LLM Mart Basic

Places, routes, travel times, distances and weather in China through the 高德地图 (Amap) MCP server. Use when the user asks how far, how long, how to get somewhere (car, transit, bike, foot), what is near a place, or about the weather in a Chinese city.

Compare two to five options — products, plans, places, tools, offers — on the criteria that matter to the user, in a table the user can re-weight, with a recommendation. Use when the user asks which to pick, for a comparison, or "X vs Y".

The user's 飞书 / Lark through its command-line tool (lark-cli) — agenda, people and groups, reading and sending messages, events, tasks, documents — with no app open. Use when the user mentions 飞书, Lark, a 群, a 日程 or a 飞书文档, or wants a colleague told something.

Go through recent mail and sort it into needs-a-reply, waiting-on-others, to-do and can-ignore, with draft replies ready for review. Use when the user asks to triage, sort, catch up on or clear their inbox — never to send anything on its own.

Where a parcel is, when it will arrive and what a shipment would cost, through the 快递100 MCP server — any Chinese courier (顺丰, 京东, 中通, 圆通, 韵达, 邮政 and more) from a tracking number. Use when the user asks 快递到哪了, 什么时候到, 查一下单号, or how much it costs to send something.

Prepare for a meeting — who is in it, what was last said with them, what the user owes them and wants from them — as a one-page brief. Use when the user asks to prepare for or get ready for a meeting, a call or a visit; a trigger can run it before every meeting with a client.

Read and answer messages in the chat apps on the user's phone (微信 and the like) through the screen — catch up, draft a reply in the user's voice, send only text they confirmed. Use when the user asks what someone said on WeChat or wants a chat answered.

The user's 腾讯会议 via the official tmeet CLI — upcoming meetings, creating, changing or cancelling one, inviting people, then the recording, minutes, transcript and attendance. Use when the user mentions 腾讯会议, a 会议号, a 会议链接, 纪要 or 录制, or wants a meeting set up or looked up.

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.

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.

Turn a GAIA workflow misfire into a redacted, classified, filing-ready bug report in one read-only pass. Self-diagnoses config issues inline; files probable bugs upstream on confirmation.

Judge-the-form, human-gated hardening. Reviews recurring code-audit-frontend findings and, with approval, drafts the lowest-context-weight form (deterministic check / skill / path-scoped prose rule) into the working tree. Pass `list` to see live candidates or `why <finding_class>` to explain one.

Initialize a new project from the GAIA React template, renames, strips GAIA branding, configures i18n, installs Claude skills/plugins.

Plan a complex feature using GAIA's task-orchestration pattern, structures the work into fresh-context subagent phases for your approval. Does not implement.

Cut a new GAIA release, bump version, graduate CHANGELOG, regenerate manifest, open release PR, then tag on merge. Maintainer-only.

Detect and, on explicit consent, additively append the languages Serena is not indexing to the `languages:` list in `.serena/project.yml`, then prompt a Serena restart. Never mutates without a yes; inert without Serena.

Author an immutable SPEC artifact through Socratic discovery (spec-kit wrapper), then STOP. Terminal, never runs /gaia-plan; it prints a /gaia-plan prompt the human pastes into a fresh session. Pass `auto <description>` for non-interactive mode that answers its own questions.

Maintainer-only autonomous health audit + auto-heal loop. Runs N=3 fresh-team audit-fix-audit cycles with circuit breakers, reports an F-to-A+ verdict (folding in the shared Claude-integration fitness grade) or escalates.

Single post-init onboarding command; detects situation, runs only owed phases; safe to re-run. --reconfigure rotates token and re-selects tools.

GAIA before_specify hook: constitution placeholder check + spec-kit version-pin drift detection.

GAIA after_specify hook: immutability lint over the just-written SPEC artifact.

Close a plan after implementation+merge. Offers wiki-promote for the plan's consolidated SUMMARY.md, cold-consolidates an out-of-band merge, then early-reaps the local plan folder once cost is represented in cost.jsonl.

GAIA self-review: pre-gate-2 review pass on the in-progress SPEC draft.

Close a SPEC after implementation+merge. Optional drain of deferred wiki-promote, cold-consolidates an out-of-band merge into SUMMARY.md, then early-reaps the local SPEC folder once cost is represented in cost.jsonl.

GAIA Socratic discovery wrapper: /speckit-specify for the initial draft, then GAIA's own Socratic clarify loop.

GAIA before_implement hook: render PO-authored UATs into Playwright e2e specs at .playwright/e2e/spec-NNN/.

Promote merged SPEC or plan content into the GAIA wiki.

This project uses the GAIA preset. Bare `/speckit-clarify` is not the clarify path here: core clarify writes an off-shape artifact (a `## Clarifications` / `### Session` block with five-word answers) and carries a question cap GAIA does not use. Run `/gaia-spec` instead — it driv

GAIA-wrapped /speckit-specify: writes through core, then relocates the artifact to .gaia/local/specs/SPEC-NNN/SPEC.md and stamps GAIA frontmatter.

Show or configure the compact Fallow Impact statusline in Claude Code

Conduit — native SwiftUI iOS client for Hermes Agent

一个现代化的可视化规则引擎平台，用于编排复杂的 AI 工作流。在无限画布上设计、测试和部署 AI 流程——无需编写代码。结合 flowgram.ai 的能力与 Java 服务端，提供生产级工作流管理。在此之上提供AI Agent / Copilot的助手编排能力。

Job application tracker and AI-powered job search assistant. Helps job seekers manage their search journey with AI resume review, job matching, task logging, an…

📝 Markdown and HTML renderer for Svelte 5 — built for streaming AI agent output from Claude Code, ChatGPT, and agentic workflows. XSS-safe defaults, token cach…

ServiceNow MCP server: 500+ tools and 26 AI capabilities for any AI (Claude, ChatGPT, Gemini, Cursor, Copilot). Multi-transport (stdio, SSE, HTTP), A2A, dynamic…

Free crypto news API - real-time aggregator for Bitcoin, Ethereum, DeFi, Solana & altcoins. No API key required. RSS/Atom feeds, JSON REST API, historical archi…

Build production-ready AI agents in both Python and Typescript.

From agent user to agent builder: build a Claude Code-style coding agent from scratch in Python: 8 articles, 4 videos, one codebase

🪁 A lightweight, modern Kubernetes dashboard that unifies multi-cluster and resource management, enterprise-grade user governance (OAuth, RBAC, and audit logs)…

Stateful runtime management for LLM agents—inject, manipulate, and retrieve Python objects across turns.

AgentCall lets AI Agents join meetings with voice, video & screen-share to build together. Supports Google Meet, Teams, Zoom (Beta)

Kition brings Markdown, DataTable, WhiteBoard, a tool-using AI agent, browser research, and visual workflows into one desktop workspace.

IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.

A powerful Model Context Protocol (MCP) server providing comprehensive Google Maps API integration with LLM processing capabilities.

Turn your Claude Pro/Max subscription into an OpenAI-compatible API for your IDEs and devices — LAN auth, per-key quotas, response cache, disciplined cli.js ali…

Paw Work - selection-first web agent for Chrome: select on the live page, describe the outcome, take away an editable office file. BYOK, sandboxed, no server.

基于 AI Agent + MCP 工具链 + 渗透 Skill 编排， 配合大语言模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。

Lexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台

First AI Journey for DevOps - with comprehensive learning paths, practical tips, and enterprise guidelines

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-…