LLM Mart Basic

Run ESM protein language models — ESMC for embeddings and representations, ESMFold2 for structure prediction, and ESM3 for generative multimodal protein design across sequence, structure, and function — locally or through the hosted Biohub Platform API (formerly Forge). Use when

Manipulate, annotate, and render phylogenetic trees programmatically with the ETE Toolkit (ete3) — parse and edit Newick/NHX, detect duplication/speciation events, infer orthology and paralogy, query NCBI taxonomy, and export PDF/SVG figures. Use when traversing or reformatting t

Parse and write FCS (Flow Cytometry Standard) files v2.0-3.1 with FlowIO — extract event data as NumPy arrays, read $-keyword metadata and channel/parameter definitions, and convert events to CSV or pandas DataFrame. Use when loading raw .fcs flow-cytometry files, inspecting chan

Run fast one-liner queries to 20+ bioinformatics databases from the gget CLI or Python — gene info (Ensembl), BLAST, AlphaFold structures, Enrichr enrichment, and more. Use for quick interactive lookups of genes, sequences, structures, or pathways — for batch processing or advanc

Analyze and engineer protein glycosylation — scan sequences for N-glycosylation sequons (N-X-S/T), predict O-glycosylation hotspots, and reach curated glycoengineering tools (NetOGlyc, GlycoShield, GlycoWorkbench). Use when identifying or designing glycosylation sites, optimizing

Extract and preprocess tiles from whole-slide images (WSI) with histolab — OpenSlide-backed slide loading, tissue detection and masks, Random/Grid/Score tile extraction, and image/morphological filters for H&E preprocessing. Use when the user needs lightweight WSI slide preproces

Manage, annotate, and trace biological data with LaminDB, an open-source FAIR data framework that makes datasets queryable, versioned, and reproducible. Use when registering or querying biological datasets (scRNA-seq, spatial, flow cytometry), validating and curating data against

Design protein sequences around bound ligands, metals, and nucleic acids with LigandMPNN (Dauparas 2023) — inverse folding that conditions on non-protein context, so binding-pocket and metal-site residues are chosen to fit the actual ligand. Use when designing a small-molecule or

Analyze Neuropixels 1.0/2.0 extracellular electrophysiology with SpikeInterface — load SpikeGLX/Open Ephys recordings, preprocess and motion-correct, run Kilosort4 spike sorting, compute quality metrics, apply Allen/IBL curation, and do AI-assisted visual inspection. Use when wor

Runs FASTQ-to-VCF germline and somatic variant calling via the Nextflow nf-core/sarek pipeline pinned to -r 3.10.0 — builds the samplesheet.csv (patient, sex, status, sample, lane, fastq_1, fastq_2), runs bwa-mem/bwa-mem2/dragmap alignment plus GATK4 MarkDuplicates and BQSR again

Run full computational-pathology workflows with PathML — whole-slide-image (WSI) analysis across 160+ slide formats, multiplexed immunofluorescence (CODEX, Vectra, MERFISH), nucleus segmentation/classification (HoVer-Net, HACTNet), tissue- and cell-graph construction, HDF5 datase

Build phylogenetic trees end-to-end from raw sequences — MAFFT multiple sequence alignment, optional TrimAl trimming, IQ-TREE 3 maximum-likelihood inference with model selection and bootstraps, FastTree for large datasets, then visualize with ETE3 or FigTree. Use when reconstruct

Design protein sequences for a fixed backbone with ProteinMPNN (Dauparas 2022) — message-passing inverse folding that outputs sequences predicted to fold to a given structure, with fixed positions, tied/symmetric chains, amino-acid bias, and a soluble-model variant. Use when inve

Run differential gene expression analysis on bulk RNA-seq count matrices with PyDESeq2, the Python port of DESeq2 — size-factor normalization, dispersion estimation, Wald tests, FDR (Benjamini-Hochberg) correction, and volcano/MA plots. Use when identifying differentially express

Build complete mass-spectrometry workflows with pyOpenMS — feature detection, peptide identification, protein quantification, and full LC-MS/MS pipelines across many MS file formats (mzML, mzXML) and algorithms. Use for comprehensive proteomics and MS data processing — for simple

Read and write genomic alignment and variant files in Python with pysam (htslib bindings) — SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences, plus region extraction and per-base coverage/pileup. Use when scripting NGS data-processing pipelines that parse, filt

Runs 16S/ITS amplicon (microbiome) analysis with the QIIME 2 distribution (2026.7; the "amplicon" distribution was renamed "qiime2" in 2026.4) in the correct order: manifest import, cutadapt trim-paired primer removal BEFORE dada2 denoise-paired (trunc-len chosen from the demux q

Generate de-novo protein backbones with RFdiffusion (Watson 2023) — a diffusion model for unconditional monomer generation, motif scaffolding, binder design against a target, and symmetric oligomers. Use when generating a new protein backbone from scratch, scaffolding a functiona

Quantifies bulk RNA-seq transcript abundance with salmon 2.x (the Rust rewrite; selective alignment or --sketch) and kallisto (v0.52.0, kb-python workflow), builds a decoy-aware gentrome index, runs quant with --gcBias -l A, then imports estimates via tximport/tximeta with a tx2g

Run the standard single-cell RNA-seq analysis pipeline with Scanpy on AnnData — QC filtering, normalization, dimensionality reduction (PCA, UMAP, t-SNE), Leiden/Louvain clustering, marker/differential expression, PAGA trajectories, and plotting. Use when analyzing scRNA-seq data

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

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.

Run OCR in delegation mode — OCR handles file selection and rules, the host agent performs the actual review.

Run OpenCodeReview (OCR) to review code changes and autonomously apply fixes.

Log in to Hivemind and select your organization

Update the Hivemind plugin to the latest version

Log in to Hivemind and select your organization

Update the Hivemind plugin to the latest version

credo - Disable credo for this directory (silence onboarding and the [credo] line here, reversible)

credo - Enable credo for this directory (opt in; overrides a previous decline)

credo - Explain something in depth (what/why/example/consequences)

credo - Migrate an existing repo into the .credo/ structure

credo - Pin the target repo for credo's project layer (hub-aware), or show the resolved target

credo - Interactive guide to available topics and workflows

credo - Clear this session's default role (back to no role; the agent does everything)

credo - Set this session's default role to plan/clarify (owns clarifying 1_clarify items, no commits/push)

credo - Set this session's default role to task/build (owns implementing GO items incl. commits/push per dogma)

credo - Promote an accepted sandbox artifact from .credo/sandbox-tmp/ to .credo/sandbox/

credo - Set the session mode to active (intensive live collaboration, no keep-alive)

credo - Set the session mode to autonomous (work approved GO items unattended, hook-enforced keep-alive ON)

credo - Initialize session with main agent workflow instructions

credo - Set the session mode to passive (user available for clarifications only, no keep-alive)

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…