LLM Mart Basic

Multi-jurisdiction reference framework for corporate capital allocation, investment appraisal (NPV, IRR, MIRR, payback, profitability index), cost of capital (WACC, CAPM, hurdle rates), M&A valuation methods (DCF, trading comparables, precedent transactions, accretion/dilution),

Multi-jurisdiction reference framework for debt and capital structure advisory — optimal capital structure theory (M&M, trade-off, pecking order), leverage and credit metrics, debt instruments, covenant analysis, refinancing, WACC optimization, Basel III/IV capital requirements,

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

Reference framework for financial planning and analysis (FP&A) covering driver-based budgeting, rolling forecasts, zero-based budgeting (ZBB), scenario and sensitivity analysis, budget-versus-actual variance analysis, long-range planning (LRP), integrated P&L/balance sheet/cash f

Multi-jurisdiction reference framework for OECD transfer pricing (arm's length principle, five TP methods, BEPS Action 13 documentation, CbCR) and OECD Pillar Two GloBE rules (IIR, UTPR, QDMTT, ETR computation, SBIE carve-outs, safe harbors, deferred tax divergence under IAS 12 v

Multi-jurisdiction reference framework for corporate treasury operations, cash and liquidity management, FX and currency risk, hedge accounting qualification (ASC 815 / IFRS 9), FX translation (ASC 830 / IAS 21), Basel III LCR/NSFR, Dodd-Frank and EMIR derivatives reporting, and

Variance decomposition framework and SEC Regulation S-K Item 303 MD&A commentary guidance for FP&A and corporate finance teams. Provides driver decomposition methodology (Volume/Price/Rate/Mix/One-Time), MD&A structural requirements with regulatory citations, restatement-risk tri

Multi-jurisdiction reference framework for working capital management — cash conversion cycle (CCC) optimization, accounts receivable management (collections, credit policy, aging analysis, factoring, invoice discounting, AR securitization, ASC 860 / IFRS 9 SPPI derecognition), a

Pair every cloud spend value with a kgCO2e estimate by region and service category for CSRD and SEC climate disclosure. Input is region, service category, and dollar value; output is paired kgCO2e with confidence label (vendor-published, third-party, or estimated) and source cita

Fetch live per-token, per-image, and per-GPU-hour prices for foundation models across Anthropic, OpenAI, Google, AWS Bedrock, Azure OpenAI, OCI Generative AI, and Vertex AI. Supports single-model lookup and comparative multi-provider tables. Every price is labeled with source URL

Fetch live public prices and build cost estimates for AWS, Azure, OCI, Scaleway, Gandi, Alibaba Cloud, and Tencent Cloud using each provider's public pricing API or official documentation. Supports live-environment cost analysis and prototype cost planning. Currency defaults to U

Normalize vendor-specific billing rows (AWS CUR, Azure Cost Management, GCP Billing Export, OCI) into FOCUS v1.2 columns from user-pasted CSV or JSON input. Refuses to invent column values not derivable from the input. No credentials accepted; operates on user-supplied data only.

Emit pod CPU and memory request/limit recommendations from user-pasted p50, p95, and p99 utilization metrics over a 7-14 day window. Outputs recommended requests at p95 plus 20% headroom, limits at p99 plus 30%, estimated monthly savings, and Karpenter consolidation eligibility f

Use this skill when reviewing FluxCD Kustomization, HelmRelease, GitRepository, HelmRepository, or OCIRepository resources. Trigger when the user asks whether a Flux configuration is safe for production, whether SOPS encryption is required, whether prune is safe on a given worklo

Apply an elevated review pass to AI or LLM-generated frontend code changes, checking specifically for hallucinated framework APIs, slopsquatted or non-existent dependency names, unsanitized dynamic-HTML sinks, and missing accessibility semantics before the diff is merged.

Statically review Angular component and service architecture for correct Signals usage (signal/computed/effect boundaries and purity), appropriate change-detection strategy (OnPush vs default), and service/DI boundary design, grounded in Angular's own Signals, change-detection, a

Statically review Angular SSR bootstrap configuration and component templates for hydration-mismatch risk (NG0500-class errors), unjustified ngSkipHydration usage, and direct-DOM-manipulation patterns that bypass Angular's template-owned DOM model, grounded in Angular's own hydra

Statically review Angular templates and components for injection via DomSanitizer bypass calls (bypassSecurityTrustHtml, bypassSecurityTrustUrl, bypassSecurityTrustResourceUrl), unsanitized [innerHTML] bindings, and dynamically bound iframe security attributes such as [attr.sandb

Reviews frontend-to-backend API contracts — BFF route handlers and direct backend calls — for data-minimization, server-side object-level authorization enforcement, error-shape leakage, CORS misconfiguration, and backward-compatible versioning before they ship.

Audit JS/CSS/HTML feature usage against the project's declared Browserslist/supported-browser matrix using Baseline and caniuse status data, flag unguarded non-Baseline usage, and verify feature-detection or polyfill fallback coverage, with per-feature caniuse/Baseline lookups lo

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.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

Generate a typed client from an Anchor or Shank IDL (Codama or Anchor TS)

Migrate TypeScript from @solana/web3.js 1.x to @solana/kit

Plan a Solana feature before coding: accounts, PDAs, instructions, risks, tests

First-time-user product review: scorecard and fix roadmap; --harsh for a roast

Measure compute units per instruction and flag the expensive ones

Format, lint and commit with a conventional message on a kit-named branch

Resync external skill submodules to latest upstream versions

Scaffold a Solana project (Anchor, fullstack, frontend, Pinocchio) with the kit

Set up GitHub Actions CI for Solana programs: lint, build, test, audit

Configure MCP server API keys in .env and add the optional MCP servers

Run tests, auto-fix fmt and lint, and fix failures until green or stuck

Run C# tests: Unity Test Framework in batchmode, or dotnet test

Run Rust tests for programs (LiteSVM, Mollusk, Surfpool, Trident) and backends

Run TypeScript tests for programs (Anchor TS, Kit) and dApp frontends

Update solana-ai-kit to latest version from upstream

Write docs for a Solana program, SDK or component from its code and IDL

Allow all file creation (short for /ar:allow)

Set AutoFile policy to allow-all mode (full file creation permissions)

Set AutoFile policy to justify-create mode (require justification for new files)

Set AutoFile policy to strict-search mode (only modify existing files)

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.