LLM Mart Basic

Use when the user asks which phx-* command fits a task (review, plan,

Initialize plugin in a project — install Iron Laws, auto-activation rules,

Walk through the Elixir/Phoenix plugin commands, workflow, and features

Investigate Elixir/Phoenix bugs root-cause first. Reproduce failures,

Use this skill for a specific cloud workflow. Mention provider, trigger phrases, expected inputs, and when not to use it.

Plan who does each step of a task in this repo, on which model, at which effort: Haiku or Sonnet subagents for search, recon, and log-reading; code edits on Opus 5.5; start at medium effort and escalate on evidence (high, then xhigh, then Fable 5.1 for one stuck task); the orches

The ordered finish-line runner for any change in this repo — generators, then the asset-integrity refresh last on its own, then the full gate suite, then commit and push; use before declaring any change finished or whenever the stop hook reports uncommitted or untracked changes.

Re-verify and extend catalog/model-registry.json — the fail-closed model-name and reasoning-effort matrix scripts/model-policy.mjs validates against — via delegated Context7-backed research, orchestrator-owned registry edits, and the full validation chain; use when a policy check

The repeatable loop for watching a pull request until it is merged or closed, pairing webhook subscription with a scheduled self check-in so CI results, new pushes, and merge-conflict transitions are never missed; use when asked to watch, babysit, or autofix a PR, or right after

Route accounting questions to the narrowest specialist in the catalog. Use when you do not already know the specialist needed. Not for direct accounting answers; Maestro classifies, dispatches, and synthesizes only. Dispatches single agent for focused tasks, parallel team (max 3)

Multi-jurisdiction business combinations reference framework covering acquisition accounting, purchase price allocation, goodwill, and post-combination integration under ASC 805 and IFRS 3.

Multi-jurisdiction financial close cycle reference framework covering month-end, quarter-end, and year-end close. Provides regulatory filing deadlines by jurisdiction (SEC, EU TD, UK DTR, TSE/FSA, CSRC, SEBI, ASX, HKEX), record-to-report process steps, reconciliation standards, i

Multi-jurisdiction consolidation scope and intercompany elimination reference framework covering ASC 810 / IFRS 10 control models, VIE (Variable Interest Entity) primary beneficiary analysis, NCI measurement, equity method accounting (ASC 323 / IAS 28), intercompany eliminations

Multi-jurisdiction equity-based compensation reference framework covering stock options, RSUs, ESPPs, and performance awards under ASC 718 and IFRS 2.

Multi-jurisdiction fixed assets, depreciation, and impairment reference framework covering PP&E, intangibles, right-of-use assets, and goodwill under US GAAP and IFRS.

Multi-jurisdiction reference framework for foreign currency translation and remeasurement covering functional currency determination, ASC 830 / IAS 21 method selection, CTA in OCI, highly inflationary economy treatment, net investment hedge interactions, and multi-GAAP comparison

Multi-jurisdiction hedge accounting reference framework covering ASC 815 (US GAAP) and IFRS 9 hedge designation, effectiveness testing, OCI mechanics, IFRS 9 rebalancing, cost-of-hedging approach, discontinuation rules, embedded derivatives, and local GAAP treatments (German HGB

Multi-jurisdiction indirect tax and e-invoicing reference framework covering VAT/GST compliance and mandatory electronic invoicing mandates across EU, Brazil, India, Mexico, China, UK, and Australia.

Multi-jurisdiction lease accounting reference framework covering ASC 842 (US GAAP) and IFRS 16, with additional coverage of UK FRS 102 (2024 periodic review amendments effective 1 Jan 2026), German HGB, JGAAP (ASBJ Statement No. 34, effective FY beginning on/after 1 Apr 2027), CA

Multi-jurisdiction payroll accounting reference framework covering compensation expense recognition, employee benefits, pension/post-retirement obligations, and payroll tax compliance.

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.

CoalWash self-update — check for a newer version and offer to apply it, or set how updates are handled.

Create an AI skill from any source (URL, repo, PDF, video, notebook, etc.)

One-command skill creation and packaging for a target platform

Sync a scraping config's URLs against the live documentation site

Generate and run validation queries for the current change

Generate and run validation queries for the current change

Check code-intelligence prerequisites (ripgrep + a language server) and print install hints

Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion

Design concise overview, mechanism, or workflow figures as editable PowerPoint objects

Run the implement-review staged-change review loop

Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill

Run prun: parallel delegation fan-out on Agy workers (the session coordinates)

Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim

Vet the staged change: run the implement-review review loop (short alias)

Create space-efficient paper and proposal figures (HTML mockups, TikZ, or skia-canvas) from tool selection through LaTeX insertion

Design concise overview, mechanism, or workflow figures as editable PowerPoint objects

Run the implement-review staged-change review loop

Detect the work type (papers, proposals, code, figures, admin) and dispatch to the right domain skill

Run prun: parallel delegation fan-out on Agy workers (the session coordinates)

Audit a GitHub README and rewrite it with modern patterns for a scannable ten-second skim

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.