LLM Mart Basic

Audit frontend code for internationalization readiness — externalized ICU MessageFormat strings, Intl-based date/number/currency/plural formatting, correct lang/dir attribute propagation, and RTL-safe CSS logical properties — before translation vendor engagement, with CLDR plural

Review JavaScript/TypeScript for event-loop and microtask/macrotask ordering correctness, unhandled Promise rejection paths, DOM event-listener and timer cleanup, and race-condition risk in rapid-repeated-async UI patterns, tracing actual browser scheduling semantics rather than

Inventory the hidden behaviors in a legacy jQuery/Backbone-era codebase — implicit global event delegation, direct DOM mutation outside any render cycle, plugin side effects, ad-hoc accessibility shims, and unsanitized HTML string building — that a mechanical framework port would

Reviews micro-frontend/module-federation boundary contracts for shared-dependency versioning safety, runtime isolation, and ownership clarity before adoption or extension of a distributed frontend architecture.

Reviews monorepo task-graph configuration (Turborepo tasks/caching, Nx task pipelines) alongside dependency and lockfile governance (pnpm catalogs, npm overrides, lifecycle-script risk) to prevent false-green CI from stale cache reuse and unpinned supply-chain exposure.

Statically review Next.js App Router Server/Client Component boundaries and Server Action data mutations for correct data-fetching placement, bundle-leak risk, and authorization-trust integrity, escalating client-trusted authorization to a security finding rather than a style not

Statically review Next.js App Router route segments and fetch() calls for rendering-mode (static/ISR/dynamic) and Data-Cache misconfiguration, escalating cross-user data leakage to a security finding rather than a performance nit.

Statically review Next.js middleware, Server Actions, next.config.js, and environment-variable files for four documented server-side defect classes -- middleware matcher exclusions that silently skip auth on Server Functions, Server Actions missing allowedOrigins CSRF protection,

Statically review Nuxt 3/4 full-stack code for private secrets exposed via runtimeConfig.public/NUXT_PUBLIC_* env vars, useState/module-scope cross-request state pollution in Nitro, server-route SSRF via $fetch/ofetch with blind useRequestHeaders/credential forwarding, NuxtPayloa

Statically review payment-page frontend code for PCI-DSS-relevant defects in the browser/DOM slice only — raw PAN collection in self-controlled inputs instead of Stripe hosted fields, card data persisted client-side or to analytics, raw card data POSTed to a first-party endpoint,

Review frontend analytics instrumentation and A/B or multivariate experiment configurations for event-schema correctness, sample-ratio-mismatch risk, statistically valid stopping rules, and consent-gated privacy compliance before shipping a tracking or experiment change.

Validates installability against W3C manifest criteria and tests real offline navigation behavior end to end, rejecting a manifest-schema-valid but practically non-installable or non-functional-offline PWA.

Statically review React component trees for composition, prop-interface, and state-placement defects (God-components, prop drilling, overbroad context, hook-rule violations) against React's own composition guidance, producing ranked file:line findings.

Statically review React Server Components code for data leaks across the server-to-client serialization boundary — secrets passed as props to Client Components, server-only modules missing the `server-only` guard, `use server` actions with no authorization check, non-public envir

Statically review useState/useEffect/useReducer call sites against React's documented "You Might Not Need an Effect" anti-pattern catalog, plus race-condition and stale-closure detection via dependency-array and cleanup-function analysis, producing ranked file:line findings.

Reviews route-tree structure, loader/action placement, code-splitting boundaries, and navigation-blocking/focus-management behavior in React Router and Next.js applications for correctness, server-side security enforcement, and accessibility conformance on route transitions.

Reviews service-worker route-matching and caching-strategy choices (precache vs. cache-first vs. network-first vs. stale-while-revalidate) against request type and security sensitivity, rejecting uniform blanket strategies and flagging authenticated/PII responses cached in the Ca

Diagnoses hydration-mismatch errors and streaming/Suspense-boundary structural issues to their specific root cause — non-deterministic rendering source, missing error boundary, serial data-fetch waterfall, or premature auth-unchecked streaming — grounded in the exact React/Next.j

Reviews whether data is correctly classified as server state, client state, or derived state, and whether the resulting store/cache design (query keys, invalidation, optimistic-update rollback, SSR instantiation, selector shape) avoids duplication, stale-data bugs, and unnecessar

Statically review SvelteKit form actions, load functions, hooks, and templates for CSRF origin-check bypass (checkOrigin/trustedOrigins), unauthenticated sensitive-data returns from load(), auth guards confined to +layout.server.js without an enforced parent()/hooks check, insecu

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.

Extract facts from meetings and update your knowledge base — person profiles, chronological log, and index. Use when the user asks "ingest my meetings", "update my knowledge base", "extract facts from meetings", "sync meetings to wiki", "backfill knowledge", or wants their PARA/Obsidian/wiki profiles updated from conversation data.

Health-check your meeting knowledge for contradictions, stale commitments, and decision conflicts. Use when the user asks "any conflicts in my meetings", "check for stale action items", "lint my meetings", "consistency check", "are there contradictions", or wants to audit their decision history.

List recent meetings and voice memos. Use when the user asks "what meetings did I have", "show my recent recordings", "any meetings today", "list my voice memos", or wants an overview of their meeting history. Also use when they need to find a specific meeting by browsing rather than searching.

Act as the user's live meeting sidekick inside the current terminal agent session. Use when the user explicitly asks you, the terminal agent, to watch a meeting, follow the live transcript, answer during the call, offer strategist thoughts, silently watch for risks, or track decisions. Do not use this skill to start or control the separate Minutes Coach HUD; explicit Coach or HUD lifecycle requests belong to minutes-copilot, and an ambiguous request such as "coach me live" requires one short surface clarification.

Self-coaching analysis of your own behavior across meetings — talk-time ratio, filler words, hedging language, monologue length, energy patterns, and (when meetings are tagged via /minutes-tag) what your behavior in winning meetings looks like vs losing ones. Use this whenever the user says "how did I do", "review my last meeting", "mirror", "self-review", "show my patterns", "coach me", "where am I weak", "talk time", "am I improving", "what do I do in meetings I win", "feedback on me", or asks for any kind of personal feedback on their own meeting behavior. This is the rare skill that gives the user a mirror to their own habits — surface it whenever they show curiosity about their own performance, even if they don't use the word "mirror".

Add a note to the current recording or annotate a past meeting. Use whenever the user says "note that", "remember this", "mark this as important", "add a note about", "annotate the meeting", or wants to capture a thought during or after a recording. Plain text input — no markdown needed.

Interactive meeting preparation — builds a relationship brief and talking points before a call. Use when the user says "prep me for my call with", "I'm meeting with X", "prepare me for", "what should I bring up with", "meeting prep", "get ready for my call", or wants to review history with someone before a meeting.

Generate a daily digest of today's policy-authorized meetings and voice memos — key decisions, action items, and themes across available recordings. Use when the user asks "recap my day", "what happened in my meetings today", "daily summary", "what did I discuss today", "any action items from today", or wants a consolidated view of the day's conversations.

Start or stop recording a meeting, call, or voice memo. Use this whenever the user says "record", "start recording", "capture this meeting", "stop recording", "I'm in a meeting", "take notes on this call", or wants to transcribe live audio. Also use when they ask about recording status or want to know if something is being recorded.

Draft user-facing Minutes release notes for a version from the commit range, recent GitHub releases, and the repository release checks. Use when the user asks to write, generate, prepare, revise, or review release notes or a changelog for a Minutes version.

Search past meeting transcripts and voice memos for specific topics, people, decisions, or ideas. Use this whenever the user asks "what did we discuss about X", "find that meeting where we talked about Y", "what did Alex say", "did we decide on", "what was that idea about", or any question that could be answered by searching their meeting history. Also use for "do I have any notes about" or "check my meetings for".

Guided first-time setup for Minutes — download whisper model, create directories, configure audio input. Use when the user says "set up minutes", "install minutes", "first time setup", "configure minutes", "get started with minutes", "how do I start using minutes", or when verify shows missing components.

Lightweight outcome tagging for meetings — won, lost, stalled, great, or noise. Use whenever the user says "tag this meeting", "mark that as a win", "that one was a loss", "tag yesterday's call as stalled", "mark this great", "that meeting was noise", "label that meeting", or any time they describe a meeting outcome in passing. Tagging takes 5 seconds and unlocks /minutes-mirror correlation analysis — the more meetings get tagged, the smarter mirror gets at telling the user what behavior patterns lead to wins. Surface this skill any time the user mentions a meeting result, win, loss, or wasted time.

Verify that Minutes is properly set up and working — model downloaded, mic accessible, directories exist, no stale state. Use when the user says "is minutes working", "check my setup", "verify minutes", "test recording setup", "why isn't minutes working", "minutes health check", or after running setup for the first time.

Analyze a product walkthrough, bug report video, Loom, or ScreenPal using Minutes transcription plus visual review. Use when the user wants a recorded demo or bug clip turned into a durable brief with transcript, key frames, issues, and next steps.

Weekly meeting synthesis — themes, decision arcs, stale commitments, and what deserves your attention next week. Use when the user says "weekly review", "what happened this week", "weekly summary", "recap my week", "any outstanding items", "week in review", or at the end of a work week.

Search agent history or trace code to its original agent session

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

Generate a custom checklist for the current feature based on user requirements.

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

Conduit — native SwiftUI iOS client for Hermes Agent

一个现代化的可视化规则引擎平台，用于编排复杂的 AI 工作流。在无限画布上设计、测试和部署 AI 流程——无需编写代码。结合 flowgram.ai 的能力与 Java 服务端，提供生产级工作流管理。在此之上提供AI Agent / Copilot的助手编排能力。

Job application tracker and AI-powered job search assistant. Helps job seekers manage their search journey with AI resume review, job matching, task logging, an…

📝 Markdown and HTML renderer for Svelte 5 — built for streaming AI agent output from Claude Code, ChatGPT, and agentic workflows. XSS-safe defaults, token cach…

ServiceNow MCP server: 500+ tools and 26 AI capabilities for any AI (Claude, ChatGPT, Gemini, Cursor, Copilot). Multi-transport (stdio, SSE, HTTP), A2A, dynamic…

Free crypto news API - real-time aggregator for Bitcoin, Ethereum, DeFi, Solana & altcoins. No API key required. RSS/Atom feeds, JSON REST API, historical archi…

Build production-ready AI agents in both Python and Typescript.

From agent user to agent builder: build a Claude Code-style coding agent from scratch in Python: 8 articles, 4 videos, one codebase

🪁 A lightweight, modern Kubernetes dashboard that unifies multi-cluster and resource management, enterprise-grade user governance (OAuth, RBAC, and audit logs)…

Stateful runtime management for LLM agents—inject, manipulate, and retrieve Python objects across turns.

AgentCall lets AI Agents join meetings with voice, video & screen-share to build together. Supports Google Meet, Teams, Zoom (Beta)

Kition brings Markdown, DataTable, WhiteBoard, a tool-using AI agent, browser research, and visual workflows into one desktop workspace.

IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.

A powerful Model Context Protocol (MCP) server providing comprehensive Google Maps API integration with LLM processing capabilities.

Turn your Claude Pro/Max subscription into an OpenAI-compatible API for your IDEs and devices — LAN auth, per-key quotas, response cache, disciplined cli.js ali…

Paw Work - selection-first web agent for Chrome: select on the live page, describe the outcome, take away an editable office file. BYOK, sandboxed, no server.

基于 AI Agent + MCP 工具链 + 渗透 Skill 编排， 配合大语言模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。

Lexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台

First AI Journey for DevOps - with comprehensive learning paths, practical tips, and enterprise guidelines

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-…