LLM Mart Basic
@llm-mart · Joined Jun 2026
Trains in China through the 12306 MCP server — routes, dates, options, connections and stops with no screen; booking only on the user's word, in the 12306 app on their phone, stopping before payment. Use when the user asks about 火车票 / 高铁 / 12306 or a train between two cities.
Plan a trip end to end — itinerary by day, a packing list to tick off, a budget, and the calendar checked for conflicts — as pages in the workspace. Use when the user is going somewhere for more than a day and wants a plan, an itinerary or a packing list.
Look back at the past week and set up the next one — calendar, mail, goals and files in one page, with a short plan. Use when the user asks for a weekly review, a week in review, "how did my week go" or to plan next week.
Подготовка русского текста к проверке системой «Антиплагиат» (antiplagiat.ru, «Антиплагиат.ВУЗ»): оценка доли «ИИ-сгенерированного» текста по фрагментам в духе модуля ИИ-детекции, переписывание подсвеченных абзацев своим голосом, чистка технических артефактов, из-за которых докум
Аудит и правка русских текстов от признаков ИИ-генерации («ИИ-стиль», канцелярит, кальки с английского, шаблонная структура). Используй, когда просят «убрать ИИ-стиль», «очеловечить текст», «почистить от нейросетевых штампов», «проверить, не звучит ли как ChatGPT», «вычистить кан
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
Convert a grover_base checkpoint (encoder-only or encoder + vocab heads) into a hybrid checkpoint by adding a randomly-initialized cMIM decoder + latent_dist, then continue pretraining on the user's corpus as hybrid (vocab + contrast). Effectively kermt-continue-pretrain with a o
Continue KERMT pretraining on a custom SMILES corpus with a grover_base, cmim, or hybrid checkpoint. Use a local checkpoint or optionally download a pinned Hugging Face model bundle using HF_TOKEN if configured. Run containerized training and write model bundles, prepared data, l
Extract per-molecule embeddings from any encoder-bearing KERMT checkpoint. Use a local checkpoint or optionally download a pinned Hugging Face model bundle using HF_TOKEN if configured. Run containerized embedding extraction and write model bundles, per-readout .npy embeddings, c
Run predictions with a finetuned KERMT checkpoint on a SMILES-only CSV. The skill validates that the input ckpt has task FFN heads (refuses pretrain ckpts with a redirect to kermt-finetune), validates the CSV, prepares the data (clean + rdkit_2d features), then launches main.py p
Check progress for a detached KERMT run (pretrain, finetune, or any kermt_run_detached invocation). Reads run.json, queries docker for container state, tails the pretrain/finetune log, and parses progress lines (epoch, step, val loss).
Bootstrap the KERMT agent environment — verify host docker + nvidia-container-toolkit, build the kermt:latest image from the repo's Dockerfile if it doesn't yet exist, and run a GPU smoke test inside the container. Every other kermt-* skill depends on this; invoke it first.
NOTE: your protein sequence and the retrieved MSA alignment are transmitted to external NVIDIA-hosted APIs (health.api.nvidia.com) on every call. Use local NIM containers for confidential or proprietary sequences. Run a complete protein structure prediction pipeline using NVIDIA
Use when porting circuits from another framework (e.g. Qiskit) into CUDA-Q kernels while preserving the source algorithm and validation fidelity.
Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).
LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.
LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API.
Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routing in Python.
Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline.
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.
Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.
/health
Health
Quick health check
/hubs
Hubs
Find pages that swallowed the graph
/index
Index
Rebuild the index
/ingest-chats
Ingest chats
Import an exported chat history
/ingest-highlights
Ingest highlights
Ingest book or article highlights
/ingest-mine
Ingest mine
Ingest your own finished work
/ingest-newsletter
Ingest newsletter
Ingest newsletters without duplicating
/ingest-paper
Ingest paper
Ingest an academic paper
/ingest-pdf
Ingest pdf
Ingest a PDF
/ingest-url
Ingest url
Clip and ingest a web page
/ingest-voice
Ingest voice
Ingest a voice note
/ingest-youtube
Ingest youtube
Ingest a video or podcast transcript
/ingest
Ingest
Ingest new material from raw/ into the wiki
/init
Init
Scaffold a new vault
/install
Install
Install the skills, commands and agents
/know
Know
What do I know about a topic
/link
Link
Find and add missing connections
/lint
Lint
Audit structure and repair what is mechanical
/merge
Merge
Merge two pages
/metrics
Metrics
Record a dated metrics snapshot
Claude Code skills for Chinese-narration recaps from supported video files, with optional editable JianYing/CapCut draft export. | 用 Claude Code skills 为支持的视频文件…
8 views 0 likesDrive the Unity Editor from an AI agent or the terminal. The Editor serves MCP itself over HTTP, so there is no second process to run, and the isuzu-unity-cli c…
3 views 0 likes面向企业的数字员工构建与运行平台:把专业员工的经验、流程与判断标准,固化为可随时上岗、可配置、可审批、可观测的 AI 数字员工。
1 views 0 likesA local-first, Pi-powered AI agent workspace for Desktop, WebUI, and CLI
1 views 0 likes660+ muapi-hosted generative-media models plus community-submitted third-party API tools (SEO, enrichment, social, scraping) — one YAML file per entry, browsabl…
5 views 0 likesA compounding agent OS for recursive agents. Also an open source alternative to Grok Bot and Meta's Muse.
6 views 0 likesIndependent desktop client for OpenCode 2. Manage projects, sessions, parallel agents, requests, and changes on Linux and macOS.
9 views 0 likesProduction agent skills for Claude Code, Cursor, and any SKILL.md harness — Codex fleets, video pipeline, monorepo review bundles, multi-chain explorer.
11 views 0 likesSee and manage what your coding assistants load — skills, commands, subagents, plugins and MCP servers, with real usage.
10 views 0 likesAn Enterprise-Grade Full-Stack RBAC Permission Management System Built with Go + React
9 views 0 likesCreate AI Agents in a No-Code Visual Builder or TypeScript SDK with full 2-way sync. For shipping AI assistants and multi-agent AI workflows.
9 views 0 likes基于 DeepSeek Harness(DSH)的稳定桌面端,集成Git、内置浏览器与记忆功能 | DeepSeek Harness desktop GUI with local workspaces, Git, browser and memory.
9 views 0 likes⚡ Control Apache Airflow with natural language via MCP. Chat with your workflows using Claude, GPT, or any LLM — no REST API calls needed. Supports Airflow 2.x…
2 views 0 likesOpen-source CLI, schemas, resolver, and DSH agent tools for DSH Plugin Hub
1 views 0 likesPi Coding Agent 中文学习蓝皮书:从安装与第一个可验收任务开始,逐步掌握 Session、Context、Skill、Extension、Subagent 与长期 Agent 工作流。
1 views 0 likesSelf-hosted framework for orchestrating fleets of specialist AI agents — ensemble reasoning and a full agentic coding pipeline, model-agnostic and local-friendl…
4 views 0 likesSelf-hosted, vendor-neutral control plane for your local coding agents (Claude Code & Codex). Run your agents, on any plane.
2 views 0 likesA practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and…
5 views 0 likesVibe Coding 从入门到精通教程|AI 结对编程工作流|Prompt、Skill、Workflow、上下文管理、codex实战指南
2 views 0 likesStatic security scanner for LLM agents — prompt injection, MCP config auditing, taint analysis. 51 rules mapped to OWASP Agentic Top 10 (2026). Works with LangC…
1 views 0 likes