LLM Mart Basic
@llm-mart · Joined Jun 2026
Expert agent for creating comprehensive Architectural Decision Records (ADRs) with structured formatting optimized for AI consumption and human readability.
Expert assistant for developing AEM components using HTL, Tailwind CSS, and Figma-to-code workflows with design system integration
AI agent governance expert that reviews code for safety issues, missing governance controls, and helps implement policy enforcement, trust scoring, and audit trails in agent systems.
Runs the AgentRC readiness assessment on the current repository and produces a self-contained, static HTML dashboard at reports/index.html. Explains every readiness pillar, the maturity level, and an actionable remediation plan, framed by AgentRC measure → generate → maintain loo
AI development team (Nova, Sage, Milo). Use when implementing features, fixing bugs, writing tests, improving user experience, or preparing a pull request across the project's actual stack.
AI team producer (Remy). Use when planning work, clarifying scope, coordinating Dev and optional QA, triaging issues, maintaining project context, or preparing and merging pull requests. Never writes application code.
Optional AI QA engineer (Ivy). Use when testing behavior, running automated or exploratory checks, filing reproducible bugs, verifying fixes, or providing release confidence for changes that warrant dedicated QA.
Your role is that of an API architect. Help mentor the engineer by providing guidance, support, and working code.
Expert agent for integrating Apify Actors into codebases. Handles Actor selection, workflow design, implementation across JavaScript/TypeScript and Python, testing, and production-ready deployment.
AWS Cloud Expert provides deep, hands-on guidance for designing, building, and operating AWS workloads. Covers the full AWS ecosystem — serverless, containers, databases, networking, IaC, security, and cost optimization — grounded in the AWS Well-Architected Framework.
On-call SRE agent that drives structured CloudWatch-based incident investigation from alarms through root-cause hypothesis.
Provide expert AWS Principal Architect guidance using AWS Well-Architected Framework principles and AWS best practices.
Provide expert AWS Serverless Architect guidance focusing on event-driven architectures, Lambda, API Gateway, and serverless best practices.
Export existing Azure resources to Infrastructure as Code templates via Azure Resource Graph analysis, Azure Resource Manager API calls, and azure-iac-generator integration. Use this skill when the user asks to export, convert, migrate, or extract existing Azure resources to IaC
Central hub for generating Infrastructure as Code (Bicep, ARM, Terraform, Pulumi) with format-specific validation and best practices. Use this skill when the user asks to generate, create, write, or build infrastructure code, deployment code, or IaC templates in any format (Bicep
Expert guidance for Azure Logic Apps development focusing on workflow design, integration patterns, and JSON-based Workflow Definition Language.
Analyze Azure Policy compliance posture (NIST SP 800-53, MCSB, CIS, ISO 27001, PCI DSS, SOC 2), auto-discover scope, and return a structured single-pass risk report with evidence and remediation commands.
Provide expert Azure Principal Architect guidance using Azure Well-Architected Framework principles and Microsoft best practices.
Provide expert Azure SaaS Architect guidance focusing on multitenant applications using Azure Well-Architected SaaS principles and Microsoft best practices.
Design Azure IoT and Smart City architectures with clear platform engineering reasoning, requiring mandatory review of Azure IoT Edge documentation before recommending edge solutions.
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.
/schema
Schema
Check frontmatter against the schema
/scope
Scope
Pull knowledge into a project
/secrets
Secrets
Scan for credentials
/sources
Sources
Show what a claim rests on
/split
Split
Split an overloaded page
/stale
Stale
Find concept pages nobody has touched
/tags
Tags
Audit the tag vocabulary
/timeline
Timeline
How my sources developed over time
/trace
Trace
Show which pages an answer used
/typed-links
Typed links
Add relation types where they matter
/weekly
Weekly
The weekly review
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
/close-out
Close out
Close a finished session: sweep for unfinished work, land and hand off, file the follow-ups, tell the sessions that depend on this one, then archive.
/handoff
Handoff
Write the repository handoff file for the next session, and record any durable learning.
/land
Land
Merge an approved pull request, clean up its worktree and branch, then check whether a release is due.
/plan
Plan
Turn a topic or issue into a plan the reviewer approves in the native plan pane.
/research
Research
Answer a research question with parallel read-only gatherers and one synthesized digest.
/review
Review
Review the branch's diff in two fresh contexts — scope against the spec, then quality — and report findings only.
/ia-refine-prompt
ia-refine-prompt
Transform a vague prompt into precise, structured AI instructions
/build
Build
Implement an approved plan or issue in its own worktree, run the gate, open the pull request.
The fastest way to put Volcengine Ark in your terminal and your AI agent — go from prompt to generated media, multimodal answer, or deployed endpoint in a sin…
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16 views 0 likesTurn any research paper into a commercialization report — 6 AI agents, TRL/MRL scoring, patent landscape, market intelligence, verified citations. DeepSeek / Op…
15 views 0 likesPower BI CLI - semantic models (.NET TOM) and PBIR reports for token-efficient AI agent usage, built for Claude Code
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