LLM Mart Basic

Use when building or shipping a Manifest V3 browser extension and hitting its quirks — service worker dying and losing state, permission warnings, a Chrome Web Store rejection, content-script/worker/popup messaging, or an MV2-to-V3 migration. NOT a generic web app (that is `nextj

Use when a spec exists and must be de-risked before planning — hunt its ambiguities, unstated assumptions and edge cases, ask the few build-changing questions, bake the answers back into the spec. The rsc SDD gate between `specify` (writes the spec) and `plan` (designs the build)

Use when running a ClickHouse server for high-volume OLAP: choosing a MergeTree engine and ORDER BY/PARTITION BY keys, ingesting billions of event/log/metric rows, pre-aggregating with materialized views, or fixing a query that scans instead of pruning. NOT in-process file analyt

Use when a deal closed or a user signed up and the first 30 days need an activation plan: sales→delivery handoff, one verifiable activation event, kickoff, and a 30/60/90 or day-0→14 plan with owners, dates and a measurable exit. NOT reactive ticket triage (that is `customer-supp

Use when working on Cloudflare's edge platform — wrangler.jsonc bindings, choosing between D1/KV/R2/Durable Objects/Queues, deploying a Worker or SPA via Static Assets, or designing around a Workers runtime limit. NOT generic CI/release (that is `deployment`), NOT Next.js framewo

Use to judge a concrete diff, branch, or GitHub PR on its own merits with no rsc-SDD spec/plan chain to key off — the spec-less giving pass behind /code-review: only findings you can defend, one verdict, read-only unless --comment or --fix. NOT the SDD gate keyed to 02-DOCS/wiki/

Use when you land in an unfamiliar or inherited codebase and must get productive fast: a breadth-first map of entry points, request flow, module ownership, hidden side effects (cron, webhooks, workers) and churn hotspots, committed as CODEBASE-MAP.md. NOT a deep audit of one modu

Use when writing a cold email or LinkedIn DM to a stranger and its cadence: first-touch copy under a word ceiling, 4-7 step bump sequences, per-inbox volume and warm-up limits, the compliant opt-out footer. NOT SPF/DKIM/DMARC setup (that is email-deliverability), NOT sourcing the

Use when building or running a persistent two-way community space — Discord, Telegram, Circle: platform choice, structure, onboarding, native→bot→human moderation, rituals, growth loops, health metrics. NOT churn of paying product customers (that is `retention`), NOT broadcast em

Use when an already-named set of rivals is watched on a cadence — pricing, features, positioning and changelog diffed into a maintained tracker plus an append-only, classified change log. NOT sizing the market or choosing who the rivals are (that is `market-research`), NOT one-of

Use when scoping which regulatory frameworks bind a business — SOC 2, ISO 27001, HIPAA, PCI DSS, EU AI Act, DORA, NIS2 — building a control register with owners and evidence, or standing up the cadence that keeps it audit-ready. NOT drafting privacy-policy/ROPA/DPA or ToS text (t

Use when building one shared Compose UI in Kotlin across Android, iOS, and desktop — commonMain @Composables, expect/actual, source-set placement, native interop, multiplatform ViewModel/navigation/Koin. NOT a single-platform native build (that is kotlin-android / swift-ios), and

Use when setting or amending a project's non-negotiables — stack canon, quality bars, conventions, security/a11y floors — as numbered, testable rules later phases obey. First rsc-sdd phase; writes 02-DOCS/wiki/sdd/constitution.md. NOT a feature spec (that is `specify`), NOT the t

Use when a content operation needs a SYSTEM: a dated editorial calendar built top-down from pillars, plus the stage gates, briefs, WIP limits and 1:10 atomization plan that move each slot to publish-ready. NOT writing the pieces (that is `article-writing`), NOT publishing them (t

Use when drafting or reviewing business contracts and clauses in plain language — NDAs, MSAs, SOWs, contractor agreements, risk boilerplate (liability caps, indemnity, force majeure, termination, IP) — or redlining a counterparty's paper. NOT consumer Terms of Service (that is te

Use when self-hosting apps and databases with Coolify on a VPS you own — install, first-admin lockdown, Git-to-deploy (Nixpacks/Dockerfile/compose), managed Postgres/Redis, scheduled S3 backups, domains + auto-SSL. NOT a PaaS someone else runs (that is `railway`), NOT sizing/hard

Use when metering and capping AI or cloud app spend — tokens read from the response `usage` object, priced off a dated rate table, ledgered per user/tenant/feature, with alerts and a hard cap before the bill. NOT cash runway (that is `finance-ops`), NOT cost-per-unit margin (that

Use when turning "I want to teach X" into a defensible course skeleton — measurable outcomes (Bloom + ABCD), assessment that proves each one, sequenced modules, and an outcome×module×assessment matrix — for a workshop, bootcamp, cohort or onboarding track. NOT making one concept

Use when lesson or course content is correct but forgettable and a concept has to LAND: profiles the learner, breaks the blocking false belief, then rebuilds it as epiphany story → named model → grounded analogy → proof → so-what. NOT outcomes, assessment or module order (that is

Use when writing, reviewing, modernizing, building, or debugging C++ - RAII and resource lifetime, smart-pointer ownership, move semantics and the Rule of Zero/Five, target-based CMake with FetchContent, and killing undefined behavior with ASan/UBSan/TSan plus clang-tidy. NOT bor

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.

Intelligent issue resolution with multi-agent debugging, root cause analysis, and verified fix implementation

Scaffold a TypeScript project (Next.js, React with Vite, Node.js API, or library) with pnpm, testing, and dev tooling

Build AI assistant application with NLU, dialog management, and integrations

Create LangGraph-based agent with modern patterns

Optimize prompts for production with CoT, few-shot, and constitutional AI patterns

Run the eval-gated fine-tuning lifecycle end to end — eval harness, method selection, data, environment, training, checkpoint gate, export

Re-gate an existing fine-tuned checkpoint against the current eval harness and export it on PROMOTE

Orchestrate specialized agents to build a production ML pipeline from data analysis through training, deployment, and monitoring

Quick gallery search. Use when user runs /meigen-ai-design:find with keywords to browse inspiration.

Quick image generation. Use when user runs /meigen-ai-design:gen with a prompt. Skips intent assessment, generates directly.

Orchestrate cross-platform feature development across web, mobile, and desktop with API-first architecture

Set up monitoring and observability with Prometheus metrics, Grafana dashboards, distributed tracing, log aggregation, and alerting

Implement SLOs with SLI selection, error budgets, burn-rate alerting, dashboards, and reporting

Run an AI-assisted code review that combines static analysis tools with AI review of security, performance, and architecture

Coordinate specialized review agents in parallel or in sequence and synthesize their findings into one code review

Full quality certification with badge

Compare two skills head-to-head

Evaluate a plugin or skill for quality

Verify every receipt in ./receipts/receipts.jsonl against the signer's public key. Detects tampered or malformed receipts across the audit trail.

Verify a single Ed25519-signed receipt file against the signer's public key. Returns exit 0 if valid, 1 if tampered, 2 if malformed or the key is missing.

VCP 部署在 AI 模型 API 与前端应用之间，是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架，将原本“无状态、无记忆、无工具调用能力”的大语言模型，彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。

The open source Unity Dev Agent

Context is yours. Agents are replaceable. Orbital — a project agent that turns your context into assets.

Self-hosted search API + MCP server for AI agents. Bundles SearXNG. Zero API keys, one-command deploy. Open-source alternative to Tavily, Exa, and Serper.

🛡️ Free open-source AI-powered security terminal & vulnerability scanner (CVE, SBOM). Supports SSH, SFTP, RDP, VNC, Serial, and 12+ autonomous AI agents (DeepS…

Watch, approve and steer your coding agents from your phone.

MARVIS-Agent: all-purpose credit risk agent for model development, validation, data processing, feature engineering, and strategy workflows.

TikTok e-commerce video generation, replication, and analysis SKILL

小红书/抖音/快手/视频号/B站 自媒体账号体检+爆款拆解工具。扫同赛道找对标、拆爆款为什么爆、诊断为什么没人看，顺手出可粘贴仿写初稿。支持带货电商模式。支持codex, claude code, workbuddy

Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.

A power user focused interface for LLM base models.

Outsource your understanding. Capture every human-AI decision as a step in a trajectory; grade trajectories retroactively when outcomes land (deal closed, sprin…

The open-source AI research workbench for scientific research and agent workflows. Local-first, model-agnostic desktop app with extensible skills, MCP tools and…

🤖 Taskade MCP · Official MCP server and OpenAPI to MCP codegen. Build AI agent tools from any OpenAPI API and connect to Claude, Cursor, and more.

A block-based content engine and bilingual blog backend for Laravel Gutenberg-style editor, media library, post templates, roles, and an AI writing assistant,…

ACRYL - Agent Context Relay Yielding Lifecycles. One persistent workspace, one canonical context, any coding agent.

Okou connects to the tools your team already uses and does the work — across marketing, sales, engineering, and operations, under your control.

Open-source agent-native visual production workspace where humans and coding agents edit the same live canvas — local-first, BYOK image/video models.

Persistent memory extension for pi with daily logs, scratchpad, and optional qmd‑powered semantic search.

Hermes Agent CN desktop app, Windows-First, built with Tauri, Typescript and Rust. Isolated Hermes Agent core insides.