LLM Mart Basic

Deploy an AI legal operations agent for contract review, regulatory monitoring, policy enforcement, audit preparation, and document management. Complete Hermes configuration blueprint.

Deploy an AI marketing agent for SEO monitoring, campaign analytics, content performance, competitive intelligence, and social scheduling. Complete Hermes blueprint with cron and connectors.

Deploy an AI research agent for competitor monitoring, market intelligence, academic literature reviews, patent tracking, and news aggregation. Complete Hermes configuration blueprint.

Deploy an autonomous Hermes sales agent for lead qualification, pipeline management, outreach sequences, and daily CRM reporting. Complete configuration blueprint with cron schedules.

Deploy an AI customer support agent for ticket triage, knowledge base search, response drafting, SLA monitoring, and trending issue detection. Complete Hermes configuration blueprint.

Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..."

Orchestrate many forge runs at once: analyze which tasks collide on the same files, schedule the colliding ones sequentially, and run the rest in parallel worktrees at the right model tier and review depth. Use when the user runs /blacksmith-orchestrate or asks to ship several is

Brainstorm UI/UX changes into an approved design through interactive browser proposals rendered in the project's real design language. Option clicks assemble a response prompt copied to the user's clipboard. Use when the user runs /blueprint or wants to brainstorm, redesign, or v

Forge an issue, ticket, or PR into a shipped fix: propose a plan, get it approved, then implement, review, and refactor. Use when the user runs /forge or asks to investigate, fix, resolve, triage, or solve one. See Parameters for modifier flags.

Manage Todoist tasks, projects, labels, filters, sections, comments, reminders, and workspaces via the `td` CLI. Use when the user wants to view, create, update, complete, or organize Todoist items, or mentions tasks, inbox, today, upcoming, projects, labels, or filters.

Guide for adding new CLI commands or subcommands to todoist-cli. Use when implementing new SDK endpoints, adding subcommands to existing command groups, or extending CLI functionality.

Guide for adding new CLI commands or subcommands to todoist-cli. Use when implementing new SDK endpoints, adding subcommands to existing command groups, or extending CLI functionality.

Use when composing an ask_user_question round inside a workflow, or when a workflow skill names it at a question step. Shared norms for the tool — not a workflow, nothing to execute.

Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip th

Use FIRST when any new piece of work arrives — a request, feature, change, fix, question, or idea — before starting on it or choosing an approach. Not for continuing work already routed to a workflow skill.

Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced proj

Use whenever asked to set up, onboard, initialize, or spec a project — the front door when the workspace has no spec graph yet (brand-new or an existing codebase); also seeded by the app's Set-up-project card (/skill:setting-up-a-project). Not for feature work in an already-specc

Use when finished work needs to ship as a pull request, or when the ask is about a PR — creating one, bringing it up to date, adding screenshots, watching its checks, or addressing its review comments. Not for reviewing a PR you are not shipping.

Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instea

Use when a workflow step drafts or revises a spec artifact — a goal-and-requirements, an architecture, or a module SPEC — or when a workflow skill names it at such a step. The shared quality bar for specs — not a workflow, nothing to execute.

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.

Commit changes with festival traceability metadata

Create a new festival, phase, sequence, or task

List all festivals with their status and completion percentage

Get the next actionable festival task with full context

Show festival progression (in-progress tasks, roadmap, and dependency view)

Show festival progress and current status

Learn about the Festival Methodology (concepts, structure, rules, and workflows)

Validate festival structure and find issues

Turn one sentence of intent into a structured plan, sized correctly and planned through the loop

Canonical reference for invoking `agentii-investment-intelligence` slash commands across Claude Code, OpenCode, Goose, Codex, OpenClaw, and Claude Cowork. Frozen at v1.0 per the mode-addressability syntax + Round 4 Q12.

Operational KPI dashboard — headcount trends, utilization rates, backlog/book-to-bill

Revenue decomposition — segment breakdown, geographic split, product-line waterfall

Unit economics analysis — CAC/LTV estimation, churn inference, gross margin per unit

What-if scenario analysis — scenario tree construction (bear/base/bull), sensitivity to macro variables

Business model classification and structural analysis — product/service/platform, distribution channels, revenue composition, market sizing

Competitive landscape analysis — peer positioning, market-share dynamics, moat assessment

Earnings sentiment analysis — analyst estimates vs. guidance, sentiment trends, surprise history

Growth strategy analysis — organic/inorganic growth decomposition, pipeline analysis, execution tracking

Recent quarter performance analysis — quarterly P&L, margin drivers, EPS, sequential momentum

Risk analysis — regulatory, competitive, macro, and technology risk assessment

Open-source MCP servers for Latin American commerce — Pix, NF-e, banking, fiscal, logistics, and messaging across Brazil, Mexico, Argentina, Colombia, Chile, an…

pi coding agent in a technicolor web trenchcoat

Open-source AI Search Intelligence Platform — track, analyze, and improve AI visibility, citations, prompts, competitors, and content opportunities across ChatG…

Open-source toolkit for the QVeris capability routing network: CLI, MCP server, Python SDK, skills, and REST API docs for agents to discover, inspect, call, and…

⚡ The Complete X/Twitter Automation Toolkit — Scrapers, MCP server for AI agents (Claude/GPT), CLI, browser scripts. No API fees. Open source. Unfollow people w…

The AI agent that interacts with you in the real world.

Offline Codex Desktop migration for Windows and macOS.

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashbo…

Your smart, reliable, and friendly personal AI assistant.

The LLM Anti-Framework

A general-purpose AIGC video engine: script to finished film in one pipeline — dramas, ads, product videos, otome games, and more. | 通用 AIGC 视频引擎 —— 从剧本到成片一条流水线…

GTM agent for technical founders. Pay-per-result. Signed receipts. Two surfaces: terminal CLI + local web dashboard.

Desktop automation MCP server — computer use for any AI agent: control screen, windows, mouse/keyboard, and Chrome via Model Context Protocol (stdio)

DeepSeek Harness (dsh) Windows desktop client - bundled Node.js + dsh CLI, one-click launch

Open-source, real-time collaborative AI canvas - notes, mini-apps, and agents on one infinite board.

MCPSafari: Native Safari MCP Server for AI Agents

197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Po…

The AI agent with a wallet — spends USDC autonomously to get real work done. Apache-2.0, TypeScript.

The fastest browser for AI agents to run browser automation, built for sharing your logged-in browser state with your AI agents, like Codex or Claude Code, with…

Ouroboros — self-creating AI agent. Born Feb 16, 2026.