LLM Mart Basic

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.

Rollback deployment to previous version

Read project commands and documentation to optimize AI-assisted development process

Run CI checks and fix any errors until all tests pass

Perform comprehensive security assessment

Harden application security configuration

Capture and document session learnings

Setup automated release workflows

Configure CDN for optimal delivery

Setup complete testing infrastructure

Setup complete development environment

Configure code formatting tools

Configure Kubernetes deployment manifests

Setup code linting and quality tools

Configure load and performance testing

Setup monitoring and observability tools

Configure monorepo project structure

Implement API rate limiting

Setup visual regression testing

Open the Build with Claude contribution guide for writing a community story

Test and refine simulation accuracy with validation loops, bias detection, and continuous improvement frameworks.

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it.…

Curated systems, benchmarks, and papers etc. on memory for LLMs/MLLMs --- long-term context, retrieval, and reasoning.

:memo: Vimlike Modal Text Editor in Rust

CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.

Hermes Agent memory plugin/provider for scope-aware recall, SQLite truth, LanceDB semantic search, and hybrid retrieval.

For You Agent——AI 时代的个人随身数字人格。把你的模型、AI 账号、技能、提示词和工作方式，带到每一个 AI 工具里。

A coding agent: give it a prompt and it reads, writes, runs commands, and searches code in a loop until the work is done, using native tool-calling across OpenA…

A secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, Telegram, WhatsApp, Discord, Teams, and…

Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption

DeepSeek Harness Desktop (dsh-desktop). EAC: Embracing All Creation (揽尽万象). Bundled Node.js runtime with full dsh-CLI kernel, one-click startup, 10 built-in UI…

See your agent think. Zero-config observability & governance for 26 AI agent runtimes: Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Cline, Ope…

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP…

Yet another coding agent harness, lightweight and written in go.

a coding Agent from pi. ∞ providers, sub-agents, hashline edits, and a permission gate

Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting…

🧠 Leon is your open-source personal assistant.

The Station, an open-world multi-agent environment that models a miniature scientific ecosystem.

The Frontend Stack for Agents & Generative UI. React, Angular, Mobile, Slack, and more. Makers of the AG-UI Protocol

VelaTerm = iTerm2 + Codex, The Best Terminal for AI Coding