LLM Mart Basic

Use EnterpriseRAG-Bench to evaluate an enterprise RAG or knowledge-agent system against a realistic synthetic company corpus with answer, recall, and comparative scoring.

Run realistic enterprise-style IT scenarios before trusting an automation agent in production operations.

Run CIS benchmark checks against cluster nodes and control planes when an agent needs a narrow Kubernetes hardening audit, not a general platform listing.

Run a real-task benchmark suite against OpenClaw agents so model or harness changes can be compared before they hit production workflows.

Run structured prompt-injection attack and defense experiments against an LLM-integrated app before production by measuring attack success and testing detection or recovery pipelines.

Run concurrent scripted conversations against a target agent to measure whether it stays on task, responds correctly, and holds up in repeatable test cases.

Better Auth is an open source authentication framework for TypeScript apps. It gives agents a concrete way to wire sign-in, sessions, passkeys, OAuth providers, and plugins into modern web stacks with real package and docs support.

A fast, configurable secrets scanner built by the creator of Gitleaks and backed by Aikido Security. Betterleaks detects leaked passwords, API keys, and tokens in git repositories, directories, and stdin with CEL-based validation and parallelized scanning.

Automates migration from ESLint and Prettier to Biome (formerly Rome) by parsing .eslintrc and .prettierrc configs, mapping rules to biome.json equivalents, and running biome check --apply for bulk reformatting.

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

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.

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Chart a big legal matter as a wayfinder decision map — grill the attorney breadth-first, create the map and decision tickets, fire research tickets in parallel. Planning only: charting resolves no decisions itself.

Define a checkable legal success condition for /legal-loop. Accepts a named profile (citations-clean, draft-passes-gate, adversarial-converge, nda-batch-clean, reg-watch, timeline-sourced) or free-text objective. Produces a persisted Goal Record — never starts work itself.

Iterate a worker-evaluator cycle against a Goal Record until the success condition is met or a stop limit is reached. The evaluator (a different agent than the worker) judges each iteration using MCP verification tools. Produces an auditable verdict trail and a final MET / NOT MET status.

Build a sourced legal chronology from case documents — every event with mandatory provenance, undisputed/alleged/contested status, explicit date conflicts, evidentiary gaps, and optional deadline markers. Outputs table, interactive HTML, and docx under bcc-output/timeline/.

Work one ticket from a legal-wayfinder decision map — claim a frontier ticket, resolve it by type (research / grilling / prototype / task), record the decision, graduate newly-sharp fog, and emit the handoff pack when the map is clear.

Primary entry point for all BetterCallClaude requests — classifies intent, resolves jurisdiction (via swiss-legal-research), runs inline briefing for complexity 4–6, activates full briefing session when complexity ≥ 7 (via legal-intake skill), and routes to specialist agents or workflow pipelines. Invoked explicitly as /bettercallclaude:legal or as the default when no other command matches. Supports --refine, --briefing, --skip-briefing/--direct, --no-framework flags.

Triage NDAs against Swiss law — classify as GREEN (standard) / YELLOW (review) / RED (issues) using playbook thresholds and Swiss legal criteria. Supports single file or batch (folder) mode.

Search and analyze Swiss BGE/ATF/DTF precedents with precedent chain tracking and evolution analysis

View or change the BetterCallClaude privacy mode (strict/balanced/cloud)

Refine vague legal queries into structured prompts through Socratic dialogue, with workflow recommendations and multi-lingual terminology guidance

Search Swiss legal precedents (BGE/ATF/DTF), analyze statutes, and verify citations with multi-lingual support

Check MCP server connectivity

Welcome and first-use onboarding — checks MCP connectivity, guides playbook creation, shows usage examples tailored to your profile. Replaces /setup.

Develop litigation strategy with risk assessment, procedural analysis, cost-benefit calculation, and settlement evaluation for Swiss courts

Summarize and consolidate multi-agent pipeline output -- deduplicate disclaimers, terminology, and citations with length control (--short, --medium, --long)

Translate Swiss legal documents between DE, FR, IT, and EN while preserving legal terminology precision

Validate Swiss legal citations in bulk -- check format, existence, and cross-language consistency

Display BetterCallClaude plugin version, installed components, and system status

Define and execute multi-agent legal workflows -- due diligence, litigation prep, contract lifecycle, real estate closing

Audit web accessibility for WCAG compliance with automated axe-core tests, keyboard and screen reader checks, and remediation guidance

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…

Governance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…

Ultimate Multi-Agent OS for Autonomous AI NPCs 2026

Personal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant

Proven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control

Slash API Batch: Cut AI Costs by 50% in 2026

Web dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics

Agent Skills for Solopreneurs

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card

Zero, your trustworthy AI teammate for real work.

一套 DSH runtime，Desktop、Web 与 TUI 三种开发体验。

Open-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.

⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki

Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…

Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…

NocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…

An open-source AI coding agent that lives in your terminal.

PawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…