LLM Mart Basic
@llm-mart · Joined Jun 2026
A source-backed ASE skill for Beekeeper Studio, the SQL editor and database manager for Linux, macOS, and Windows. It fits workflows that need a real client for querying, browsing tables, and working across PostgreSQL, MySQL, SQLite, SQL Server, and other supported databases.
Manage and tag music libraries with beets, the Python-based CLI tool that auto-tags audio files using MusicBrainz metadata. Import, organize, deduplicate, and query your music collection with a powerful plugin system and flexible query language.
Use MemoryBench to run repeatable conversational memory and RAG benchmarks across providers, datasets, judge models, checkpoints, and structured reports.
Benchmark clean and incremental Xcode builds, surface compile and configuration hotspots, and produce an approval-first optimization plan before changing project files.
Compare browser-agent reliability on a repeatable task and anti-bot suite before choosing a stack or claiming progress.
Run a repeatable evaluation suite for browser agents against static web task snapshots instead of judging them from demos or one-off tests.
Run Claude Code, Codex CLI, Gemini CLI, or OpenCode through bounded H100 post-training tasks and compare how well each agent improves a base LLM.
Score deep research agents on benchmark tasks using factual verification, report-quality scoring, and process evaluation before model or workflow changes ship.
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.
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.
/sonar
sonar
SonarQube 정적분석 실행 및 결과 조회. 코드 품질·보안 핫스팟·커버리지 확인 시 사용.
/fix-issue
fix-issue
GitHub 이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):
/sdlc-cycle
sdlc-cycle
이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→PR)을 사람 개입 없이 자동 실행.
/fix-issue
fix-issue
GitLab 이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):
/sdlc-cycle
sdlc-cycle
이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→MR)을 사람 개입 없이 자동 실행.
/README
README
Invoke a repeated task with `/name`. File name = command name (`fix-issue.md` → `/fix-issue`).
/fix-issue
fix-issue
Handle issue #$ARGUMENTS (issue-first workflow):
/knowledge-graph
Knowledge graph
Renders the connection structure of the AGENTS.md ecosystem
/sdlc-cycle
sdlc-cycle
Automatically runs one SDLC cycle (issue → development → testing → verification → PR/MR) based on an issue or spec, without human intervention.
/sonar
sonar
Run SonarQube static analysis and check the results. Use to check code quality, security hotspots, or coverage.
/fix-issue
fix-issue
Handle GitHub issue #$ARGUMENTS (issue-first workflow):
/sdlc-cycle
sdlc-cycle
Automatically runs one SDLC cycle (issue → development → testing → verification → PR) based on an issue or spec, without human intervention.
/fix-issue
fix-issue
Handle GitLab issue #$ARGUMENTS (issue-first workflow):
/sdlc-cycle
sdlc-cycle
Automatically runs one SDLC cycle (issue → development → testing → verification → MR) based on an issue or spec, without human intervention.
/plan-status
Plan status
Show Hermes planning-with-files status for the current project.
/plan
Plan
Start Hermes planning-with-files workflow in the current project.
/plan-ar
Plan ar
بدء تخطيط الملفات بنمط Manus. إنشاء task_plan.md و findings.md و progress.md للمهام المعقدة.
/plan-attest
Plan attest
Lock the current task_plan.md content with a SHA-256 attestation. Hooks then refuse to inject plan content if the file diverges from the attested hash, blocking silent tampering. Use --show to print the stored hash, --clear to remove the attestation. Available since v2.37.0.
/plan-de
Plan de
Starte Manus-artige Dateiplanung. Erstelle task_plan.md, findings.md, progress.md für komplexe Aufgaben.
/plan-doctor
Plan doctor
Self-check for the planning-with-files mechanisms that fail silently: plan resolution, hook injection, canonicalizer path shape, attestation state, install surfaces, and per-fire hook latency. Run it whenever hooks seem quiet or after installing on a new machine. Available since v3.6.0.
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