LLM Mart Basic

Run a portable sequential plan-work-verify-review-compound lifecycle.

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

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.

Create a multi-agent group chat with AG2 using configurable speaker selection patterns

Scaffold an A2A-compliant AG2 agent with server wiring, card settings, and skill definitions

Scaffold a new AG2 ConversableAgent with tool functions, system prompt, and LLM config

Create a tool function for an AG2 agent with type annotations, docstrings, and JSON return contracts

Create a sequential multi-agent pipeline where each agent processes and passes results to the next

Design a complete multi-agent workflow from a natural language description, selecting the right orchestration pattern

Follow RED-GREEN-REFACTOR cycle approach for test-driven development

Implement secure user authentication system

Generate and maintain project changelog

Setup mutation testing for code quality

Add and configure new project dependencies

Setup application performance monitoring

Implement property-based testing framework

Add a new entry to the project's CHANGELOG.md file following Keep a Changelog format

Preflight a repo before AI agents change files

Display all available development tools

Review and improve system architecture

Explore architectural decisions through systematic scenario analysis with trade-off evaluation and future-proofing assessment.

Enable bidirectional GitHub-Linear synchronization

Interview to flesh out a plan/spec

PiG (Pi in Go) is a faithful Go port of upstream Pi, the TypeScript codebase behind the Pi coding agent. It is a parity-bound translation, not a rewrite: upstre…

An AI Agent that lives in your pocket. Local-first and privacy focused.

Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.

Adaptive Test-time Learning and Autonomous Specialization

Prediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests

Knowledge Management for Humans and Agents

Open-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs…

DeepAgent Code: AI coding agent with persistent memory and control plane

Awesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.

CLI for Telegram — agent-friendly, daemon-based, with webhook event push.

AI deep-research agent that turns any question into a cited report: plans searches, reads real sources, verifies evidence. Self-hosted, multi-provider, Docker-r…

Event-stream AI Agent framework for building your persona bot 🍊

Give the agent a machine. Just not yours. Each AI coding agent gets its own isolated machine with root, Docker, and systemd - active defense detects and stops t…

Local Emperor-style AI agent with Vue WebUI, multi-provider LLMs, streaming chat, tools, skills, memory, and token telemetry.

Open-source AI reverse-engineering agent platform and MCP server for Ghidra, Frida, x64dbg and Rizin — automated PE/APK/binary analysis, CTF and malware researc…

"Never send a human to do a machine's job" - Open Source AI hacking agent

Prismer Cloud

My Personal Blog (Robotics)

Tau Coding Agent - like Pi, but twice as much

Open-source alternative to OpenAI Dots: self-hosted AI chat, tools, approvals, connectors, and computer tasks.