Flags coded variables whose le
Dataset version control for research reproducibility. Builds a deterministic content-hash manifest of a dataset (file SHA-256 + tabular schema + per-column value hashes), verifies a later copy against it to detect drift (schema change, row-count change, value changes), and diffs
Choose a model architecture for a medical-imaging research question before scaffolding. Maps the task (classification, segmentation, detection, transfer), modality and dimensionality, labelled-data scale, and class imbalance to a shortlist of architectures, each grounded in its s
Produce or audit the interpretability/explainability analysis of a medical-imaging model — Grad-CAM / Grad-CAM++ / attention-rollout / saliency / integrated-gradients — so it clears the rigor bar a reviewer expects: mandatory Adebayo sanity checks (model- and data-randomisation),
Design or audit a model-agnostic evaluation harness for an LLM or multimodal LLM on a clinical task (radiology report generation, visual question answering, clinical text extraction/classification) — the adjudicated reference standard, clinical-efficacy metrics (RadGraph-F1 / Che
Generate the documentation an engineer-built medical-imaging model must carry — a Model Card (Mitchell et al. 2019), a Datasheet for its dataset (Gebru et al. 2021), and a METRIC-informed data-quality pass — filled from user-supplied facts, then verify every required section is p
Compute and report task-correct held-out metrics for a trained medical-imaging model — segmentation (Dice plus a boundary metric such as HD95 or NSD, per structure), classification (AUROC plus AUPRC and sensitivity/specificity with bootstrap CIs at the deployment prevalence), det
Generate a reproducible, runnable PyTorch training repo for a medical-imaging task — segmentation, classification, detection, image-to-image synthesis, self-supervised pretraining, or fine-tuning a pretrained backbone (transfer learning) — the missing middle link between choosing
Vet the concrete third-party model a study will be built on — this repository, this revision, this checkpoint — not the architecture family. Records a model dossier (source and version pin, licence and the file it was read from, intended use, pretrained-weight provenance, model t
Design or audit the clinical-validation study for an engineer-built medical-imaging model (segmentation, classification, or detection) before the validation report or manuscript is written. Covers patient-level split disjointness and the data-leakage taxonomy, tuning-on-test, int
/chore
Chore
This is the lane for changes with no behavior to test-drive — prose edits, a version bump on an
/cleanup
Cleanup
Use this after a pull request has merged but your local checkout is still on the topic branch.
/commands
Commands
Prints the public command catalog straight from `COMMANDS.md` — the plugin's own single source
/commit
Commit
This is the single entry point for turning staged work into a commit — nothing in codeArbiter
/conflict
Conflict
The protocol for a rule conflict — not a skill route, an orchestrator-level halt. When two sources
/context-check
Context check
An optional, on-demand drift audit for the bypass case: a merge, a direct push, or a manual edit
/create-context
Create context
This is the populator for a project that already has code to read. Instead of interviewing you about
/debug
Debug
`/ca:debug` investigates an unexplained symptom and returns a cited diagnosis or a bounded
/decompose
Decompose
This is the populator for a project that has no code yet to read. Rather than guessing at
/doctor
Doctor
Proves the install is actually enforcing, rather than just present. codeArbiter's worst failure
/feature
Feature
This is the standard entry point for new work with a human in the loop at every step. A short
/fix
Fix
This is the entry point for an authorized repair of a confirmed code defect. Give the observed
/init
Init
This is how a repository opts into codeArbiter for the first time. It writes the root-level state
/metrics
Metrics
A bare-numbers governance glance — three metrics, each with a trend arrow against the prior
/override
Override
The sanctioned, logged escape hatch. A routine gate — a lint rule, a style check, a non-security
/pr
Pr
Explicit PR entry and a direct request to open a PR use the same branch-finishing owner.
/preview
Preview
A zero-onboarding, read-only dry-run of the reviewer fleet against whatever is currently
/prune
Prune
This is a Feature Forge preview command — the after-each-turn service ships **off** by default and
/reconcile
Reconcile
Compares architectural records with the scaffold and prior decisions using SMARTS.
/refactor
Refactor
This is the lane for moving or reshaping code without changing what it does — a rename, an extract,
Make any song you can imagine
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