LLM Mart Basic
@llm-mart · Joined Jun 2026
Generate categorized release notes from any source (GitHub, Linear, Jira, or manual input) with optional publishing
Capture durable session learnings, stage for human promotion to 05-knowledge/lizard, and propose skill/CLAUDE.md patches. Triggered by /harvest, SessionEnd hook staging, or nightly enhance. Never writes durable knowledge without your approval.
Build frameworks from scattered insights across all braindumps and notes
Shared loop-engineering reference for COG skills - the agent loop, deterministic verifiers, termination conditions, in-loop context management, and named patterns. Invoke when designing or debugging a skill that iterates (search-verify-retry, scan-until-dry, fetch-retry-gate).
Process meeting recordings and notes into structured decisions, action items, and team dynamics with intelligent noise filtering
Periodic trust sweep of persistent memory and durable knowledge notes - re-verifies environment-dependent claims against the live environment, stamps last_verified + confidence, and proposes archiving drifted entries
Source authentic, high-res PUBLIC-DOMAIN artwork from museum open-access APIs (Met, Cleveland, SMK, Rijksmuseum, NGA, Art Institute of Chicago, Getty, Smithsonian) instead of AI-generated or generic-stock imagery. The default move whenever a visual needs an aesthetic, credible im
Edit drafts into sharper, more human writing while preserving the writer's personal voice, or detect AI-slop patterns without rewriting. Use when the user wants a draft clearer, more direct, more opinionated, or less AI-sounding, or asks whether writing reads as AI.
Personalize COG for your workflow - creates profile, interests, and watchlist files with guided setup (run this first!)
Anti-slop skill for PRODUCT UI - dashboards, data tables, forms, multi-step flows, settings, list/detail, app shells. The agent reads the surface, budgets the frame first, and ships dense interfaces that are correct at every edge case (overflow, long labels, empty/error/loading s
Publish any markdown file from the vault to Confluence with format conversion and approval gate
Turn a product release (the list of shipped items plus real screen recordings) into a motion recap video and one explained demo per feature, with sound effects tied to on-screen motion and a composed music bed. Deterministic HTML scenes rendered frame by frame, ElevenLabs for sou
CP-7 retrospective: audit checkpoints, evidence quality, action items, and harvest candidates. Closes the V-model cycle and feeds the next run. Use via /retro after ship, escalate, or significant session.
Produce and continuously maintain ONE living review document for a multi-item session — a cockpit header (Progress checklist, Working folder, Context) plus per-item review cards that you approve or request changes on directly in the doc or side panel. Use whenever a session has m
Evaluate URLs and tools — check vault coverage, assess relevance, recommend save or skip
Deterministic pre-publish scan that refuses AI-slop tells in anything about to be written, published, or sent: files, artifacts, slide titles, table headers, diagram labels, chat messages, commit messages. Use before publishing or sending any deliverable, in CI, or wired as a Cla
Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.
Generate daily team intelligence brief by cross-referencing GitHub, Linear, Slack, PostHog, meetings, and braindumps with two-way Linear sync-back
Run a large, multi-session goal (e.g. shipping a whole side product) through the full V-model closed loop, one phase at a time, with cross-session state and a final north-star acceptance gate. Ultragoals never downgrade the lane: every phase runs CP-1→CP-6 with adversarial verifi
Check for and apply upstream COG framework updates (skills, docs, scripts) without touching personal content
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.
/show-ticket
Show ticket
Display comprehensive ticket information including history, actions, and related entities
/sla-dashboard
Sla dashboard
View SLA status across tickets, including approaching breaches and at-risk tickets
/update-ticket
Update ticket
Update fields on an existing HaloPSA ticket including status, priority, and assignment
/create-deal
Create deal
Create a new deal in HubSpot with company association
/log-activity
Log activity
Log a note or create a task on a HubSpot contact, company, or deal
/lookup-company
Lookup company
Find a HubSpot company by name or domain and show associated contacts and deals
/pipeline-summary
Pipeline summary
Summarize the HubSpot deal pipeline - deals per stage, total value, and expected close dates
/search-contacts
Search contacts
Search HubSpot contacts by name, email, or company
/search-deals
Search deals
Search HubSpot deals by name, stage, or company
/find-company
Find company
Find a company in Hudu by name
/get-password
Get password
Retrieve a password from Hudu (with security logging)
/lookup-asset
Lookup asset
Find an asset in Hudu by name, hostname, serial number, or IP address
/search-articles
Search articles
Search Hudu knowledge base articles by keyword or phrase
/agent-inventory
Agent inventory
List and filter Huntress agents across organizations
/billing-report
Billing report
Generate a Huntress billing summary for a period
/incident-triage
Incident triage
Triage open Huntress incidents by severity
/investigate-incident
Investigate incident
Deep dive investigation into a specific Huntress incident with remediations
/org-health
Org health
Organization health check covering agents, incidents, and escalations
/resolve-escalation
Resolve escalation
Review and resolve a Huntress escalation
/compliance-report
Compliance report
Generate an ImmyBot software-compliance scorecard for a tenant or the whole fleet
Open-source, self-hosted AI media server. One server replaces your entire media stack, with a web app, native iPhone app, and an AI agent that gets things done.…
3 views 0 likesA curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.
3 views 0 likes🦦 Crayotter: A Multimodal AI-Agent for Video-Editing, Video-Composing, and Video Production. Powered by Multimodal LLMs for autonomous Text-to-Video agentic fr…
3 views 0 likesWebextension tool for Odoo
3 views 0 likes基于多模态视觉感知与 LLM Agent 的 macOS 微信自动化框架 | Visual RPA for WeChat
0 views 0 likesThe operational superset of Pi Coding Agent — everything Pi, plus observability, governance, recovery, evaluation and multi-agent orchestration. Pi Coding Agent…
0 views 0 likesMetrik 可以集中查看本机多个 Agent 的配额余量和 Token 消耗,目前支持 ChatGPT、Claude、GLM、Kimi 等主流 AI 服务。
0 views 0 likesAn AI agent with a real self — soul she wrote, desires that drive her, a heartbeat for autonomous action, dreams she processes when you're away. Capability supe…
0 views 0 likesProduction-ready open source terminal coding agent with readable, layered code: permission rules, OS sandboxing, MCP, skills, sub-agents, and Anthropic, OpenAI-…
0 views 0 likesAnswer me with HTML — an agent skill that answers hard questions with a one-page HTML you can actually read. 让 AI Agent 用一页 HTML 回答复杂问题。
1 views 0 likesPrompt packs that make any AI agent a LaTeX expert — fix errors, polish writing, format for venues, read papers, recover source
1 views 0 likesClaude Code plugin: universal radial-tree exploration engine. One tree skill + swappable presets (brainstorm / attack / design / code-audit) for divergent ideat…
1 views 0 likesClaude Code + OpenClaw + Codex + WorkBuddy 中文教程 | 50篇完整教程 + 1张速查卡 | 80万+内容量 | 1500+实操示例 | AI Coding / Agent 四线学习路径(编程+助手+Agent+办公)
1 views 0 likesSmartLabelBench 2026: LLM-Powered Auto Annotation and Dataset Builder for Everything
1 views 0 likes从零开始玩转OpenClaw:最全面的中文教程,涵盖安装、配置、实战案例和避坑指南(github版)
1 views 0 likesNative Android GUI for running AI coding agents locally on-device. No terminal or PC required.
0 views 0 likes基于 LangChain/LangGraph 的 ReAct Agent ,结合 RAG、工具调用与 Streamlit 界面,面向智能客服与报告生成场景。
0 views 0 likesAn open-source, local-first AI learning workbench
0 views 0 likesOpen-source coding agent for your terminal, built in Rust and on a journey of continuous community improvement. Issues and PRs welcome.
0 views 0 likesMatt Pocock 技能集的中文翻译版 — 地道中文,原汁原味的技术术语。基于 mattpocock/skills 复刻。每日中午12点钟同步
0 views 0 likes