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

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.

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.

Sanctioned lane for non-behavioral work — docs-only edits, dependency bumps, reverts. Type-scaled gates; no TDD demanded of prose.

{{SKILL_ENTRY:post-merge-cleanup}}

Show the codeArbiter command catalog — the public command list and what each routes to.

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Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.

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Verify the active host install, package, command ownership, enforcement{{IF:pi}}, wrapper self-test, and active-dispatch coverage gap{{ELSE}}, and harmless live-fire probe{{END}}. Read-only.

Start a feature: brainstorm a spec, get it approved, then drive it test-first through the pipeline. The one entry to implementation.

Fix a confirmed bug: a failing regression test first, then a minimal fix, then the rest of the tdd gates.

Opt this repo into codeArbiter — scaffold the root-level .codearbiter/ state store.

Read-only 3-metric governance glance — override rate, small-lane rate, sprint low-confidence ratio — each with a trend arrow vs. the prior 20-commit window.

Sanctioned, logged bypass of a gate or hard rule — one audit line, then proceed.

{{SKILL_ENTRY:finishing-a-development-branch}}

Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.

Trim transcript clutter to extend session lifetime — analyze, prune a copy, or toggle the after-each-turn service. Dry-run by default; gains land at resume/compaction, not the current turn.

{{SKILL_ENTRY:decision-variance}}

AI assistant in Telegram that remembers everything and helps you run your life. Self-hosted in one command.

知更 — 本地 AI 的上下文与记忆层。Mac 上用语音输入、情境代回并调度 Codex / Claude Code；iOS 正在成为随身记忆终端和本地 Agent 遥控器。Local-first · BYOK.

Agent skill that turns Claude Code / Codex into a motion-design studio for voiceover-driven explainer videos — word-level voiceover sync, 78 motion recipe cards…

CoCo Super Intelligence is the orchestration layer that turns Claude Code, Cursor, or Codex into an engineering department: a routed advisory board, 185 skills,…

Deploy AI agent teams at scale without compromise

大师.skill — 输入行业，自动调研 6 轨[行业大佬 / 工具地图 / 工作流 / 知识正典 / 信息源 / 术语标准] → 提炼为可运行的行业 Master OS skill；装到任意 Claude Code / OpenClaw / Codex / Hermes agent 即让其进入「这一行的资深人」模式。…

Notion MCP server for Claude, Cursor, ChatGPT & Claude Desktop. Connect AI agents to Notion via Model Context Protocol — pages, databases, blocks, comments, fil…

Hook-based token compressor for 5 AI CLI hosts (Claude Code, Copilot CLI, OpenCode, Gemini CLI, Codex CLI). Up to 95% bash compression, signature-mode for code…

Model-neutral agent desktop/runtime for private, enterprise, and OpenAI-compatible / Anthropic-compatible model API. Tested on DeepSeek, Qwen, Kimi, GLM models.…

AI agent skill for end-to-end hotel search and booking—compare live rates across leading OTAs and hotel suppliers, verify availability, book stays, and manage r…

More than just Karpathy’s LLM Wiki, 100% local with Ollama. Drop Markdown notes → AI extracts concepts → your Obsidian wiki auto-links and grows. Zero sharing.…

Claude Code Guide - Setup, Commands, workflows, agents, skills & tips-n-tricks from beginner to power user!

A magical tool that changes how you use Agents. Install once — every Agent automatically discovers and uses all your MCP tools, and saves your tokens along the…

Open-source 24/7 Cowork app for OpenClaw, Hermes, Claude Code, Codex, OpenCode and 20+ more CLI Agent | Customize your assistants | Team them up｜Star if you lik…

AgenticX is a unified, production-ready multi-agent platform — Python SDK + CLI (agx) + Studio server + Machi desktop app. Features Meta-Agent orchestration, 15…

Query, provision and operate Cloud, SaaS, API and Model Context Protocol (MCP) resources through a unified SQL-based framework for humans and AI agents.

Open-source AI job search: scan job portals, evaluate listings into a structured A-H report with a global 1-5 score, tailor your CV, track applications — runs l…

A self-healing scraper for hostile sites: broken selectors repair themselves, browser rendering kicks in when needed, and a coherent identity layer (Chrome TLS…

Lightweight AI-native workflow builder for individuals and small teams — describe your idea in natural language, get a runnable workflow on a visual canvas, pub…

Minimal AI coding agent (~1,000 lines of Python) inspired by Claude Code. Works with any LLM. Think NanoGPT for coding agents. Formerly NanoCoder.