LLM Mart Basic

Simplifies, polishes, and declutters code without changing behavior. Use when asked to simplify, clean up, refactor, declutter, remove dead code or AI slop, or improve readability. For analysis-only reports without code changes, use code-simplicity-reviewer agent.

Terraform and OpenTofu configuration, modules, testing, state management, and HCL review. Use when working with Terraform, OpenTofu, HCL, tfvars, tftest, state migration, or IaC patterns.

Audit whether tests detect regressions in the behavior they claim to protect. Find mocked-away subjects, weak or circular assertions, undiscriminating fixtures, swallowed failures, and tests missing from gates. Use for test-quality audits, suspected false confidence in generated

Enforces fresh verification evidence before any completion claim. Use when about to claim "tests pass", "bug fixed", "done", "ready to merge", handing off work, or before editing when a request has ambiguous scope.

Prose editing, rewriting, and humanizing text for natural tone, or auditing a draft for AI tells without rewriting. Use when asked to write, rewrite, edit, humanize, proofread, fix tone, remove AI language, or check whether writing reads as AI. For copy, docs, blog posts, emails,

Generic test writing discipline: test quality, real assertions, anti-patterns, and rationalization resistance. Use when writing tests, adding test coverage, or fixing failing tests for any language or framework. Complements language-specific skills.

Build or refresh the Operator Project Index.

Initialize and configure the Operator Project Brain.

Diagnose and repair Operator memory load failures.

Initialize and configure the Operator User Partition.

Take an agent-written app from repo to live production on the user's OWN accounts, with providers they choose (hosting, database, auth, payments, email, domain/DNS). The human connects accounts and approves changes; supported wiring operations run through a local CLI and produce

Primary router skill for broad .NET work. Classify the repo by app model and cross-cutting concern first, then switch to the narrowest matching .NET skill instead of staying at a generic layer.

Use a repo-root `.editorconfig` to configure free .NET analyzer and style rules. Use when a .NET repo needs rule severity, code-style options, section layout, or analyzer ownership made explicit. Nested `.editorconfig` files are allowed when they serve a clear subtree-specific pu

Design or review .NET solution architecture across modular monoliths, clean architecture, vertical slices, microservices, DDD, CQRS, and cloud-native boundaries without over-engineering.

Use the open-source free `ArchUnitNET` library for architecture rules in .NET tests. Use when a repo needs richer architecture assertions than lightweight fluent rule libraries usually provide.

Build, upgrade, and operate .NET Aspire application hosts with current CLI, AppHost, ServiceDefaults, integrations, dashboard, testing, and Azure deployment patterns for distributed apps.

Build, debug, modernize, or review ASP.NET Core applications with correct hosting, middleware, security, configuration, logging, and deployment patterns on current .NET.

Use the open-source free `Asynkron.Profiler` dotnet tool for CLI-first CPU, allocation, exception, contention, and heap profiling of .NET commands or existing trace artifacts.

Build, review, or migrate Azure Functions in .NET with correct execution model, isolated worker setup, bindings, DI, and Durable Functions patterns.

Use Biome in .NET repositories that ship Node-based frontend assets and want a fast combined formatter-linter-import organizer for JavaScript, TypeScript, CSS, JSON, GraphQL, or HTML. Use when a repo prefers a modern all-in-one CLI over a larger ESLint plus Prettier style stack.

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.

`crabbox inspect` prints the full record for a single lease: state, provider,

Run named, repo-local jobs defined in your Crabbox config.

`crabbox list` shows the current Crabbox machines (leases) for a provider. It is

`crabbox login` authenticates the CLI against a coordinator, stores the

`crabbox logout` clears the stored broker token from your user config so the CLI

`crabbox logs` prints the retained command output for a recorded run.

`crabbox marketplace` previews the Crabbox credits gateway: one Crabbox billing

`crabbox media` turns a recorded desktop video into lightweight review

`crabbox open` prepares an existing SSH-capable lease for an external editor.

`crabbox pause` pauses a single lease, freeing the remote compute while

`crabbox pond` is the cross-provider peer-discovery and lifecycle surface for a

`crabbox pool` contains machine-pool helpers. `pool list` keeps the older

`crabbox ports` bridges provider-native port publishing for an existing Crabbox

`crabbox prewarm` leases a reusable box and prepares it for test runs. For

`crabbox providers` prints the provider capability matrix that the CLI compiles

`crabbox receipt <run-id>` retrieves a brokered run's committed terminal

`crabbox results` prints the structured test summary attached to a recorded

`crabbox resume` resumes a lease previously paused with [`pause`](pause.md),

`crabbox run` syncs the current dirty checkout to a box, runs a command there,

`crabbox screenshot` captures a single PNG from a desktop lease without opening a

A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从…

Convert Files / Folders / GitHub Repos Into AI / LLM-ready Files

Open-source, local-first conversational AI video editor with a professional multi-track timeline, Agent Skills, MCP integration, and Remotion rendering.

Maintainer-governed agent for evidence-backed open-source contribution proposals

A Claude Code skill by Hao (駱君昊) that learns your Facebook voice and auto-posts to FB / IG / Threads / X with a 14-day content calendar. Mega-viral validated: 8…

Local-first AI agent workspace for coding, writing, design, research, and automation — one runtime for desktop GUI and TUI.

Open-source AI Agent platform for teams. Your agents don't just chat — they read files, run code, call APIs, and deliver results.

Give your AI agent eyes for PDFs — structured text, tables, OCR, visual evidence, and page-level citations via MCP. Native Rust, local-first.

Real-world AI penetration testing engineer for authorized assessments — built-in cloud module covering AWS/Azure/GCP + Aliyun/Tencent/Huawei clouds. Built on Cl…

OpenGUI is an Android GUI agent framework for phone-use AI that can see, plan, and operate real mobile apps through the GUI.

Tinybot is a lightweight personal AI Agent that is constantly evolving

Goink 桌面 AI 小说创作助手，对话式写作 + 自动状态追踪 + 本地语义搜索。跨平台开箱即用。AI Agent Novel Generator.

Pluggable DeepSeek-colored TUI for DeepSeek Harness

Entity-level git merge driver. Resolves false conflicts git invents when independent agents edit the same file. ~95% reduction vs. line-based merge.

Percho: Minimalist desktop GUI for the Pi coding agent — the same engine as the Pi CLI, in a clean visual interface. Multi-session chat, visual tool approvals,…

Run Claude Code, Codex & Gemini in parallel on Windows & macOS — git worktree fan-out with atomic hunk adoption, approval gates, reboot-surviving sessions

A hierarchical memory framework for personalized presentation agents. Try it at memslides.com.

Real-time multimodal desktop agent evolving toward a persistent AI OS interface (0.1 α).

clawdcursor compiles whatever's on screen into one UI map — accessibility tree and OCR fused into stable, addressable elements, with a screenshot only when need…

Repeatable agentic engineering. The workflow layer that turns AI coding agents into a disciplined factory: durable specs, fresh-context workers, adversarial cro…