LLM Mart Basic

When the user wants to set up, optimize, or manage LinkedIn Ads. Also use when the user mentions "LinkedIn Ads," "LinkedIn Campaign Manager," "Sponsored Content," "Lead Gen Forms," "Sponsored Messaging," "Message Ads," "Conversation Ads," "Accelerate," "Classic ad set," "Audience

When the user wants to set up, optimize, or manage Meta (Facebook/Instagram) Ads. Also use when the user mentions "Meta Ads," "Facebook Ads," "Instagram Ads," "Meta Pixel," "Conversions API," "Advantage+," "lookalike audience," or "Meta retargeting." For landing pages, use landin

When the user wants to set up, optimize, or manage Reddit Ads. Also use when the user mentions "Reddit Ads," "Promoted Posts," "subreddit targeting," "Reddit advertising," or "Reddit communities." For organic Reddit, use reddit-posts.

When the user wants to set up, optimize, or manage TikTok Ads. Also use when the user mentions "TikTok Ads," "TikTok for Business," "TikTok Pixel," "Events API," "TikTok Spark Ads," or "TikTok video ads." For organic TikTok, use tiktok-captions.

When the user wants to run YouTube ads, set up TrueView or Bumper campaigns, or optimize video ad creative. Also use when the user mentions "YouTube ads," "TrueView," "Bumper ads," "YouTube Discovery," "video ads," "YouTube campaign," or "in-feed ads." For organic YouTube, use yo

When the user wants to analyze competitors for SEO, content, backlinks, or positioning. Also use when the user mentions "competitor analysis," "competitor research," "competitor keywords," "competitor backlinks," "link gap," "content gap," "competitor content," "competitive analy

When the user wants to optimize content for SEO—word count, H2 keywords, keyword density, multimedia, tables, lists. Also use when the user mentions "content length," "word count," "keyword stuffing," "H2 keywords," "keyword density," "tables," "bullet points," or "content struct

When the user wants to plan content for SEO, create content calendar, or build topic clusters. Also use when the user mentions "content strategy," "content plan," "topic clusters," "pillar content," "pillar page," "cluster articles," "editorial calendar," "content hub," "content

When the user wants to improve E-E-A-T, add trust signals, or optimize for expertise and authority. Also use when the user mentions "E-E-A-T," "E-E-A-T signals," "experience expertise authority trust," "author bio," "YMYL," "trust signals," "expertise signals," "authority signals

When the user wants to research keywords, find target keywords, or analyze search intent. Also use when the user mentions "keyword research," "keyword tool," "target keywords," "search volume," "search intent," "keyword difficulty," "topical map," "keyword clustering," "People Al

When the user wants to analyze backlinks, audit link profile, or identify link issues. Also use when the user mentions "backlink analysis," "backlink audit," "referring domains," "toxic links," "link profile," or "disavow file." For acquisition, use link-building.

When the user wants to build backlinks, acquire links, or improve off-page SEO. Also use when the user mentions "link building," "backlinks," "off-page SEO," "link acquisition," "outreach," "guest posting," "broken link building," "link outreach," "acquire backlinks," "how to bui

When the user wants to optimize the meta description or meta tag description. Also use when the user mentions "meta description," "meta desc," "page description," "SEO description," "search snippet," "SERP description," "description tag," "snippet for search," "meta description l

When the user wants to optimize for Featured Snippets, Position Zero, or snippet extraction. Also use when the user mentions "featured snippet," "position zero," "snippet optimization," "answer box," "definition box," "list snippet," "table snippet," "paragraph snippet," "PAA opt

When the user wants to optimize heading structure (H1-H6), fix heading hierarchy, or improve content structure. Also use when the user mentions "H1," "heading," "heading hierarchy," "content structure," "H2," "H3," "heading tags," "heading SEO," "multiple H1," or "heading structu

When the user wants to optimize images for search engines and performance. Also use when the user mentions "image SEO," "alt text," "image captions," "figcaption," "image optimization," "WebP," "lazy loading," "LCP," "image sitemap," "responsive images," "srcset," "image format,"

When the user wants to optimize internal linking, fix orphan pages, or improve link structure. Also use when the user mentions "internal links," "internal linking," "anchor text," "link equity," "internal linking strategy," or "orphan pages." For IA, use website-structure.

When the user wants to optimize meta tags other than title, description, Open Graph, or Twitter Cards. Also use when the user mentions "hreflang," "meta robots," "viewport," "charset," "canonical meta," "other meta tags," "meta robots noindex," "meta robots nofollow," "hreflang t

When the user wants to add or optimize Open Graph metadata for social sharing. Also use when the user mentions "Open Graph," "og:tags," "og:title," "og:image," "og:description," "Facebook preview," "LinkedIn preview," or "social share preview." For X (Twitter) link previews, use

When the user wants to add or optimize structured data (Schema.org, JSON-LD). Also use when the user mentions "schema," "structured data," "JSON-LD," "rich results," "rich snippets," "Google rich snippets," "featured snippet schema," "add schema to page," "missing structured data

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.

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.

Orchestrate the end-to-end academic research-to-publication workflow (research, write, integrity check, review, revise, re-review, finalize) with mandatory integrity gates and two-stage peer review. Invokes the alterlab-research-pipeline orchestrator.

Infrastructure-first security audit — secrets, supply chain, CI/CD, LLM/skill security, OWASP, STRIDE. Complements /audit-solana (program-level)

Security audit for Solana programs (Anchor/native)

Benchmark CU usage and compare against baseline for regression detection

Build web client application (Next.js, React, Vite)

Build Solana program (Anchor or native)

Build Unity project (WebGL, Desktop, or PSG1)

Initialize forked template — setup CLAUDE.md and remove config repo scaffolding

Version the Solana AI Kit config in git (un-ignores .claude/, CLAUDE.md, .mcp.json, .gitmodules and commits them)

Reproduce and debug a user-reported failing transaction against forked cluster state, mapping the failure back to source code

Deploy Solana program (devnet first, then mainnet)

AI-powered diff review for Solana-specific issues and code quality

Health check for the dev environment and solana-ai-kit config — read-only, with one exact fix-it command per failure

Memory consolidation — dedupe, contradiction-check, prune, and re-rank MEMORY.md + CLAUDE.md Project Learnings. Run after major refactors

Explain complex Solana/blockchain code with visual diagrams and step-by-step breakdowns

Generate TypeScript client from Solana program IDL using Codama or Anchor

Migrate from @solana/web3.js to @solana/kit

Plan feature implementation with technical specifications for Solana projects

Product quality review — first-time-user walkthrough, 8-dimension scorecard, prioritized fix roadmap. --harsh for the brutal roast variant

Profile compute unit usage per instruction in a Solana program

An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作

Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.

The go-to web for your AI coding agent — local-first search, fetch, crawl & research over MCP. No API keys, no cloud, $0/query. Public beta.

Transform and optimize your markdown documentation for Large Language Models (LLMs) and RAG systems. Generate llms.txt automatically.

合乎周礼：DeepSeek-powered Zhouli-style Chinese translator, web app, and distributable Skill package.

This is a fork of the https://dockbox.dev project I made

🏆 Curated, ranked list of AI agent harnesses (100+) — plus an MCP server, llms.txt & JSON so agents can recommend them too. Rescored weekly.

A Python framework for modular, self-contained skill management for machines.

ADHD — a skill for coding agents. Tree-of-thought with pruning, built on the Claude & Codex Agent SDK. Fans out parallel divergent thoughts under different cogn…

AI Agent 驱动的开源可自部署视频工作台：将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿，支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video producti…

DeepSeek Harness Desktop App: a local AI desktop workspace for DSH Sessions, projects, files, web research, plugins, and Office artifacts.

Autonomous Offensive Security, Bug Bounty & Red Teaming Agent Framework powered by Hermes Agent, specialized reasoning skills, and multi-model LLM orchestration…

⌥ Coding agent with the IDE wired in

Supercharge AI Agents, Safely

X (Twitter) Scraper API and X API Alternative. You do not need an official X developer account. You do not need to connect or use an X account for supported scr…

My AI Stand. Realtime by day, rewriting itself by night. Summon my AI superpower.

Open-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.

观澜 / Guanlan：AI Agent 的中文互联网研究、阅读与信源路由工具。

Mac Agent for macOS 26: the agentic AI harness for your Mac Desktop. Computer use, automation, scripting, coding, and more. Powered by 18+ providers across loca…

Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 28 languages via tree-sitter. Built for coding agents.