LLM Mart Basic

Applies client-server architecture for web/mobile apps. Use when designing systems with centralized backend services, trust boundaries, or offline-first sync.

Applies CQRS and Event Sourcing for read/write separation and audit trails. Use when designing systems with complex domain logic or full state-change history.

Models a business in its own language. Use when the domain has real business rules to capture.

Applies event-driven async messaging to decouple producers and consumers. Use when designing real-time or multi-subscriber systems needing loose coupling.

Applies Functional Core, Imperative Shell to isolate logic from side effects. Use when business logic is entangled with I/O or unit tests are slow and brittle.

Applies hexagonal architecture isolating domain from infrastructure. Use when designing systems where testability and port/adapter separation are priorities.

Applies layered n-tier architecture with enforced boundaries. Use when designing moderate systems needing clear presentation, domain, and persistence layers.

Applies microkernel architecture with minimal core and plugin extensibility. Use when building platforms where third parties extend core functionality.

Applies microservices for independent deployment and per-service scaling. Use when teams need autonomous release cycles with distinct capability scaling needs.

Applies modular monolith with enforced internal boundaries. Use when teams want service-level autonomy without distributed system overhead.

Applies pipes-and-filters for sequential data transformations. Use when data flows through discrete stages like ETL, streaming analytics, or CI/CD pipelines.

Applies serverless FaaS patterns for event-driven workloads. Use when designing bursty workloads with minimal infrastructure and pay-per-execution cost model.

Applies coarse-grained service architecture for deployment independence. Use when independent deployment is needed but shared databases rule out microservices.

Applies data-grid architecture for high-traffic stateful workloads. Use when a single database cannot scale and in-memory partitioning is needed.

Selects and routes to the right architecture paradigm. Use when choosing patterns for a new system or comparing trade-offs before making architecture decisions.

Generates a Mermaid architecture diagram showing high-level component relationships. Use when visualizing how plugins or modules fit together.

Traces execution paths through the code graph with criticality scoring and Mermaid charts. Use when understanding how a function propagates through the system.

Generates a Mermaid class diagram showing types, inheritance, and composition. Use when visualizing class hierarchies or documenting a module public API.

Detects architectural clusters and coupling boundaries via community detection on the code graph. Use when identifying module groupings or refactoring targets.

Generates a Mermaid sequence diagram showing how data moves between components. Use when tracing request flows or documenting data transformation pipelines.

A green PR, a controller reporting success, and not one line of the new code running

Generate requirements from goal and research

Run or re-run research phase for current spec

Smart entry point that detects if you need a new spec or should resume existing

Show all specs and their current status

Switch active spec

Generate implementation tasks from design

Decompose a large feature into multiple dependency-aware specs (epic triage)

Check for or install a verified Tree Ring Memory CLI update without changing installation scope

This directory contains the command implementations for the fast-agent CLI.

They operate it without you.

Promised, measured, accepted. A number nobody signed is claimed, not delivered.

Prepare the meeting. One page from the record.

Find the receipt. A dated line, or it did not happen.

Diagnose trust. Process gap, or they stopped trusting you.

Generate, convert, and maintain animated GitHub-safe Markdown documents with animated SVG diagrams. Covers four SVG patterns (architecture flow, lifecycle loop, field carousel, timeline phases), guided interview for any doc type (README, architecture guide, runbook, API reference, tutorial, RFC, post-mortem, how-it-works, or custom), converting existing plain Markdown, diffing for stale diagrams, quality auditing, local preview, and multi-platform export. Use when asked to "create a README for X", "write an architecture doc", "animate this guide", "convert my doc to animated", "check if my diagrams are stale", or "export my doc for Confluence".

AWS profile management for MCP servers — discover profiles across SSO, Granted, and assumed-role chains, check credential TTL, switch profiles across VS Code and Claude Code MCP configs, and scan AWS Organization accounts.

Structured guidance for AWS CloudFront distributions, WAF web ACLs, Lambda@Edge, CloudFront Functions, Firewall Manager multi-account enforcement, and IAM/IRSA patterns. Covers OAC, cache policies, security headers, managed rule groups, rate limiting, FMS FIRST/MIDDLE/LAST ownership model, and production-ready Terraform generation.

Azure identity (Workload Identity, OIDC, Entra ID), resource tagging, AKS platform patterns, RBAC scoping, and production-readiness review — with Terraform generation.

Design, run, and debug Chaos Engineering experiments on Kubernetes using Litmus Chaos v3 and Chaos Mesh v2. Covers fault injection (pod-delete, network-loss, CPU stress, node-drain), steady-state hypothesis probes, GameDay runbooks, scheduled experiments, DORA feedback loop, and RBAC setup. Use when asked to "inject a pod fault", "run a GameDay", "schedule chaos experiments", or "debug why my ChaosEngine is stuck".

Bootstrap Checkov on a developer laptop, run static or plan-level Terraform security scanning for AWS/Azure/GCP/EKS, resolve private GitHub modules via gh CLI, generate pre-commit hooks, produce multi-format output (cli/json/sarif/junit), and fix violations with AI-generated patches. Use when asked to "scan my Terraform", "run checkov", "check my IaC for security issues", "set up checkov pre-commit", or "fix checkov findings".

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-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…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP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

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi 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…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.