LLM Mart Basic
@llm-mart · Joined Jun 2026
Use apko to build small OCI images from declarative package manifests when supply-chain clarity and minimal contents matter more than a conventional Dockerfile flow.
Use DeepAgents to build long-running task agents with a batteries-included harness for planning, tools, and workflow structure.
Extract structured intelligence from audio using the AssemblyAI API with sentiment analysis, entity detection, topic modeling, and auto-chapter generation. Uses the assemblyai Python SDK for transcript processing pipelines.
Summarizes audio content using AssemblyAI's LeMUR (Large Language Model for Audio Understanding) API. Chains the /v2/transcript endpoint with /lemur/v3/generate/summary for contextual audio intelligence.
Streams audio from Twilio Media Streams over WebSocket to AssemblyAI real-time transcription, extracting speaker-diarized transcripts with word-level timestamps. Triggers entity detection and sentiment analysis via AssemblyAI LeMUR on completed call segments. Results are pushed t
Transcribes audio and generates auto-chapters with summaries using AssemblyAI's /v2/transcript endpoint with auto_chapters=true. Extracts key topics, sentiment analysis, and content safety labels via AssemblyAI SDK.
Use ast-grep (sg) to search, lint, and rewrite code across large codebases using AST pattern matching. A blazing-fast alternative to regex-based code transformations that understands syntax structure.
Astro is a modern web framework for building content-driven websites. It ships zero JavaScript by default, supports multiple UI frameworks (React, Vue, Svelte, Solid), and provides islands architecture for optimal performance.
Generates event-driven architecture documentation from AsyncAPI 3.0 specifications. Uses the AsyncAPI parser-js library to extract channels, message schemas, and server bindings for Kafka and RabbitMQ.
Parses AsyncAPI 2.x/3.x specifications to generate event-driven architecture catalogs using the AsyncAPI Generator. Produces channel documentation, message schema validators, and EventBridge rule templates.
mcp-atlassian is a Model Context Protocol server that connects AI assistants to Atlassian Jira and Confluence. It enables searching and managing Jira issues, reading and editing Confluence pages, and performing project management tasks through natural language via any MCP-compati
The Atlassian Rovo MCP Server bridges your Atlassian Cloud workspace with any MCP-compatible client. Search and summarize Jira issues, create tickets from natural language, update Confluence pages, and query Compass services.
Atuin replaces your existing shell history with a SQLite database that records additional context like exit codes, session IDs, working directories, and command durations. It provides encrypted cross-machine sync and a full-screen fuzzy search UI bound to Ctrl-R.
Identifies audio content using Chromaprint/AcoustID fingerprinting, Shazam API recognition, and ACRCloud monitoring. Matches music, speech, and ambient audio against fingerprint databases.
Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta's Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format co
Integrate Audiobookshelf's self-hosted audiobook and podcast server into AI agent workflows. Agents can manage libraries, track listening progress, search metadata, and automate podcast episode downloads through the comprehensive REST API.
audioFlux is a deep learning tool library for audio and music analysis and feature extraction, supporting dozens of time-frequency transforms and hundreds of feature combinations for classification, separation, MIR, and ASR tasks.
audiowaveform is a BBC open-source C++ CLI tool that generates waveform data from MP3, WAV, FLAC, Ogg Vorbis, and Opus audio files. It outputs binary or JSON waveform data and renders PNG waveform images at configurable zoom levels.
Use GEO Optimizer from the CLI or MCP so agents can audit a site for AI search visibility, generate llms.txt/schema fixes, check bot access, and track citation readiness.
Use HarnessKit to inventory, audit, enable, disable, and deploy skills, MCP servers, plugins, hooks, CLIs, configs, memory, and rules across multiple coding agents.
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.
/plan-es
Plan es
Iniciar planificación de archivos estilo Manus. Crear task_plan.md, findings.md, progress.md para tareas complejas.
/plan-goal
Plan goal
Bridge Claude Code's /goal to the active plan. Derives a goal condition from task_plan.md and invokes /goal so Claude keeps working until the plan is complete. Available since v2.38.0.
/plan-loop
Plan loop
Run a planning-aware cadence with Claude Code's /loop. Default tick checks plan status, runs check-complete, nudges progress.md update if stalled. Available since v2.38.0.
/plan-zh
Plan zh
启动 Manus 风格的文件规划。为复杂任务创建 task_plan.md、findings.md、progress.md。
/plan-zht
Plan zht
啟動 Manus 風格的檔案規劃。為複雜任務建立 task_plan.md、findings.md、progress.md。
/plan
Plan
Start Manus-style file-based planning. Creates task_plan.md, findings.md, progress.md for complex tasks.
/pwf
Pwf
Short alias for /plan. Starts Manus-style file-based planning: task_plan.md, findings.md, progress.md. Available since v3.0.0.
/start
Start
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Now with automatic session recovery after /clear
/status
Status
Show current planning status at a glance - phases, progress, and any logged errors.
/adversarial
Adversarial
Run three-agent adversarial analysis -- advocate builds the case, adversary challenges it, judicial analyst synthesizes
/briefing
Briefing
Structured pre-execution briefing session -- collects case context through specialist panel, builds execution plan, supports resume and depth control
/cantonal
Cantonal
Analyze cantonal law for all 26 Swiss cantons -- cantonal court decisions, cantonal legislation, procedural specifics, and interaction with federal law
/cite
Cite
Validate, format, and look up Swiss legal citations including BGE/ATF/DTF decisions and statutory references
/create-workflow
Create workflow
Create a reusable custom workflow by combining BetterCallClaude agents. Interview-based: pick agents, order them, define the output. Saved for future use with /bettercallclaude:workflow.
/doc-analyze
Doc analyze
Analyze Swiss legal documents -- identify legal issues, extract key clauses, verify citations, and assess compliance
/doctor
Doctor
Diagnose MCP server connectivity — tests each server, reports status and impact in plain language, suggests fixes for issues.
/draft
Draft
Draft Swiss legal documents including contracts (OR), court submissions (ZPO), and legal opinions (Gutachten) with multi-lingual support
/federal
Federal
Force Federal Law Mode for Swiss federal legal analysis, overriding cantonal auto-detection
/help
Help
Show complete BetterCallClaude command reference, available agents, skills, and usage examples
/legal-5step
Legal 5step
Execute the BetterCallClaude 5-step Swiss legal framework: intake → research → strategy → adversarial → draft. A complete end-to-end pipeline for any Swiss legal matter, from document analysis through final legal output.
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