LLM Mart Basic
@llm-mart · Joined Jun 2026
Apply the scGPT single-cell foundation model (Cui 2024) to annotate and embed cells — zero-shot and fine-tuned cell-type annotation, gene/cell embeddings, batch integration, and gene-regulatory / perturbation inference from AnnData. Use when annotating cell types with a pretraine
Run RNA velocity analysis with scVelo on single-cell RNA-seq data — estimate cell-state transitions from spliced/unspliced mRNA dynamics, infer trajectory direction, compute latent time, and identify driver genes. Use when adding directionality to trajectories or studying differe
Train deep generative models for single-cell omics with scvi-tools — probabilistic batch correction and integration (scVI), reference-mapping transfer learning (scArches), differential expression with uncertainty, and multimodal models (totalVI for CITE-seq, MultiVI for multiome)
Analyzes spatial transcriptomics with squidpy (1.8.x) on AnnData and SpatialData objects, routing platforms correctly: Visium spots use spatial_neighbors(coord_type='grid') and pair with deconvolution, while Xenium/MERFISH single-cell data use coord_type='generic'/Delaunay neighb
Store and query genomic variant data at scale with TileDB-VCF — ingest VCF/BCF into compressed TileDB arrays, add samples incrementally, run fast parallel region/sample queries, and export back to VCF. Use when managing population-genomics variant datasets that are too large for
Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel
Runs molecular machine learning with DeepChem — diverse featurizers, pre-built MoleculeNet benchmark datasets, and pre-trained models (ChemBERTa, GROVER) for property prediction (ADMET, toxicity, solubility) via traditional ML or graph neural networks. Use when running end-to-end
Predicts protein-ligand binding poses with DiffDock diffusion-based molecular docking from PDB structures and SMILES, producing pose confidence scores for virtual screening and structure-based drug design. Use when docking ligands into a protein, generating binding poses, or scre
Computes mass-spectral similarity and identifies compounds for metabolomics with matchms — comparing mass spectra, scoring similarity (cosine, modified cosine), and searching spectral libraries to annotate unknowns. Use when matching MS/MS spectra, identifying metabolites, or lib
Applies medicinal-chemistry filters with the medchem library — drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, and molecular complexity metrics for compound prioritization and library cleanup. Use when filtering or triaging a compound library, flagging PA
Featurizes molecules for machine learning with molfeat — ECFP/MACCS/MAP4 fingerprints, RDKit and Mordred physicochemical descriptors, pharmacophore and shape descriptors, and pretrained embeddings (ChemBERTa, ChemGPT, CheMeleon) exposed as scikit-learn transformers that convert S
Queries the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biomedical relationships across genes, drugs, diseases, phenotypes, pathways, and biological processes. Use when exploring drug-disease or gene-disease links, building disease-centric knowledge subgraphs, or
Loads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction. Use when fetching a standardized benchmark datas
Provides the RDKit cheminformatics toolkit for low-level, fine-grained molecular primitives — SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure/SMARTS search, 2D/3D coordinate generation, similarity, and reaction handling. Use when custom sanitization,
Drives the Rowan cloud quantum-chemistry platform via its Python API for computational chemistry — pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2), wi
Builds PyTorch-native graph neural networks with TorchDrug for molecules and proteins, exposing custom GNN architectures, task/dataset abstractions, molecular generation, retrosynthesis planning, and knowledge-graph reasoning. Use when a project specifically needs TorchDrug's dat
Generates professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings — biomarker-stratified patient cohort analyses with outcomes and evidence-based treatment recommendation reports with decision algorithms, supporting GRADE evidence
Prepares ISO 13485 certification documentation for medical device Quality Management Systems (QMS) — gap analysis of existing documentation, Quality Manuals, required procedures and work instructions, and Medical Device Files. Use for ISO 13485 QMS documentation, conducting a doc
Processes and analyzes physiological biosignals with the NeuroKit2 Python toolkit — ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements, or when
Reads, writes, and manipulates DICOM (Digital Imaging and Communications in Medicine) medical imaging files with the pydicom Python library. Use when reading/writing/modifying DICOM data, extracting pixel data from CT, MRI, X-ray, or ultrasound images, anonymizing DICOM files, wo
Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.
A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.
A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.
None of the safety came from the model. It came from six boring habits.
Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.
Six hours in, one step left, everything green, and the incident that didn't happen
CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.
Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it
An API request routing a model's tool call through an approval gate to a remote MCP server
31 config keys, two audits, and why the first one was wrong in both directions
The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.
Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.
Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.
"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks
stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.
The most important rule wasn't about what I could change. It was about what I was allowed to display.
Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
/story-cover
Story cover
网文封面生成。分析书名题材,生成专业封面图。
/story-deslop
Story deslop
网文去AI味。检测并清除文本中的AI写作痕迹,让文字回归自然。
/story-import
Story import
逆向导入已有小说。将已写好的小说反向解析为标准项目目录结构。
/story-long-analyze
Story long analyze
长篇网文拆文。深度拆解爆款长篇小说的黄金三章、人设、爽点、节奏。
/story-long-scan
Story long scan
长篇网文扫榜。分析起点、番茄、晋江等平台排行数据,提炼市场趋势。
/story-long-write
Story long write
长篇网文写作。从大纲到正文,辅助长篇网络小说的创作。
/story-review
Story review
多视角对抗式审查。使用多个 Agent 对作品进行多维度审稿。
/story-setup
Story setup
网文写作环境部署与检查。部署 hooks、rules、agents、项目指令等基础设施;传入 check 只检查不改动。
/story-short-analyze
Story short analyze
短篇网文拆文。拆解爆款短篇的故事核、结构、情感线和反转设计。
/story-short-scan
Story short scan
短篇网文扫榜。分析知乎盐言、番茄短篇等平台热门数据。
/story-short-write
Story short write
短篇网文写作。辅助短篇小说创作,从构思到成稿。
/story
Story
网文工具箱路由入口。根据模糊意图自动分发到对应的写作、拆文或扫榜工具。
/browser-cdp
Browser cdp
浏览器操控。通过 CDP 复用 Chrome 登录态执行浏览器自动化。
/story-cover
Story cover
小说封面生成。根据书名、作者名和题材生成专业网文封面。
/story-deslop
Story deslop
网文去 AI 味。检测并清理模板化、解释腔和过度工整表达。
/story-import
Story import
逆向导入已有小说,将成稿或半成品解析为可续写项目。
/story-long-analyze
Story long analyze
长篇网文拆文,分析黄金三章、人设、爽点和长线节奏。
/story-long-scan
Story long scan
长篇网文扫榜,分析起点、番茄、晋江等平台趋势。
/story-long-write
Story long write
长篇网文写作,从选题、大纲到逐章正文和持续追踪。
/story-review
Story review
多视角小说审查;ZCode 项目 agents 不可用时自动降级 solo。
Persistent session memory for AI coding agents — local-first, with on-device inference, associative recall, and drift detection. Works with Claude Code, Cursor,…
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12 views 0 likesBrowser Harness | Self-healing harness that enables LLMs to complete any task.
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