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.

hydra - Show detailed status of one or all worktrees

hydra - Live monitoring of background agents with status table

import - List all cached documentation

import - Search within cached documentation

import - Update cached documentation

import - Fetch URL (via Playwright if blocked) or copy local path to docs/

limit - Display all highscores for all plans

marketplace - Restore original plugin version from backup

marketplace - Install local plugin version for testing (backup original)

<claude-mem-context>

Aggregate SKMTC friction log entries into a review — cluster patterns, classify interventions, calculate convergence metrics, produce an action plan

<claude-mem-context>

Run a SKMTC retrospective on the current session — capture friction and wins to the friction log

CoalMine measurement dashboard — canary activity this session + rule-freshness status across the project's rules home

CoalMine self-update — check for a newer CoalMine version and offer to apply it, or set how updates are handled

CoalMine measurement dashboard — canary activity this session + rule-freshness status across the project's rules home

CoalMine self-update — check for a newer CoalMine version and offer to apply it, or set how updates are handled

CoalWash stats — current band, certain-fat reading, both break-evens, Memory-BMI (informational), pending-ask state, and the last run's trace for this project

CoalWash self-update — check for a newer version and offer to apply it, or set how updates are handled.

CoalWash stats — current band, certain-fat reading, both break-evens, Memory-BMI (informational), pending-ask state, and the last run's trace for this project

Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.

Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it.…

Curated systems, benchmarks, and papers etc. on memory for LLMs/MLLMs --- long-term context, retrieval, and reasoning.

:memo: Vimlike Modal Text Editor in Rust

CI-native security testing for MCP servers. Attack simulation, schema drift detection, and health scoring before agents depend on them.

Hermes Agent memory plugin/provider for scope-aware recall, SQLite truth, LanceDB semantic search, and hybrid retrieval.

For You Agent——AI 时代的个人随身数字人格。把你的模型、AI 账号、技能、提示词和工作方式，带到每一个 AI 工具里。

A coding agent: give it a prompt and it reads, writes, runs commands, and searches code in a loop until the work is done, using native tool-calling across OpenA…

A secure persistent personal agent server in Rust. One binary, sandboxed execution, multi-provider LLMs, voice, memory, Telegram, WhatsApp, Discord, Teams, and…

Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption

DeepSeek Harness Desktop (dsh-desktop). EAC: Embracing All Creation (揽尽万象). Bundled Node.js runtime with full dsh-CLI kernel, one-click startup, 10 built-in UI…

See your agent think. Zero-config observability & governance for 26 AI agent runtimes: Claude Code, Cursor, OpenAI Codex, GitHub Copilot, Gemini CLI, Cline, Ope…

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP…

Yet another coding agent harness, lightweight and written in go.

a coding Agent from pi. ∞ providers, sub-agents, hashline edits, and a permission gate

Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting…

🧠 Leon is your open-source personal assistant.

The Station, an open-world multi-agent environment that models a miniature scientific ecosystem.

The Frontend Stack for Agents & Generative UI. React, Angular, Mobile, Slack, and more. Makers of the AG-UI Protocol

VelaTerm = iTerm2 + Codex, The Best Terminal for AI Coding