LLM Mart Basic

Generates Blender Python (bpy) scripts that programmatically create Geometry Nodes modifier trees, using the node_groups API and GeometryNodeTree interface for parametric 3D asset generation.

Put an inline firewall and containment layer in front of agent network traffic, tool calls, and MCP traffic before you trust an agent with local secrets.

Add hard pre-execution guardrails to Claude Code so destructive shell commands are blocked before an agent can run them.

Use CC Safety Net when coding-agent CLIs need pre-execution hooks that block destructive commands, secret access, and unsafe file operations before tools run.

Scan staged changes, commits, or repositories for secrets before they leave the workstation or CI job, instead of relying on a later platform-side catch.

Add a runtime guard that evaluates agent actions, blocks dangerous commands or secret exposure, and audits new skills before they run.

How to use CrystalJson, the custom JSON library in SnowBank.Core (namespace SnowBank.Data.Json). Covers the JsonValue DOM (JsonObject / JsonArray / JsonString / JsonNumber / JsonBoolean / JsonNull / JsonDateTime), the read-only vs mutable model, the CrystalJson static API (Serial

Advanced engineering for sophisticated FoundationDB layers with the .NET client (FoundationDB.Client / SnowBank) — the cluster model and transaction lifecycle (proxies, resolvers, tlogs, storage servers, the sequencer/version clock), latency/throughput optimization (batching read

How to run a FoundationDB cluster and connect to it from .NET — getting the IFdbDatabaseProvider that the keys/transactions/layers skills assume you already have. Covers the ways to get a provider (plain DI services.AddFoundationDb, FdbDatabaseProvider.Create, or Aspire), the Asp

How to correctly encode keys and values, use subspaces and the Directory layer, and write custom "Layers" with the FoundationDB .NET client (FoundationDB.Client / SnowBank). Covers the lazy strongly-typed key structs (subspace.Key(...), FdbTupleKey, FdbRawKey, FdbKey.Increment /

How to correctly run transactions with the FoundationDB .NET client (FoundationDB.Client / SnowBank): the db.ReadAsync / WriteAsync / ReadWriteAsync retry loop and why a handler must be safe to run more than once, the 5-second and size limits, conflicts and how to avoid them, sna

How to guard arguments and assert invariants with the Contract family in SnowBank.Core (namespace SnowBank.Diagnostics.Contracts): the argument guards (Contract.NotNull / NotNullOrEmpty / NotNullOrWhiteSpace / Positive / GreaterThan / GreaterOrEqual / LessThan / LessOrEqual / Equ

How to write, run, and especially DIAGNOSE multi-node integration tests built on the SnowBank distributed-test framework (SnowBank.Testing.Framework / SnowBank.Testing.Common — a general-purpose harness, NOT FoundationDB-specific). Covers DistributedTest/MakeItSo + virtual hosts

How to correctly use the Slice type and its companions (SliceReader, SliceWriter, SliceOwner) for binary data in the FoundationDB .NET client / SnowBank.Core codebase. Slice is a readonly struct (namespace System) — the logical equivalent of a ReadOnlyMemory of bytes with many he

How to use CrystalJson, the custom JSON library in SnowBank.Core (namespace SnowBank.Data.Json). Covers the JsonValue DOM (JsonObject / JsonArray / JsonString / JsonNumber / JsonBoolean / JsonNull / JsonDateTime), the read-only vs mutable model, the CrystalJson static API (Serial

Advanced engineering for sophisticated FoundationDB layers with the .NET client (FoundationDB.Client / SnowBank) — the cluster model and transaction lifecycle (proxies, resolvers, tlogs, storage servers, the sequencer/version clock), latency/throughput optimization (batching read

How to run a FoundationDB cluster and connect to it from .NET — getting the IFdbDatabaseProvider that the keys/transactions/layers skills assume you already have. Covers the ways to get a provider (plain DI services.AddFoundationDb, FdbDatabaseProvider.Create, or Aspire), the Asp

How to correctly encode keys and values, use subspaces and the Directory layer, and write custom "Layers" with the FoundationDB .NET client (FoundationDB.Client / SnowBank). Covers the lazy strongly-typed key structs (subspace.Key(...), FdbTupleKey, FdbRawKey, FdbKey.Increment /

How to correctly run transactions with the FoundationDB .NET client (FoundationDB.Client / SnowBank): the db.ReadAsync / WriteAsync / ReadWriteAsync retry loop and why a handler must be safe to run more than once, the 5-second and size limits, conflicts and how to avoid them, sna

How to guard arguments and assert invariants with the Contract family in SnowBank.Core (namespace SnowBank.Diagnostics.Contracts): the argument guards (Contract.NotNull / NotNullOrEmpty / NotNullOrWhiteSpace / Positive / GreaterThan / GreaterOrEqual / LessThan / LessOrEqual / Equ

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.

A green PR, a controller reporting success, and not one line of the new code running

Systematic workflow for fixing bugs including issue creation, branch management, and PR submission

Bulk import GitHub issues to Linear

Explore multiple business timeline scenarios with constraint validation and decision optimization.

Demo changelog automation features

Perform comprehensive analysis of $ARGUMENTS to identify code quality issues, security vulnerabilities, and optimization opportunities.

Run project checks and fix any errors without committing

Setup continuous integration pipeline

Clean up merged and stale git branches

Fix all linting and formatting issues across the codebase

Test multiple code variations through simulation before implementation with quality gates and performance prediction.

Perform comprehensive code quality review

Convert code analysis to Linear tasks

Perform comprehensive code analysis with quality metrics and recommendations

Automatically create and execute a git commit using the first suggested commit message

Create well-formatted git commits with conventional commit messages and emoji

Model world constraints with assumption validation, dependency mapping, and scenario boundary definition.

Containerize application for deployment

Load project context by reading README.md and exploring relevant project files

Generate comprehensive architecture documentation

Create a new command following existing patterns and organizational structure

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.