LLM Mart Basic

Generate a draw.io architecture diagram (or PNG) from an Architecture YAML file. Produces .drawio XML following the official Company template style: DC containers with double-border, network zones with dashed borders, correct shapes for each component type (hexagon for F5/FW, par

CI enforcement gate. Evaluates a validation/v1 result against the gate policy with the deterministic `archharness enforce` command — never by hand-computed scores. Use in CI pipeline only, not for human review. Inputs: validate_result.json and arch-gate-policy.yaml. Outputs: enfo

Generate a prioritized improvement plan for an architecture. Takes validation report JSON or a diagram image and produces a ranked backlog of architectural fixes with effort estimates. Use when: you have validation findings and need to plan remediation, or when incrementally impr

Generate documentation from an architecture diagram or validation report. Produces Confluence-ready pages, executive summaries, or risk briefs. Use when: you need to present findings to a committee, write the architecture section of a project document, or generate a risk summary

Fetch application metadata from CMDB (ServiceNow, etc.) or Enterprise Architecture systems via REST API or CSV export. Provides high-confidence physical location and ownership data. Does NOT provide tech stack, protocols, or auth — those must come from other readers or interview.

Extract architecture requirements from diagram files or images. Supports: draw.io XML (.drawio), D2 (.d2), Architecture YAML (.yaml), and architecture images (.png/.jpg) via Claude Vision API. Outputs a partial requirements YAML with confidence scores. Use before arch-req-merge t

Extract architecture requirements from documents (PDF, DOCX, MD, TXT). Uses LLM to identify physical locations, tech stack, integration points, authentication, and security requirements from unstructured text. Outputs a partial requirements YAML. Medium confidence — always verify

Merge multiple partial requirements YAML files from different readers into one consolidated req.yaml. Detects field conflicts between sources, identifies critical gaps, and produces a gap report. Run after all readers, before the gap-filling interview in arch-requirements.

Architecture committee review. Evaluates a diagram or design document against enterprise standards with structured scoring per dimension. Produces a gate decision: APPROVED / APPROVED WITH CONDITIONS / REJECTED. Use when: preparing for architecture review board, requesting commit

Deep-dive security audit of a technical architecture diagram. Focused exclusively on authentication, authorization, credential protection, network boundaries, and data classification. Does NOT score overall quality — produces a prioritized security finding list. Use after arch-va

Validate a technical architecture diagram image against enterprise architecture standards. Scores six dimensions (10 pts total), outputs structured JSON + text report. Use when: reviewing a draw.io export, checking a new design before committee review, or running CI validation on

Pipeline gatekeeper that enforces the mandatory ArchHarness stage order (requirements -> design -> draw -> validate -> enforce -> security/review -> optimize -> report). Uses the executable `archharness workflow` state machine — checks recorded manifests and gate decisions before

Design a new technical architecture from requirements. Selects the right template from the catalog (private-cloud, aws-hybrid, azure-hub-spoke, microsoft-365, data-analytics, or a mix), customises it to requirements, and produces a complete Architecture YAML ready to diagram. Use

Generate a draw.io architecture diagram (or PNG) from an Architecture YAML file. Produces .drawio XML following the official Company template style: DC containers with double-border, network zones with dashed borders, correct shapes for each component type (hexagon for F5/FW, par

CI enforcement gate. Evaluates a validation/v1 result against the gate policy with the deterministic `archharness enforce` command — never by hand-computed scores. Use in CI pipeline only, not for human review. Inputs: validate_result.json and arch-gate-policy.yaml. Outputs: enfo

Generate a prioritized improvement plan for an architecture. Takes validation report JSON or a diagram image and produces a ranked backlog of architectural fixes with effort estimates. Use when: you have validation findings and need to plan remediation, or when incrementally impr

Generate documentation from an architecture diagram or validation report. Produces Confluence-ready pages, executive summaries, or risk briefs. Use when: you need to present findings to a committee, write the architecture section of a project document, or generate a risk summary

Fetch application metadata from CMDB (ServiceNow, etc.) or Enterprise Architecture systems via REST API or CSV export. Provides high-confidence physical location and ownership data. Does NOT provide tech stack, protocols, or auth — those must come from other readers or interview.

Extract architecture requirements from diagram files or images. Supports: draw.io XML (.drawio), D2 (.d2), Architecture YAML (.yaml), and architecture images (.png/.jpg) via Claude Vision API. Outputs a partial requirements YAML with confidence scores. Use before arch-req-merge t

Extract architecture requirements from documents (PDF, DOCX, MD, TXT). Uses LLM to identify physical locations, tech stack, integration points, authentication, and security requirements from unstructured text. Outputs a partial requirements YAML. Medium confidence — always verify

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

credo - Set up Claude Code with recommended workflows and plugins

dogma - Find and fix AI-typical patterns in code (reactive cleanup)

dogma - Sync documentation across README files and wiki articles

dogma - Interactively collect and apply CLAUDE rules to the project

dogma - Add ignore patterns to multiple locations at once

dogma - Run project-specific linting and formatting on staged files (non-interactive)

dogma - Create or update DOGMA-PERMISSIONS.md interactively (Git, File, and Workflow permissions)

dogma - Sanitize git history from Claude/AI traces and fix tracking issues

dogma - Intelligently sync Claude instructions from a source to the current project with interactive review

dogma - Check and fix version mismatches across all version files

Install GSD resources into the active Claude config dir (${CLAUDE_CONFIG_DIR:-$HOME/.claude}/get-shit-done/) (required before using other GSD commands)

Remove GSD resources from the active Claude config dir (${CLAUDE_CONFIG_DIR:-$HOME/.claude})

hydra - Remove already merged worktrees and their branches

hydra - Create a new Git worktree for isolated work

hydra - Safely remove a Git worktree

hydra - Show available commands and explain the concept

hydra - List all Git worktrees of the repository

hydra - Merge a worktree branch back into current branch

hydra - Start multiple agents in parallel across worktrees

hydra - Start an agent in an existing worktree

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.