LLM Mart Basic
@llm-mart · Joined Jun 2026
Manage Ghost CMS content over the Admin API — browse posts, pages,
Deploy, manage, and troubleshoot self-hosted GitHub Actions runners. Covers systemd service, Docker containers, Kubernetes (Actions Runner Controller), and the Scale Set Client. Use when setting up a CI runner, debugging registration failures, designing autoscaling, or hardening
Operate, configure, provision, secure, and troubleshoot Grafana OSS, Enterprise, and Cloud, including dashboards, folders, data sources, annotations, alert rules, contact points, notification policies, silences, mute timings, service accounts, RBAC, plugins, APIs, and as-code wor
Search, download, and extract public-domain books from Project Gutenberg. Look up books by ID or keyword via gutendex, download plain-text and EPUB editions, strip licensing boilerplate, extract clean text from EPUB for illustrated works, and classify fiction vs non-fiction. Ship
Build production search and NLP pipelines with Haystack. Pipeline DAG composition, document stores, retrievers, PromptBuilder (Jinja2), generators, evaluation, Hayhooks deployment. Use when building search pipelines or comparing NLP application frameworks. Do not use this skill f
Build, customize, and debug advanced Hugo CMS themes — template architecture, asset pipeline (CSS/JS/image processing), shortcodes and render hooks, page bundles, cover images, Hugo Modules, performance, SEO, and CI/CD. Use when working on a Hugo theme or site template layer. Do
Plan the implementation of an approved requirement or specification: produce an executable, dependency-aware delivery plan covering work breakdown, dependency mapping, critical path, ownership, parallelism and sequencing, rollout strategy, rollback and recovery paths, and verific
Convert operational incident and near-miss evidence into durable product, engineering, test, evaluation, and governance improvements with verified closure. Separate observed facts from causal hypotheses and unresolved uncertainty; map follow-up work across code, tests, skills, op
Query your Jellyfin media server from the terminal — recently added media,
'Interact with Atlassian Jira from the terminal: search issues with
Diagnose Kanban flow problems and design board operating models. Load this when your team is struggling with throughput, cycle times are unpredictable, multiple stakeholders compete for the same engineers, or you're wondering if Kanban is right for you. Do not use this skill for
Build multi-agent AI systems with LangGraph — the low-level orchestration framework for stateful, graph-based agent workflows. Covers supervisor, swarm, and hierarchical multi-agent patterns; subgraph composition; state management (checkpointers/stores); persistence; evals; and p
Analyze legal and regulatory risk, IP, contracts, privacy, governance, and employment questions as structured issue-spotting for counsel. Do not use this methodology as legal advice or for technical security implementation, CRM, or delivery execution.
Guide a bounded, user-led coaching process for personal goals, decisions, transitions, habits, recurring nonclinical patterns, accountability, and progress review. Use when a person explicitly asks to be coached, wants reflective challenge, or wants help examining ambivalence whi
Operate, configure, secure, and troubleshoot the LiteLLM AI gateway (proxy) and Python SDK: run the proxy (litellm --config), route to 100+ providers through one OpenAI-compatible API, configure model lists and routing/reliability, virtual keys, teams, budgets, rate limits, cachi
Operate, configure, benchmark, and troubleshoot llama.cpp across CPU, Metal, CUDA, HIP/ROCm, Vulkan, SYCL, and hybrid or multi-GPU systems. Use when installing or building llama.cpp, selecting or inspecting GGUF models, running llama-cli, serving an OpenAI-compatible API with lla
Build LLM applications with the LlamaIndex framework. Use when working with LlamaIndex or comparing RAG and agent orchestration frameworks. Do not use this skill for unrelated requests; route to the nearest named specialist.
Capture MeshCore Companion packets via BLE, serial, or TCP. Do not use this skill for unrelated requests; route to the nearest named specialist.
Plan and execute safe cross-system migrations, including service extraction from monoliths. Use when moving data, schemas, interfaces, infrastructure, or service ownership through compatibility windows, dual-running, reconciliation, cutover, recovery, or deprecation. Do not use f
Plan and execute production ML engineering work — model training and fine-tuning (LoRA/QLoRA), evaluation and eval-set design, quantization decisions, inference deployment, and regression triage, grounded in practical engineering patterns for production ML systems. Do not use for
Fourteen posts of being wrong in production, compressed to checkboxes
Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds
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.
/export
Export
Export a page or set of pages
/gaps
Gaps
What is missing from my understanding
/graph-export
Graph export
Export the graph for outside analysis
/graph
Graph
Report the shape of the graph
/handoff
Handoff
Prepare a handoff brief
/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
Make any song you can imagine
39 views 0 likesLeading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars
37 views 0 likesHermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research
36 views 0 likesKilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster
34 views 0 likesGeneral-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…
20 views 0 likesAutonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.
20 views 0 likesTSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目
15 views 0 likesCurated, verified Agent Skills powered by ModelStudio.
18 views 0 likesRun Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…
17 views 0 likespi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…
14 views 0 likesA persistent workspace for development work that self-improves and continues beyond one session.
35 views 0 likesOpen-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.
20 views 0 likes📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…
28 views 0 likesDeterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.
31 views 0 likesDeterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…
20 views 0 likesNative Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…
34 views 0 likesAgent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
15 views 0 likesGit for agent memory. Branches, diffs, PRs, and rollback for what your agents know.
35 views 0 likesMulti-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…
16 views 0 likesProduction-grade MCP server for MikroTik RouterOS with secure AI-native network automation.
31 views 0 likes