LLM Mart Basic
@llm-mart · Joined Jun 2026
Data analysis and reference enrichment.
Maximize information density: preserve all instructions, remove prose filler.
Generate headlines, titles, and subject lines: charge, volume, tighten.
FFmpeg-based video creation from image and audio.
Plan multi-part content series: structure, cross-linking, cadence.
Generate blog topic ideas: problem mining, gap analysis, expansion.
Writing: voice creation and validation, prose editing, anti-AI cleanup, professional communication, translation.
Domain-specific: SAP Commerce, OpenSearch detection, WordPress validation, enterprise search.
Design a CLI interface: args, flags, help, output, errors, exit codes, config.
Frontend: UI design, distinctive visual styles, HTML artifacts, Three.js 3D.
CPU-only motion data processing pipeline for game animation: BVH import, contact detection, root decomposition, motion blending, FABRIK IK. No GPU required.
Jev-driven browser automation: Jev picks operations, programs execute, a text model writes field values only when Jev cannot pick one from the goal.
Audit CVE/vulnerability source coverage for a technology stack. Maps each component (container, library, base image, runtime) to authoritative CVE feeds, flags gaps, and produces audit-ready reports. Generic: works for any service or stack.
Kubernetes operations: debugging, security, RBAC, and infrastructure tooling.
GitHub: notification triage, profile rule extraction.
Write, compose, integrate, and improve programs that call Jev, TypeSafe's System One judgment model.
Run benchmark-selected GPT-5.6 work through the Codex CLI.
Jev request router: validates the requested outcome, then dispatches to the matched agent, skill, and pipeline.
Toolkit management: create and evaluate skills and agents, manage routing tables, generate Claude.md.
Debugging: guided diagnosis of application bugs, and post-mortem of failed agent sessions.
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.
/implement-graphql-api
Implement graphql api
Implement GraphQL API endpoints
/init-project
Init project
Initialize new project with essential structure
/initref
Initref
Build reference documentation by creating markdown files and updating CLAUDE.md
/issue-to-linear-task
Issue to linear task
Convert GitHub issues to Linear tasks
/issue-triage
Issue triage
Triage and prioritize issues effectively
/linear-task-to-issue
Linear task to issue
Convert Linear tasks to GitHub issues
/load-llms-txt
Load llms txt
READ the llms.txt file from https://raw.githubusercontent.com/ethpandaops/xatu-data/refs/heads/master/llms.txt via `curl`. Do nothing else and await further instructions.
/log
Log
Log work from orchestrated tasks to external project management tools like Linear, Obsidian, Jira, or GitHub Issues.
/market-response-modeler
Market response modeler
Model customer and market responses with segment analysis, behavioral prediction, and response optimization.
/memory-spring-cleaning
Memory spring cleaning
Clean and organize project memory
/mermaid
Mermaid
Create entity relationship diagrams using Mermaid from SQL/database files
/migrate-to-typescript
Migrate to typescript
Migrate JavaScript project to TypeScript
/migration-assistant
Migration assistant
Assist with system migration planning
/migration-guide
Migration guide
Create migration guides for updates
/milestone-tracker
Milestone tracker
Track and monitor project milestone progress
/modernize-deps
Modernize deps
Update and modernize project dependencies
/move
Move
Move tasks between status folders following the task management protocol.
/optimize-build
Optimize build
Optimize build processes and speed
/optimize-bundle-size
Optimize bundle size
Reduce and optimize bundle sizes
/optimize-database-performance
Optimize database performance
Optimize database queries and performance
Your car as a chat-room agent: Raspberry Pi 5 + dashcam + local AI. CodeWatch's sibling for the garage.
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19 views 0 likesOpen-source desktop SQL workspace for PostgreSQL, MySQL/MariaDB, SQLite and 15+ more databases like DuckDB, ClickHouse, Redis and Firestore. Built-in MCP server…
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15 views 0 likesThe local-first sidebar AI agent for ComfyUI — runs on your own Claude OR ChatGPT subscription (no API keys, no extra LLM costs). Drives your live graph: edits,…
13 views 0 likesPersistent memory for Claude Code — identity, context, and continuity across sessions
16 views 0 likes🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI…
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25 views 0 likesWorld Memory Protocol.
23 views 0 likesRun your own organization of agents.
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13 views 0 likesFree open-source desktop app that scrapes JAV metadata and generates NFO + cover art for Jellyfin, Emby & Kodi. No Docker, no CLI — one-click install on Windows…
15 views 0 likesA cross-platform desktop app to manage Agent Skills in one place and sync them to multiple AI coding tools’ global skills directories — “Install once, sync ever…
13 views 0 likes天枢 (Tianshu) 是一个基于harness工程的终端编程智能体运行时(Tui X Gui),针对DeepSeek V4 做了前缀缓存工程优化(长会话实测稳态命中率 97–99%)和深度适配。它跳出了传统 AI 编程助手把大模型仅当成“工具”的局限,基于认知虚拟机 (CVM)、自感知层和信息素(Stigmergy…
11 views 0 likes