LLM Mart Basic

SST (Ion) infrastructure-as-code — TypeScript-first serverless on AWS with Pulumi, resource linking, and live Lambda dev

Infrastructure as Code with HashiCorp Terraform

AWS SDK v3 for TypeScript — modular clients, command pattern, S3, DynamoDB, SQS, Lambda, SNS, Secrets Manager

Cloudflare Workers edge compute platform — Wrangler CLI, KV, D1, R2, Durable Objects, Queues, Workers AI

Vercel deployment platform — project configuration, serverless/edge functions, Routing Middleware, cron jobs, environment variables, monorepo setup

Inspect a codebase, a stack the user describes, or a description of what they want to build; map what is there to agents-inc catalog skills — or intent to candidate built-in stacks the user picks from — and emit a SeedPayload plus a human-readable proposal report. Use when seedin

Composable component APIs — parts, state, polymorphism

Investigation flow (Glob -> Grep -> Read), evidence-based research with file:line references, structured output format for AI consumption. Use for pattern discovery, implementation research, and codebase investigation.

Backend specification planning frameworks. Use when a spec touches API endpoints, database schema, middleware, or auth. Covers endpoint contracts with request/response shapes, error catalogs, auth per endpoint, schema design with constraints and indexes, migration strategy, and m

CLI specification planning frameworks. Use when a spec touches a command surface, an interactive flow, config precedence, exit codes, or output modes. Covers flag contracts, prompt flow design, precedence tables, exit-code taxonomy, TTY/piped/JSON output, error text, signals, and

Frontend specification planning frameworks. Use when a spec touches UI components, forms, client state, or user-facing flows. Covers UI-state completeness (loading, error, empty, success), component boundaries, form validation contracts, state ownership, and measurable UI success

Backend code review patterns. Use when reviewing API routes, database operations, auth middleware, and server utilities. Covers injection, boundary validation, authorization coverage, secret/PII exposure, error leakage, and query patterns.

CLI code review patterns. Use when reviewing CLI applications built with Commander.js, @clack/prompts, picocolors. Covers exit codes, signal handling, error messages, user experience, testing adequacy.

Infrastructure code review patterns. Use when reviewing CI/CD workflows, Dockerfiles, deployment configs, and IaC. Covers supply-chain pinning, secret exposure, container hygiene, least-privilege permissions, and deployment safety.

Code review patterns, feedback principles. Use when reviewing PRs, implementations, or making approval/rejection decisions. Covers self-correction, progress tracking, feedback principles, severity levels.

UI component review patterns. Use when reviewing React components, hooks, props, state, styling, and accessibility. Covers rules of hooks, effect cleanup, render performance, list keys, keyboard and ARIA patterns.

React Native Gesture Handler - gesture types, GestureDetector, gesture composition, state machine, platform-specific gestures, swipeable rows, hover gestures

React Native Reanimated 4 - shared values, animated styles, spring/timing/decay, layout animations, gesture integration, scroll-driven animations, interpolation, worklets, CSS animations

React Native Skia GPU-accelerated 2D graphics - Canvas, declarative drawing, shaders, image filters, Paragraph text, Atlas batch rendering, Reanimated animations

Background fetch, processing tasks, background location, headless JS, battery optimization - Expo and bare React Native

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 shard` forks a [checkpoint](checkpoint.md) into `--count` leases

`crabbox share` grants other people access to an existing lease through the

`crabbox ssh` resolves a lease and prints a ready-to-run `ssh` command for it.

`crabbox status` prints the current state of a lease: its slug, provider,

`crabbox stop` ends a single lease. For coordinator-backed and direct cloud

`crabbox sync-plan` prints the local sync manifest and its size hotspots

`crabbox tunnel` opens one foreground SSH local port-forward to a resolved

`crabbox unshare` removes sharing rules from a coordinator-backed lease. It is

`crabbox usage` reports lease cost and usage estimates from the broker, broken down by user, organization, or the whole fleet.

`crabbox verify` checks a signed run receipt produced by `crabbox run --attest`.

`crabbox vnc` prints (or opens) the connection details for a desktop-capable

`crabbox warmup` leases a box and waits until it is ready: it provisions (or

`crabbox watch` runs a command on a warm lease, then watches the local

Linux portal viewers default to **Match window**: only the connected controller

`crabbox whoami` calls the broker's `/v1/whoami` endpoint and prints the

Vet a new or changed third-party dependency for license, provenance, and supply-chain risk before any install runs.

Inspect ADR health read-only; optionally select one ADR with --adr N.

{{SKILL_ENTRY:decision-lifecycle}}

Assemble the governance record for a range — commits, overrides, ADRs, sprint auto-decisions, open questions, checkpoint findings — into one dated audit packet. Read-only.

Lightweight Q&A about the project — answer from context and return, no routing, no state change.

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…