LLM Mart Basic

Use when someone wants to add, write, create, or scaffold new Playwright end-to-end tests for a page, flow, form, component, uncovered route, or first-project setup. The skill analyzes coverage gaps, explores live pages only on local/disposable or externally isolated approved non

Catalog-only control for a preregistered e2e-reviewer ablation.

Use this skill to generate new Playwright end-to-end tests from scratch — for a page, a user flow, a form, or a component — taking them from zero to reviewed, passing specs. Reach for it whenever someone wants to add, write, create, or scaffold Playwright E2E coverage, fill cover

Use when a Cypress end-to-end test has already run and failed and the user wants the root cause and a concrete fix. Trigger on a failing Cypress spec, Timed-out-retrying command, unresolved selector, cy.intercept alias or request race, suite-breaking hook, retry-only flake, hydra

Use when reviewing Playwright or Cypress E2E specs, Page Objects (POM), PRs, pull requests, patches, diffs, or changed test files — asked to review tests, audit test quality, or find weak, flaky, or silently-passing tests; when tests pass CI but prove nothing or miss bugs; when a

Use when a Playwright end-to-end test has already run and failed and the user wants the root cause and a concrete fix. Trigger on a failing Playwright spec, TimeoutError, broken or ambiguous selector, post-deploy suite failure, retry-only flake, hydration or timing race, or a pas

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

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

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

Plural alias for task status, pause, prompts, recovery, and ignore

Verify that the autorun plugin command surface is loaded

Tmux session management - create, list, cleanup isolated sessions, short for /ar:tmux

Tmux session management - create, list, cleanup isolated sessions

CLI testing in isolated tmux sessions, short for /ar:ttest

CLI testing in isolated tmux sessions

Graceful stop - finish current task then stop (short for /ar:stop)

Set AutoFile policy to ALLOW — permit creation of new files without justification

Refresh git commit guidelines before staging changes

Set AutoFile policy to FIND — restrict edits to existing files only

Start an autorun task with three-stage verification (initial → critical review → final verification)

Refresh the universal system design philosophy before designing or reviewing code

Show the current AutoFile policy and any active autorun state

Extract text from PDF files or directories to markdown

Trigger: `/ship` or "ship it" or "deploy to production"

Suppress 5-question enforcement for rapid sessions

Check a Dutch address for KPN outages and report what connectivity is available there

Find the KPN business-mobile contract for a lost or stolen phone and block its SIM after confirmation

Run the SkillOpt-Sleep cycle with the handoff backend — no API subprocess; this session answers the engine's model calls via prompt/answer files, in isolated fresh-context subagents

Run or manage the SkillOpt-Sleep self-evolution cycle (review past sessions, replay tasks through a selected backend, consolidate validated memory + skills, or schedule nightly runs)

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.